Category Archives: Computer Science
Bachelors programs in computer science (CS) cover the theoretical and mathematical underpinnings of computing. Schools offer various degree titles, including bachelor of arts in computer science, bachelor of applied science in computer science, and bachelor of computing in computer science.
Schools may also offer interdisciplinary bachelors degrees that allow CS students to combine interests, such as a bachelor of mathematics in computer science, a bachelor of technology in computer science and engineering, or a bachelor of engineering in computer science.
Bachelor of computer science (BCS) courses vary by school and program, but they typically cover areas like computer programming, software engineering, computer hardware, and artificial intelligence engineering. Students may examine topics such as computability, information, automata, and algorithm design.
The page below discusses bachelor of computer science degrees, including common curricula, potential career paths for graduates, and admission requirements. This degree overview also provides program rankings and describes helpful resources, such as professional organizations and scholarships for computer science students.
Most CS bachelors programs include core coursework in computer architecture and programming, data structures, algorithms, and logic and computation. However, given the breadth of the CS discipline, bachelors programs can differ significantly in terms of focus and available specializations. For example, some programs may heavily emphasize math, requiring courses in areas such as calculus, statistics, probability, and discrete mathematics.
Students often get to choose from a variety of electives and specializations in areas including data communications, software testing, operating systems, and computer networking. Theoretically minded students may opt to investigate computation theory, information theory, or human-computer interaction. Other students might pursue specializations in artificial intelligence, real-time computing, or computer graphics.
A bachelors degree in CS is extremely versatile and prepares students for diverse CS and IT careers. Potential roles for graduates include software developer, hardware engineer, computer systems or information security analyst, and network architect.
Graduates may also choose to pursue a relevant masters degree, which is a common requirement for computer and information research scientists. These professionals address complex problems by inventing innovative computing designs and new applications for technology. According to the Bureau of Labor Statistics (BLS), research scientists earn a median annual salary of $122,840, and jobs in the profession are projected to grow 16% between 2018-2028.
Explore programs of your interests with the high-quality standards and flexibility you need to take your career to the next level.
Computer science bachelors programs look for candidates with strong academic records and standardized test scores. Applicants typically need a high school diploma (or equivalent) and a minimum 2.0-3.0 GPA. Most programs also require freshman applicants to submit SAT or ACT scores. Additionally, candidates may need high school prerequisites in English, natural sciences, social sciences, foreign languages, and math.
Computer science bachelors programs often look favorably on prospective students with relevant professional experience and/or prior college coursework, and may waive standardized test score requirements for such applicants.
Most programs allow applicants to submit their application online. Materials may include official transcripts, standardized test scores, and a nonrefundable application fee, typically between $30-$75. Many schools also require letters of recommendation and an essay.
Graduates with an associate degree can pursue some technology-related roles, such as computer systems analyst, web developer, and computer support specialist. However, many entry-level IT and CS job postings expect or require applicants to hold a bachelors degree.
Graduates with a bachelors degree can work as software developers, database administrators, information security analysts, hardware engineers, or network architects. Some bachelors graduates use their degree to qualify for masters programs, which allow for further advancement in the field.
For professionals already working in the field, earning a bachelors degree in computer science can lead to salary advancement or promotion to management-level jobs with more responsibility, such as IT project manager or computer and information systems manager.
According to PayScale, professionals with a bachelors in computer science make an average of $85,000 annually, while associate degree graduates in CS make about $65,000 per year. According to the BLS, computer and information systems managers make a median annual salary of $146,360.
Banatao Family Filipino American Education Fund Scholarships
Each year, the family of Dado and Maria Banatao awards five $5,000 renewable scholarships to eligible Filipino students. Available to students from specific counties in California, each of the five scholarship recipients must be of at least 50% ethnic Filipino heritage.
Eligibility requires full-time enrollment in an accredited, four-year college and a major in a STEM subject, such as computer science. Scholarship recipients must also demonstrate financial need and hold a minimum 3.0 GPA.
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Generation Google Scholarship
In an effort to increase diversity in the computer science field, this Google scholarship supports aspiring computer science majors, emphasizing underrepresented groups in tech. Applicants must plan to study in the United States or Canada, and awardees receive $10,000 USD or $5,000 CAD. Recipients also receive an invitation to the Google Scholars Retreat.
Applicants must hold a high school diploma and demonstrate current or intended enrollment in a relevant bachelors or graduate degree program at an accredited college or university. Google chooses recipients based on demonstrated leadership, academic merit, and prospective influence on diversity in the field.
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Google Lime Scholarship
Serving students with disabilities, this scholarship awards $10,000 USD or $5,000 CAD to qualified students in the United States and Canada. Applicants must be full-time students pursuing a computer science degree at an accredited institution. They must also demonstrate leadership potential, academic merit, and a passion for their subject of study.
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CyberCorps: Scholarship for Service
A collaborative offering from the Department of Homeland Security and the National Science Foundation, the CyberCorps program offers full-tuition scholarships to full-time computer science students at participating universities. Each institution stipulates its own application process.
Participants in the program must complete summer internships and pledge to work in government for a duration equivalent to the years of scholarship funding received. If willing to work in the sector longer, some recipients can also collect $20,000-$30,000 stipends.
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Are computer science degrees worth it?
Computer science degrees pave the way for extensive job opportunities, and PayScale data indicates that computer science bachelors degree-holders make $20,000 more annually than those with associate degrees in the same field.
Is computer science a hard major?
Computer science courses are difficult, but diligent students with quantitative aptitudes typically find computer science both challenging and rewarding.
What is the best computer science degree?
When choosing the appropriate degree to pursue, students should consider their career aspirations. According to PayScale, professionals with a bachelor of engineering in computer science make an average of about $100,000 annually about $15,000 more than graduates of some other CS bachelors programs.
How long does it take to get a bachelors degree in computer science?
Bachelors programs typically take four years of full-time study to complete, but some programs offer accelerated and/or part-time options.
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What is Computer Science
Computer Science is a course which deals with the study of the algorithmic process and the computational machines that are included in this course. Computer Science is a study which ranges from topics dealing with the theoretical studies of algorithms and information to the practical issues of implementing computing systems in the hardware as well as software.
Computer Science is used in our daily lives as well to convert the raw facts and the data into useful information that can be used by humans daily. Some various subjects and topics are included in this course so that the candidate gets used to the use of computers and its applications. This course is best and ideal for the students who have an interest and also enjoy math and problem-solving.
The main focus of computer science course is to give rise to professionals who can work in the sectors that provide different services to the companies. The candidates can showcase their skills after getting hired in different job roles that include Software Developer, Systems Analyst, and many other job roles which help candidates in increasing their experience. Therefore, a course in Computer Science is very helpful for the candidates who have the interest to learn about Computer and its Applications.
For the students who wish to take admission into the course in Computer Science, it is important that they should clear the entrance examination and meet the prescribed eligibility criteria:
For the students willing to pursue a bachelors degree in this course, the eligibility criteria is clearing 10+2 in the Science stream with at least 50% marks.
The student should have studied Physics, Chemistry and Mathematics as their subjects during 10+2. They should also appear for any entrance examination conducted by the college where they wish to take admission.
The candidates must have cleared a Bachelors degree in the same field or an equivalent field and must have scored at least 50% marks.
They should score at the very least the minimum required marks as per the college/university and also clear the entrance examination to get admission into the course.
For the candidate to get admission in computer science course, they must appear for the entrance examination set up by the various universities/colleges. Some of the colleges conduct entrance examinations while others grant admission based on merit. Listed below are some of the entrance examinations :
JEE Main - This entrance examination is conducted to grant admission into undergraduate Engineering courses at numerous colleges, including the prestigious IITs.
BITSAT - It is an entrance examination that is conducted online by BITS Pilani to grant admission to the candidates who are eligible for the course.
VITEEE - Vellore Institute of Technology Engineering Entrance Examination is a common entrance examination that is conducted to grant admission into the VIT campuses.
DUET- Delhi University Entrance Test is an entrance examination that is conducted by Delhi University to grant admission to the students in their undergraduate as well as postgraduate courses offered by the university.
IIT JAM - Indian Institute of Technology Joint Admission Test is conducted to grant admission into its M.Sc. and the other postgraduate courses that are offered at IIT, Bangalore.
The scope of Computer Science course is excellent not only in India but also abroad well, as the professionals in this field are hired in different job roles wherein, they get a lot of exposure and also gain a lot of knowledge regarding the same. The career prospects in computer science for the candidates are numerous once they complete this course. Once they have completed the course, they can become working professionals in the field by working in any one of the several sectors which are a part of this course.
The candidates can further work as a Computer Programmer, Data Scientist, IT Specialist, and in various other job roles once they are hired. There is a need for professionals in the field as there are more and more computer applications coming up in the field. As the IT sector is booming, so are the job opportunities in the computer science field increasing. Therefore, the scope of the computer science course is huge not only in India but also throughout the world.
B.C.A. in Computer Science at Dharmamurthi Rao Bahadur Calavala Cunnan Chetty's Hindu College, Chennai
B.Sc. in Computer Science at Bharathi Women's College, Chennai
B.Sc.(Hons) in Computer Science at Ashoka University, Sonepat
Dual Degree in Computer Science at Coimbatore Institute of Technology, Coimbatore
M.Sc. in Computer Science at Queen Mary's College, Chennai
M.Phil. in Computer Science at Rani Anna Government College for Women, Tirunelveli
M.Sc. in Computer Science at NIIT University, Neemrana
M.Sc. in Computer Science at International Institute of Information Technology Bangalore
Ph.D in Computer Science at Kovai Kalaimagal College of Arts and Science, Coimbatore
Ph.D in Computer Science at Chikkanna Government Arts College, Tirupur
Ph.D in Computer Science at Bhupal Nobles University, Udaipur
Ph.D in Computer Science at University of Hyderabad, Hyderabad
Diploma in Computer Science at SEMCOM, Anand
Diploma in Computer Science at University of Madras, Chennai
Diploma in Computer Science at PP Savani University, Surat
M.Sc. in Computer Science at Mata Jijabai Government Girls PG College, Indore
The computer Science course subjects included in the course are there to help the students in understanding the course more accurately. It covers the aspects of the course in giving the candidate in-depth knowledge about the course. The computer science course develops skills in the students which they can use further in their job profiles. Some of the subjects included in the course are :
Introduction to Digital Electronics
Value and Ethics
Operating Systems Concepts
Introduction to Web Technology
The candidates can opt to pursue higher education in computer science after they complete a bachelors degree in the field. The candidate can apply for different career opportunities in the field once they complete the course. The salary is also decided accordingly. There are several career opportunities in computer science field where the candidate can apply for.
Most of the people who have a degree in Computer Science work in different job profiles according to their preference and choice. They work as programmes or computer system analysts which help them to get experience in the field while working.
There are also some more potential career opportunities in the computer science course that include Software Engineer, Database Administrator, and many other career opportunities. Therefore, once the candidate completes the course successfully, there are numerous career opportunities available after this course which will help them to get better opportunities in the future as well.
Computer Science itself is a field that keeps on bringing new projects and new applications for users. With the new and young talents coming in the field, it is becoming even more trending with new updates coming up in the field. Also, the technology has been growing immensely with the need for more professionals in the field to work for the companies in private as well as the public sector.
There has been an increase in the number of candidates who are willing to pursue computer science course. The trends keep changing because of the different innovations and technologies in the market. With the new upcoming trends arriving into the market, it gives the users a better experience of computers and its software. Given below are some of the upcoming trends in computer science:
Artificial Intelligence and Robotics
Big Data and Analytics
Cyber Security are some of the upcoming trends.
Once the candidate completes the computer science course successfully, it becomes easy for them to apply for a job role in different organisations. Some of the colleges provide placement to the students while some of the colleges dont. The computer science course helps the students to apply for several jobs and career options. There are several job profiles which are mentioned below:
Website Developers are the ones who are responsible for looking after the technical part of a website. They have to look after the codes, the technical side, coding, and the other aspects which come under this job role.
Network Engineers are the ones who are responsible for setting up and looking after the computer networks and also maintaining them.
The role of the Technical Writer is to write manuals, journals, articles, and content related to the technical side, which is necessary for the field.
Software Engineers are responsible for developing different solutions related to software with the help of different tools and methods. They also have to prepare and install different solutions by designing programming.
IT Supervisors are the ones who have to supervise the staff and also give training to the recruits in the company. They also have to look after the efficient working of the IT department of the company.
Some of the top recruiters in computer science field are:
The salary package varies from one job profile to another. The salary package is decided based on the candidates overall performance in all the aspects, which includes academic as well as the other activities. Also, the prior work experience is counted, i.e., if the candidate has worked earlier or has done any internship. Therefore, the salary package is decided accordingly.
Rs. 5 to 10 lakhs p.a. (approx.)
Rs. 4 to 9 lakhs p.a. (approx.)
Rs. 4 to 9 lakhs p.a. (approx.)
Software Quality Assurance Tester
Rs. 3 to 10 lakhs p.a. (approx.)
Rs. 3 to 9 lakhs p.a. (approx.)
The computer science candidates are needed to possess some required skill sets, which helps them to get better at their workplace. Having certain skill sets and including it in your resume increases your chances of getting hired in a particular job role. Mentioned below are some of the required skill sets:
Computer and Technology Knowledge - The candidate must have this skill when it comes to working in the field of computer science. Therefore, the candidate needs to have the required knowledge to work in the field.
Data Analysis - The candidate needs to interpret the data and then analyse the data that has been given to you. The candidate needs to analyse data and then use it for further information.
Software Development - A fair understanding of software and its applications and also the use of software development is important to work better. You should be able to understand the process and also work with others simultaneously to understand it in a better way.
Communication Skills - Communication is the key to everything. This skill helps you to communicate with your clients, colleagues, and also other members of the organisation to convey the information to them accurately.
Creativity - Having a creative mind is very important in this field. They should be able to create creative functions, web programs, and also websites. You need to think outside the box and also give unique ideas to create something creatively.
The computer science course curriculum is designed by the colleges or universities to give complete knowledge and understanding of the course and also its importance. The course curriculum includes the lessons and the academic content that is being taught to the students so that it helps them to get better at the course. It includes the topics that are offered in the course and which are being taught to the students.
The computer science course curriculum is designed to teach the students about the various elements that are included in the course. It is a mixture of classroom training, lab classes, and also practicals. The students are also asked to do practicals as it helps them to get a better understanding of the computer science course. Therefore, a course curriculum is important to help the students understand the course thoroughly.
Exam Date: 05 Feb, 2022 - 06 Feb, 2022
Application Process: 05 Oct, 2021 - 30 Nov, 2021
Application Process: 09 Sep, 2021 - 17 Oct, 2021
Declaration of Result: 28 Oct, 2021
Different job profiles come along with the course once they complete it successfully. The candidate can apply for any of the job profiles according to their own choice. Some of the job profiles are as follows:
It depends on the colleges if they wish to conduct entrance examinations or not according to the norms of the college. Some of the colleges conduct entrance examinations while some dont. Therefore, there is no such compulsion to appear for the entrance examination unless and until the college where you wish to take admission conducts the entrance examination.
Some of the entrance examinations conducted for the admission to the course are listed below :
Shital Waters was a newcomer to computer science. The COVID-19 pandemic forced her to find novel ways to connect with her fellow graduate students. She joined several organizations that communicated via Zoom.
I still cant believe it sometimes, says Waters of the career possibilities that have ensued.
With five Northeastern classmates, Waters developed a project that has turned into a startup, BluePlanetAI, that will deploy underwater drones to detect dangerous bacteria before it can develop in oceans, lakes, and other bodies of water.
Waters has starred in a series of cultural YouTube videos that present serious issues in a lighthearted way. Courtesy Photo Shital Waters
In support of her efforts to create BluePlanetAI, Waters has received an inaugural $5,000 Innovator Award from Northeasterns Women Who Empower inclusion and entrepreneurship initiative. The awards recognize 19 women who are graduates or current students at Northeastern. The organization is distributing a total of $100,000 in grants to help fund 17 ventures.
BluePlanetAI is focused on mitigating harmful algae bloomsincluding red tidethat proliferate in sea and fresh water to create toxins that can harm people, fish, shellfish, marine mammals, and birds.
Waters team is developing a system in which drones would identify the harmful bacteria before the blooms can cause widespread damage. BluePlanetAI is in the early stage, and the Innovator Award is being applied to research and develop its technology.
Most of us were planning to work on this project throughout the masters program for two to three years, Waters says. But its become so much more than just a school project.
Waters, whose mother is from India, has had a diverse career. She has starred in a series of cultural videos that present serious issues in a lighthearted way. The most popular of their efforts, Dark Skinned & Indian, an eight-minute comedy of love overcoming prejudice, has earned more than two million views on YouTube since its 2014 release.
We were always coming up with ideas of what we could shoot next, says Waters, who had previously filmed a commercial with the production team. We decided there are so many problems in our own culture and community, why dont we try to raise awarenessbut in a way that is lighthearted, so people are entertained but still get the message.
In 2010, Waters survived a townhouse fire that was ignited by the explosion of a neighbors propane tank.
I had just got back from Indiamy parents were still in Indiaand I was sleeping when I heard a little crackle and my neighbors dog barking, says Waters, who woke up to see flames closing in on both sides of her second-floor room. She escaped without harm but she and her family lost everything they owned, including her fathers business as a mechanic, which he had operated from the garage. Waters worked three jobs to help support the family while she earned a bachelors degree in biology and biological sciences at San Jose State.
In one of her jobs, as a lead brand ambassador in the Bay Area for Models In Tech, Waters was trained to use, explain, and demonstrate tech products at trade shows and other public events.
I was around people who had years of experience, and I realized very quickly that it was a male-dominated field, Waters says. When I would ask them questions, hoping to get some quality advice, I felt like I wasnt taken seriously and kind of pushed to the side. Or if I felt they were going to give me some great advice, it came with expectationsthey had some intention behind it. It discouraged me a bit.
She enrolled in the Align program at Northeasterns location in San Francisco to pursue a masters in computer science. Waters says she has been inspired by her role in BluePlanetAI as a co-founder and software engineer, her inclusion in a variety of campus groups, and the support of Women Who Empower.
The award was so great because of the support I was getting from such powerful women, says Waters. Its something I strive to do as wellI hope I can help other young women to be successful.
Id like to motivate women who have gone through the same path as me and have had the same kinds of struggles. I want them to know they should never give up and keep pushing through, because if you do, you will make it.
The Innovator Awards are meant to strengthen Northeasterns community of entrepreneurs, says Betsy Ludwig, executive director of womens entrepreneurship at Northeastern.
With BluePlanetAI, Shital is seeking to solve one of the worlds biggest, most complex challenges of our lifetime: monitoring and protecting our oceans from climate change, says Ludwig. As we know, our oceans affect everything from the air we breathe to the food we eat. We admire Shitals commitment to ambitious innovation and are thrilled to be supporting her with a Women who Empower Innovator Award as an entrepreneur, scientist and innovator.
The experience has elevated Waters career expectations.
If this really takes off, which Im hoping it does, then Ill be focusing on this, Waters says of BluePlanetAI. But I would also like to do other things in terms of entrepreneurship. There are just so many problems out there that can be solved using new advanced technologies.
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From computer programs that assist in medical decisions to innovative crop-cultivating techniques to software that analyzes military intelligence, computer science is embedded in a growing number of careers today. Demand is high, and opportunities are plentiful for people with programming skills, making introductory instruction essential for students at younger ages.
The Georgia legislature passed a bill two years ago mandating that all middle and high schools offer computer science courses by the 2024-25 academic year. However, finding teachers with experience in this subject area is a challenge.
A collaborative project between Mercers Tift College of Education, College of Liberal Arts and Sciences and School of Engineering aims to expand the pool of certified computer science teachers through a new endorsement track and teacher development program.
Dr. Thomas Koballa, dean of the College of Education, pitched the idea for this project soon after coming to Mercer in July 2019 and found immediate support from Dr. Susie Morrissey, assistant professor of education, and Dr. Bob Allen, professor and chair of computer science in the College of Liberal Arts and Sciences.
Supported by a $124,829 grant from the National Science Foundation (NSF), in spring 2020, the team started a capacity-building project to support computer science teachers. While science, technology, engineering and math (STEM) subjects have been emphasized in curricula for a long time, computer science has not received the same attention, Dr. Koballa said.
Computer science is 21st century skills, he said. More schools are recognizing that and thinking about it as a core area of the curriculum. But many schools and systems in rural Georgia are just not there yet. The equity issue is one were attempting to address.
While school systems in metro areas often have certified faculty teaching computer science, many rural districts dont have the capacity or manpower, Dr. Koballa said.
Its not abnormal for a school to ask a teacher with no computer science training to teach courses in the subject, Dr. Allen said. Through workshops, he has provided local teachers with tools and resources to get started, but they always need more training.
We wanted to talk with teachers and school leaders to find out what they feel needs to be done to support the development of computer science teachers, Dr. Koballa said. We needed to find some mechanism to enable teachers to be credentialed in computer science.
The capability-building project, which took more than a year, led to the development of a three-course Computer Science Master Teacher Endorsement Track and an NSF grant proposal for the implementation of a five-year computer science teacher development program. The team submitted the proposal in August and should learn if it has been funded in December or January.
Our capacity-building grant was an exploratory grant to find out what rural Georgia schools need to be able to effectively teach computer science, said Dr. Allen. We learned a lot, and we put that into our proposal thats being reviewed right now thats going to fund many years of us supporting teachers and spreading the good news that computer science is not just for geeks but for everyone.
The endorsement, developed by Dr. Allen and Dr. Morrissey, will be available in summer 2022 and open to anyone, Dr. Morrissey said. The classes could be taken as part of other degree programs or as a standalone endorsement, Dr. Koballa said.
Dr. Allen, Dr. Morrisey and professor of electrical and computer engineering Dr. Anthony Choi, who joined the team this summer, will teach the endorsement courses.
Im hoping that the computer science endorsement continues to be sustainable, Dr. Morrissey said. I hope other teachers in the state will see it as a benefit and continue to take the endorsement.
The endorsement is embedded in the teacher development program, which will train 16 teachers in eight rural school districts in South Georgia: Clinch, Coffee, Evans, Jeff Davis, Tattnall, Treutlen and Wheeler counties and Dublin City. The idea is to find established educators who are tied to their rural communities and equip them with computer science skills, Dr. Allen said.
The fellows will earn an education specialist degree in teacher leadership with endorsements in computer science and instructional coaching, in addition to being involved in other development activities. They will receive a $10,000 annual stipend, on top of their teaching salary.
Filling a gap in teacher preparation and workforce development with a variety of partners in South Georgia will allow Mercer to do what we do best collaborate with others to forward the University vision to change the world, one student at a time, said Senior Vice President for Enrollment Management Dr. Penny Elkins, whose office is a key supporter in the initiative.
Students in rural areas are often interested in careers in agriculture, health care and the military, so the Mercer team focused on developing community partners in those fields. The Georgia Rural Health Innovation Center, University of Georgia Agricultural Extension Service and the 402nd Software Engineering Group at Warner Robins Air Logistics Complex will provide the fellows with career-focused connections within their communities, Dr. Koballa said.
These partnerships will help the teachers understand how computer science is linked to jobs in the area, and in turn, they can help their students see how programming skills can be applicable to careers they are interested in. In addition, these partners will gain a bigger pool of students to recruit from for jobs.
We need more computer programmers. When we train more workers in these areas, we will have the intellectual base upon which our future industry will continue to grow and thrive, Dr. Choi said. We are trying to bring these (career) opportunities and also leverage untapped potential. We have amazing students in rural schools who have not been exposed to this.
Another key component of the grant project will be the assessment of the model and its success, Dr. Koballa said. The hope is that the initiative could later be replicated to support computer science advancement in other rural communities.
What we want to really do is use the proposal time and interaction period to establish something that is going to be ongoing, Dr. Choi said. It has to be sustainable. We want to have an impact and lay out sustainable policies and mechanisms, so that each of the school districts are able to continue what they started, so that all future students will benefit.
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Research helps Blugold discover how computer science, health care intersect – University of Wisconsin System
Thanks to his undergraduate research, Nichol He found a way to bring his passions for computer science and health care together in his future career. After He earns his degree in software engineering, the Blugold hopes to go to medical school while also continuing his research in bioinformatics. (Photo by Jesse Yang)
Coming into college, Nichol He knew he wanted to study either computer science or pre-med, two very different academic areas that he assumed could only lead to two very different careers.
Since the University of Wisconsin-Eau Claire has strong programs in both areas, He decided hed take a few classes in each discipline and then decide which path to follow.
I was really interested in computer science and I knew I didnt want to give that up, He says, noting that while his longtime goal is to be a physician, the logic of computer science, just really clicks with me. So, I decided to major in software engineering and minor in pre-professional health sciences. That way I could experiment with them both and decide which one I absolutely want to do.
This summer thanks to his work on multiple research projects He realized he doesnt have to choose between his two passions because computer science and health care intersect in ways he never imagined.
All in all, it was a very powerful experience and has had a big influence on what I want to do post-graduation, He says of his research. Coming into the university, my hopes were to go to medical school and become a physician or to graduate and be a computer scientist. I thought I would have to give one of them up. I never thought my interests in computer science and the medical field would ever intersect.
Now, because of my research, Ive found bioinformatics, which really is a combination of my two passions. I really like the intersection between software engineering/computer science and the biology/medical field.
So, his future plans now include going to medical school and specializing in radiology, and also continuing his bioinformatics research during his postgraduate studies and/or after he becomes a physician.
This summer, He worked alongside two faculty research mentors, one in biology and one in computer science.
He worked with Dr. Bradley Carter, an assistant professor of biology, to study the effects of chemicals on the development of zebra fish. And he collaborated with Dr. Rahul Gomes, assistant professor of computer science, on research involving deep learning and bioinformatics.
Both research projects are very different; they are almost complete opposites, says He, a native of Medina, Minnesota. One is really observing behaviors in fish and working with animals and the other is working with data and programs. They were completely different, but together they really gave me an enriching experience.
Through his research with Gomes, He began to understand the powerful intersection between computer science and the natural sciences.
Working with researchers at North Dakota State University, He and Gomes explored methylation markers, which are certain values associated with gene expression that possibly are related and could be a predictor of pancreatic cancer.
So, the deep learning Im doing on this project is looking at all this data and predicting whether or not a person might have pancreatic tumors or if they are healthy, He says.
Gomes and He also are working with Mayo Clinic Health System on a project that uses CT scans and data to help predict outcomes for patients with pancreatic cancer who are being treated with chemotherapy.
My research over the summer was a unique experience for me because I was working in a real-world work environment, He says. And it showed me that I really want to explore deep learning in bioinformatics more.
I went into this research without knowing anything about deep learning or bioinformatics. But Ive found this passion for it and that is really, really cool.
Bioinformatics is the science of storing, extracting, organizing, analyzing, interpreting and using biological information. It incorporates data and analytical approaches from the biological sciences, computer science, data science and mathematics.
The field of bioinformatics grew out of the need to organize and analyze the increasingly large amounts of biological data including data critical to advances in health care being generated. Bioinformatics analyses are increasingly necessary to address many biological questions.
The need for bioinformatics is now greater than ever, Gomes says. As modern technology enables us to collect more and more clinical as well as biological data, we require experts who are not only capable of processing the data to gain information but do so in the most optimized fashion to enable a faster and more accurate response.
A new bioinformatics major an interdisciplinary program that draws on expertise in the universitys biology, computer science and mathematics departments will be available at UW-Eau Claire beginning in fall 2022. It will be the only bioinformatics program of its kind in the UW System.
Gomes describes He as an outstanding student and researcher, who has made valuable contributions to their research despite having no prior background in deep learning or bioinformatics.
Nichol is very perceptive about the challenges while developing a deep learning model and how we can overcome them, Gomes says. During the pancreatic cancer research project with Mayo Clinic, he introduced and implemented a patch-based deep learning model to divide the CT scans in 3D patches, making model training more feasible on our GPU nodes at the Blugold Center for High-Performance Computing.
The fact that Nichol can take in information and also engage in discussions to modify or improve the proposed workflow is simply astounding considering that he is an undergraduate student and with no prior experience in deep learning.
He came to UW-Eau Claire primarily because of the many internship and research opportunities he knew hed find as a Blugold.
Among the opportunities he values most is being a Karlgaard Fellow, a scholarship program that, among other things, supports undergraduate student researchers who are studying computer science or software engineering.
Karlgaard scholars collaborate with computer science faculty on research and produce scholarly publications and/or formal presentations outside of the UW-Eau Claire campus.
I was fortunate enough to be chosen for this scholarship, and its been a big motivator for me to explore different areas of computer science, He says. Knowing there is someone who supports me financially makes me feel motivated to work harder, but it also makes me even more thankful for the opportunities.
David and Marilyn Karlgaard met while both were students at UW-Eau Claire. David Karlgaard graduated in 1967 with degrees in math and physics. He was co-founder, CEO and president of PEC Solutions Inc., an internet technology-consulting firm, which was acquired by Nortel Networks in 2005. Marilyn Karlgaard, who attended UW-Eau Claire from 1965-1968, is a retired human resource manager.
The Karlgaards have made substantial donations to the UW-Eau Claire Foundation, gifts that support multiple scholarships and various other university initiatives.
He says the fellowship programs ties to undergraduate research are especially meaningful because computer science majors often come into the program with a set idea of what they want to do with their degree. Research can help them discover career paths they may not have considered or otherwise known about.
Its a very wide field and a very fun field, so students need to look around and find the niches that fit them, He says of computer science and software engineering. It was being a Karlgaard Scholar that got me into this bioinformatics research. Without that, I wouldnt even know what I want to do in the future.
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Oct. 13, 2021 ACM, the Association for Computing Machinery and IEEE Computer Society have named David Abramson, a Professor at the University of Queensland, as the recipient of the 2021 ACM-IEEE CS Ken Kennedy Award.Abramson is recognized for contributions to parallel and distributed computing tools, with application from quantum chemistry to engineering design. He is also cited for his mentorship and service to the field.
Abramson has performed pioneering research in the design, implementation, and application of software tools for parallel and distributed systems. He has conducted foundational research in distributed and parallel middleware, addressing programmer productivity and software correctness, and has influenced multiple generations of researchers. His papers have been cited more than 12,000 times.
Two highly-regarded tools developed by Abramson include Nimrod, a family of software systems that support the execution of distributed parameter sweeps, searches, and workflows; and Guard, a performance tuning and debugging tool.
The Nimrod template is common in many fields and is well suited to execution in distributed environments. Nimrod makes it possible to write concisely complex parameter sweeps which entail executing an algorithm repeatedly with varying parametersand supports advanced searches that integrate optimization algorithms, design of experiments methods, and scientific workflows. Additionally, the Nimrod project spawned a family of tools that make it easy to specify complex computational experiments and has resulted in a spinoff commercial product called EnFuzion, which has been widely adopted for power grid and simulation.
Abramson designed Guard with a hybrid debugging scheme that tests new versions of a program against reference versions known to be correct. Guard greatly enhances programmers ability to locate and fix errors in new software versions. The technology was licensed to Cray Inc. (now HPE) and is distributed on Cray supercomputers. As a result, it has been deployed at major international supercomputing centers, including the US National Energy Research Scientific Computing Center (NERSC) and the Swiss National Supercomputing Centre (CSCS).
Abramsonhas been an advisor to two dozen graduate students in computer science, as well as countless undergraduate and high school students.
Among his most important initiatives, Abramson has been an international driver of the PRIME initiative, an NSF-funded University of California San Diego program that enables undergraduate students to take research internships abroad. Inspired by the success of PRIME, he has introduced similar programs for Australian undergraduates to travel abroad for internships, and he has organized travels for Australian students to top research centers in the US and the UK annually for over 12 years. Since 2011, he has run a unique program that supports Australian high school students attending SC, the leading high performance computing conference.
Also in the mentoring arena, Abramson started streaming video HPC seminars that have allowed Australian students to engage with world leaders, and he launched the Early Adopters PhD Workshop at SC09. Distinct from other doctoral showcases, the workshop specifically targets research students from fields outside of computer science who are applying HPC tools in their research.
Service to the Field
Over his career, Abramson has been General Chair, Program Committee Chair, or program committee member of many conferences related to performance and programmer productivity (on average about eight per year), including IPDPS, HiPC, HPC Asia, HPDC, ICPADS, Cluster, SC, CCGrid, Grid, and e-Science.
He is currently the Chair of the e-Science Steering Committee and has served in several senior roles in the IEEE/ACM SC series, including Chair of the Technical Papers Committee (2021) and Test of Time Award Committee (2018), Co-chair of the Invited Speakers Committee (2019), and More than HPC Plenary Committee (2020).
ACM and IEEE CS co-sponsor the Kennedy Award, which was established in 2009 to recognize substantial contributions to programmability and productivity in computing and significant community service or mentoring contributions. It was named for the late Ken Kennedy, founder of Rice Universitys computer science program and a world expert on high performance computing.The Kennedy Award carries a US $5,000 honorarium endowed by IEEE CS and ACM. The award will be formally presented to Abramson in November atThe International Conference for High Performance Computing, Networking, Storage and Analysis (SC21).
ACM, the Association for Computing Machinery, is the worlds largest educational and scientific computing society, uniting computing educators, researchers and professionals to inspire dialogue, share resources and address the fields challenges. ACM strengthens the computing professions collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.
Source: Association for Computing Machinery
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image:(From left) Anuj Karpatne, Department of Computer Science and Sanghani Center for Artificial Intelligence and Data Analytics; Amrinder Nain and Sohan Kale, both in the Department of Mechanical Engineering, meet in the STEP Lab. Photo by Peter Means for Virginia Tech. view more
Credit: Virginia Tech
With advances in deep learning, machines are now able to predict a variety of aspects about life, including the way people interact on online platforms or the way they behave in physical environments. This is especially true in computer vision applications where there is a growing body of work on predicting the future behavior of moving objects such as vehicles and pedestrians.
However, while machine-learning methods are now able to match and sometimes even beat human experts in mainstream vision applications, there are still some gaps in the ability of machine-learning methods to predict the motion of shape-shifting objects that are constantly adapting their appearance in relation to their environment, saidAnuj Karpatne, assistant professor of computer science and faculty at theSanghani Center for Artificial Intelligence and Data Analytics.
This is a problem encountered in many scientific fields, Karpatne said. For example, in mechanobiology, cells change their shape and trajectory as they move across fibrous environments in the human body, constantly tugging or pushing on the fibers and modifying the background environment, which in-turn influences the movement of cells in a perpetual loop.
This is fundamentally different from mainstream applications in computer vision where changes in the background caused by pedestrians and vehicles are far less accelerated than those possible by the movement of living cells governed by the laws of mechanics and biology, he said.
To address this challenge, the National Science Foundation has awarded a team of Virginia Tech scientists a $1 million grant to create a new avenue of research in physics-guided machine learning. The project will, for the first time, systematically integrate the mechanics of cell motion available as biological rules and physics-based model outputs to predict themovement of shape-shifting objects in dynamic physical environments.
As principal investigator, Karpatne will team with co-principal investigatorsAmrinder Nain, associate professor, andSohan Kale, assistant professor in theDepartment of Mechanical Engineering, combining his expertise in machine learning with their specialties in cell mechanobiology and computational modeling, respectively.
The work we are doing at theSTEP Labis a natural overlap, said Nain, who founded the lab and pioneered research in designing nanofiber networkplatforms and experimental imaging to study cell motion.
Cell shapes are highly dynamic and undergo limitless transformations as they sense and react to their environment. In addition, cell motion is constrained by the forces exerted by the cells on the background environment and the complex nature of cell-cell and cell-fiber interactions," Nain said. "While conventional methods for studying cell motion require manual tracking of images' features or running computationally expensive tools, our project will take advantage of our ability to create well-defined suspended nanofiber nanonets and advancements in machine learning to open to a new frontier to automatically describe new rules of cell behavior.
Kale said hisMechanics of Living Materials Labhas alreadydeveloped a computational method to estimate the forces exerted by cells from the deformed shapes of underlying fibers.
This, combined with the deep learning framework from Anuj's group, provides a framework to measure forces directly from experimental images of cells moving on nanofiber networks. Our tool enables the study of cell mechanobiology in fibrous environments in a radically different way than existing approaches in the field, said Kale.
We are fully leveraging the principles of `convergence research in our project by integratingdata, knowledge, and methodologies from our three different disciplines machine learning, experimental cell imaging, and computational modeling, said Karpatne. The ultimate goal is to accuratelypredict and explainhow cells move, interact with each other, and change their appearance in physiological environments inside our body.
The project will contribute foundational innovations by going far and beyond current standards of black-box machine learning for motion prediction in scientific problems. By anchoring our deep learning patterns with scientific theories, our work advances the frontiers of explainable machine learning by discovering new rules of cell behavior that are physically consistent and scientifically meaningful, Karpatne said.
The research has potential impact on several scientific disciplines that routinely involve predicting the trajectories of shape-shifting objects in dynamic physical environments, for example, hurricane prediction, bird migration, and ocean eddy monitoring, he said.
The project will also lead to novel advances in mechanobiology.
Studying cell migration is a major research frontier in the study of embryo development, wound closure, immune response, and cancer metastasis, Nain said. We expect that this research will also serve as a drug discovery, diagnostics, and testing platform in the context of cancer and wound healing biology where the spread of disease or repair of wound result from the constant change of cell and fibrous network shapes.
The research team is committed to supporting Virginia Techs education and workforce development goals, especially toward training a diverse cadre of students who can address complex problems requiring interdisciplinary skills. These students include those majoring in computer science, mechanical engineering, physics, and biological sciences.
Three Ph.D. students will also be working on this project. They areArka Dawin computer science, advised by Karpatne; Abinash Padhi in mechanical engineering, advised by Nain; and Maahi Tulukder in mechanical engineering, advised by Kale.
In conjunction with their research,Karpatne, Nain, and Kale will collaborate with theCenter for Educational Networks and Impactsto create a hands-on exhibition on Artificial Intelligence for Observing Cells for the annual Virginia Tech Science Festival and Hokie for a Day field trip event.
Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.
Neural networks can learn to solve all sorts of problems, from identifying cats in photographs to steering a self-driving car. But whether these powerful, pattern-recognizing algorithms actually understand the tasks they are performing remains an open question.
For example, a neural network tasked with keeping a self-driving car in its lane might learn to do so by watching the bushes at the side of the road, rather than learning to detect the lanes and focus on the roads horizon.
Researchers at MIT have now shown that a certain type of neural network is able to learn the true cause-and-effect structure of the navigation task it is being trained to perform. Because these networks can understand the task directly from visual data, they should be more effective than other neural networks when navigating in a complex environment, like a location with dense trees or rapidly changing weather conditions.
In the future, this work could improve the reliability and trustworthiness of machine learning agents that are performing high-stakes tasks, like driving an autonomous vehicle on a busy highway.
Because these brain-inspired machine-learning systems are able to perform reasoning in a causal way, we can know and point out how they function and make decisions. This is essential for safety-critical applications, says co-lead author Ramin Hasani, a postdoc in the Computer Science and Artificial Intelligence Laboratory (CSAIL).
Co-authors include electrical engineering and computer science graduate student and co-lead author Charles Vorbach; CSAIL PhD student Alexander Amini; Institute of Science and Technology Austria graduate student Mathias Lechner; and senior author Daniela Rus, the Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science and director of CSAIL. The research will be presented at the 2021 Conference on Neural Information Processing Systems (NeurIPS) in December.
An attention-grabbing result
Neural networks are a method for doing machine learning in which the computer learns to complete a task through trial-and-error by analyzing many training examples. And liquid neural networks change their underlying equations to continuously adapt to new inputs.
The new research draws on previous work in which Hasani and others showed how a brain-inspired type of deep learning system called a Neural Circuit Policy (NCP), built by liquid neural network cells, is able to autonomously control a self-driving vehicle, with a network of only 19 control neurons.
The researchers observed that the NCPs performing a lane-keeping task kept their attention on the roads horizon and borders when making a driving decision, the same way a human would (or should) while driving a car. Other neural networks they studied didnt always focus on the road.
That was a cool observation, but we didnt quantify it. So, we wanted to find the mathematical principles of why and how these networks are able to capture the true causation of the data, he says.
They found that, when an NCP is being trained to complete a task, the network learns to interact with the environment and account for interventions. In essence, the network recognizes if its output is being changed by a certain intervention, and then relates the cause and effect together.
During training, the network is run forward to generate an output, and then backward to correct for errors. The researchers observed that NCPs relate cause-and-effect during forward-mode and backward-mode, which enables the network to place very focused attention on the true causal structure of a task.
Hasani and his colleagues didnt need to impose any additional constraints on the system or perform any special set up for the NCP to learn this causality it emerged automatically during training.
Weathering environmental changes
They tested NCPs through a series of simulations in which autonomous drones performed navigation tasks. Each drone used inputs from a single camera to navigate.
The drones were tasked with traveling to a target object, chasing a moving target, or following a series of markers in varied environments, including a redwood forest and a neighborhood. They also traveled under different weather conditions, like clear skies, heavy rain, and fog.
The researchers found that the NCPs performed as well as the other networks on simpler tasks in good weather, but outperformed them all on the more challenging tasks, such as chasing a moving object through a rainstorm.
We observed that NCPs are the only network that pay attention to the object of interest in different environments while completing the navigation task, wherever you test it, and in different lighting or environmental conditions. This is the only system that can do this casually and actually learn the behavior we intend the system to learn, he says.
Their results show that the use of NCPs could also enable autonomous drones to navigate successfully in environments with changing conditions, like a sunny landscape that suddenly becomes foggy.
Once the system learns what it is actually supposed to do, it can perform well in novel scenarios and environmental conditions it has never experienced. This is a big challenge of current machine learning systems that are not causal. We believe these results are very exciting, as they show how causality can emerge from the choice of a neural network, he says.
In the future, the researchers want to explore the use of NCPs to build larger systems. Putting thousands or millions of networks together could enable them to tackle even more complicated tasks.
This research was supported by the United States Air Force Research Laboratory, the United States Air Force Artificial Intelligence Accelerator, and the Boeing Company.
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Last term, Drexel University faculty were recognized for their scholarly research and professional contributions and recognitions. This update offers a snapshot of recent activity, courtesy of the Office of the Provost.
Gwen Ottinger, PhD, associate professor in the College of Arts and Sciences, was awarded a $220,428 grant from the Sloan Foundation to support her project Open Science Hardware practice: Transforming the Politics of Scientific Knowledge Production.
Ezra Wood, PhD, associate professor in the College of Arts and Sciences, received a two-year grant from the National Oceanic and Atmospheric Administration for his project Quantification of Ozone Formation Rates in Upper Manhattan. This project is part of a multi-investigator study on air quality in densely populated coastal cities.
College of Computing & Informatics faculty Christopher MacLellan, PhD, assistant professor; Rosina Weber, PhD, associate professor; and Edward Kim, PhD, associate professor, received $999,999 from Defense Advanced Research Projects Agency to study sparse coding and extraction of ultrasound knowledge for explainable point-of-care ultrasound Artificial Intelligence.
Vasilis Gkatzelis, PhD, assistant professor in the College of Computing & Informatics, received a prestigious National Science Foundation Faculty Early Career Development Program Award of $599,782 under the title of Optimal Mechanism Design without Monetary Transfers.
Rajashi Ghosh, PhD, associate professor and chair for Policy, Organization and Leadership in the School of Education received a grant of $307,000 from the National Science Foundation to support her research project titled, Towards a Theory of Engineering Identity Development & Persistence of Minoritized Students with Imposter Feelings: A Longitudinal Mixed-methods Study of Developmental Networks.
School of Educations Toni May, PhD, associate professor, and Kristin Koskey, PhD, visiting scholar, received a grant from the National Science Foundation to support their project, Collaborative Research: Developing and Evaluating Assessments of Problem-Solving in Computer Adaptive Testing Environments.
Ivan Bartoli, PhD, associate professor in the College of Engineering, was awarded a Federal Highway Administration (FHWA) grant as part of the Accelerated Marketing Readiness program. The FHWA Cooperative Agreement will provide $499,835 in funding to develop, and eventually commercialize, wireless sensors to be used for enhancing routine and special bridge inspections which ensure the safe operation of our transportation network and performance of bridges. Such information will be critical in prioritizing repairs and maintenance of our aging transportation infrastructure.
James Tangorra, PhD, professor and department head for Engineering Leadership and Society in the College of Engineering, was part of a team to receive a three-year, $1.5 million grant from the Office of Naval Research titled Locomotion and Transitions of an Amphibious System: Biologic to Robotic. The proposed work will build on and extend fundamental studies of the California sea lions swimming mechanism and thrust production capabilities.
Peter Baas, PhD, professor in the College of Medicine, received a two-year, $833,000 NIH grant for Role of Tau in Microtubule Stability in Adult Neurons.
Christian Sell, PhD, associate professor in the College of Medicine, received a one-year, $310,000 NIH grant for Novel Longevity Enhancing Pathways Regulated by mTOR.
The Andrew W. Mellon Foundation has committed a $500,000 grant to Brandywine Workshop & Archives with Drexel as sub-grantee. Faculty members from the Westphal College of Media Arts and Designs Department of Arts & Entertainment Enterprise Julie Goodman, associate professor; Neville Vakharia, associate professor; and Brea Heidelberg, associate professor will collaborate on succession, business planning and evaluation. School of Education Associate Dean of Research and Associate Professor Jennifer Katz-Buonocontro, PhD, along with graduate students, will conduct ethnographic artist interviews. The Lenfest Center for Cultural Partnerships (led by Associate Director Melissa Clemmer) will fund co-ops, manage the collaboration, and produce a white paper on the expanded digital resource Artura.
Guy Diamond, assistant professor in the College of Nursing and Health Professions, received $147,000 for an 18-month contract from CADEkids to develop an electronic survey to assess the needs of Philadelphia school-age youth and families, related to substance use, behaviors and attitudes.
A collaboration between College of Nursing and Health Professions PI Minjung Shim, PhD, assistant research professor, and co-investigators from the Dornsife School of Public Health (Kathleen Fisher, PhD, professor; Sungchul Park, PhD, assistant professor), College of Arts & Sciences (Fengqing Zhang, PhD, associate professor) and College of Nursing and Health Professions (Arun Ramakrishnan, PhD, director of research labs) and others received $74,000 for At-Home Telehealth Mindfulness-based Dance/Movement Therapy for Older Adults with Mild Cognitive Impairment: A Feasibility Study from Commonwealth Universal Research Enhancement 2021 Formula Grant Program.
Alexis Roth, PhD, associate professor in the Dornsife School of Public Health, received a NIH R01 grant for $4.9 million to conduct a randomized control trial to assess HIV prevention interventions over the next five years.
Jana Hirsch, PhD, assistant research professor in the Dornsife School of Public Health, was awarded a five-year, $4.4 million R01 National Institute on Aging grant for Contribution of Longitudinal Neighborhood Determinants to Cognitive Health and Dementia Disparities within a Multi-Ethnic Cohort. This study aims to identify actionable, community-level interventions to address and remediate racial and socioeconomic inequalities derived from the unequal distribution of environmental supports for healthy aging.
The following faculty were named Louis & Bessie Stein Family Fellowship recipients. The endowed Fellowship supports research, exchange, teaching and collaboration with partners in Israel.
Major Gifts, Honors, Recognition
Myrna Shure, PhD, professor emeritus in the College of Arts and Sciences, was awarded a Lifetime Achievement Award from the Center for the Promotion of Social & Emotional Learning.
Rebecca Clothey, PhD, associate head of global studies and modern languages in the College of Arts and Sciences and associate professor in the School of Education, was elected to the board of the Comparative and International Education Society.
Sharon Walker, PhD, dean of the College of Engineering, has been named Executive Director of ELATES at Drexel, a national leadership development program designed to advance senior women faculty in academic engineering, computer science, and other STEM fields into effective institutional leadership roles within their schools and universities. Walker will assume this new role in addition to her responsibilities as dean.
College of Medicine faculty members Leon McCrea II, MD, associate professor and senior associate dean for diversity, equity and inclusion, and Dennis Novack, MD, professor and associate dean of medical education, received a three-year, $300,000 grant from the Josiah Macy Jr. Foundation to spearhead creation of an online learning module on antiracism.
Several faculty from the College on Nursing and Health Professions have been recognized this year for their commitment to diversity, equity and inclusion. Highlights include:
Michael LeVasseur, PhD, assistant teaching professor in the Dornsife School of Public Health, was awarded by the Office of New York State Governor for co-founding COVIDoutlook.info and for his commitment to providing accurate, scientific information to policymakers about the pandemic.
The City Council of Philadelphia honored and congratulated Sharrelle Barber, PhD, assistant professor in the Dornsife School of Public Health, for her appointment as director of The Ubuntu Center on Racism, Global Movements and Population Health Equity at Dornsife with a resolution.
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How an AI finished Beethoven’s last symphony and what that means for the future of music – BBC Focus Magazine
When he died in 1827 aged 56, Ludwig van Beethoven left his 10th symphony unfinished. Only a few handwritten notes briefly detailing his plans for the piece have survived, with most just being incomplete ideas or fragments of themes or melodies.
Now, a multidisciplinary team of computer scientists at Rutgers University-based start-up Playform AI have trained an artificial intelligence to mimic the great composers style and used it to write a complete symphony based on these initial sketches.
We spoke to the lead researcher on the project, Professor Ahmed Elgammal, to find out more.
Beethoven left sketches in different forms, mainly musical sketches, but also some written notes with some ideas in as well. Previously, in 1988 [English musicologist] Barry Cooper used the majority of these sketches, about 250 bars of music, that were meant for a first movement [in his attempt to complete the symphony].
But what was left behind is really very little. So basically, like three bars of music here and four bars of music there and some rough sketches, which sound like basically the starting points of the main themes in the movements that he [Beethoven] wanted to write.
When you look at Beethoven and other classical composers, thats usually the case. I mean, usually they work with a main theme and develop it into a sequence of a couple of minutes and then another theme comes. Thats the traditional way of composing, and thats exactly what the AI needed to learn how Beethoven and other classical composers start with a theme and develop it. Like in the Fifth Symphony da da da dah. And then take that and evolve a whole movement around it.
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The way AI generates music in general is very similar to the way your email, for example, tries to predict the next word for you. So, when you write an email, you find it jumps into suggesting what you might want to write next.
Its the same concept, basically the AI has to learn from a lot of musical data. It asks what would be the next note given what you just wrote? And if you can predict the next note, then you can predict the next note and the next note and so on. Thats the main concept.
But what we soon realise is that if you start picking up the suggestions from the phone for next word and start writing just based on the AIs suggestions, it doesnt really hold for a long time. And thats what happens with music. If you just give it a starting point and leave it to predict, yes, it can predict a couple of notes. But then after that, it becomes nonsense more or less, and is no longer faithful to the main theme.
So that was the main challenge. How can we let the AI stick to the main theme and develop it? So this is where the role of the human expert working with the AI comes in. So we had to work with human experts to annotate and label a lot of music for us to tell the AI what the theme was and where the development of the theme was in a lot of pieces of music. So basically, the AI learnt as a student. That made a big difference because then the AI could really keep sticking to the theme.
Also, the AI had to compose the music in a specific musical form. So if you are composing for a scherzo movement or a trio part of the movement or a fugue etc, each of these musical forms have certain specific structure. The AI also had to learn how to write a fugue, how to write a trio, how to write a fugue, and how to write a scherzo.
It was very challenging because Beethoven only wrote nine symphonies. Thats a very small dataset compared to the scale of what the AI needed to do. So, the way we approached this was to first imagine ourselves like a young Beethoven learning about music. What he would have listened to?
So, we trained our first version of the AI as if it was somebody living in the 18th Century listening to baroque music like Bach, as well as Hayden and Mozart. And so that was the first version of the AI, which basically would be the kind of music anyone living in that era would study to compose. And then we took that and trained it specifically on Beethoven on old Beethoven sonatas, concertos, string quartets and the symphonies as well, so not only symphonies.
We first trained the AI to generate the composition as two lines of music, not as a full symphony, which is a typical way of a composer works by just composing first and then orchestrating. So then, we had another AI that would take that composition and learn how to orchestrate it. I believe this is very similar to the way humans learn you cannot really master fourth-level college without going through the first and second and third levels first. Its always incremental.
The symphony was premiered by The Beethoven Orchestra Bonn on 9 October 2021 Deutsche Telekom
The way we harmonise music is very similar to how we use AI to translate languages. Like when you use Google Translate or another AI to translate a sentence from one language to another. These kind of models used in translation learn a lot of background sentences. So, what is the sentence in German? What is the sentence in English? And from that, they try to learn how to translate them.
So basically, imagine you have these models [for harmonisation]. You put the melody in one side and on the other side you put in how Beethoven would harmonise it so the AI learns how to translate a melody line into harmonised music.
The thing about music is that its very structured and follows a lot of rules. But this is very hard for us to capture and write down. You really have to have a PhD in musicology with a speciality in Beethoven to really understand that. But the machine is able to capture that statistically and mathematically in a very implicit way and be able to use that to give us this harmonisation.
You got it right. That decision is just an extension of the harmonisation. We wanted the machine to translate the composition into multi-track instrumentation, which we also did by training the AI based on how Beethoven and other composers would do so.
Their response is really mixed. There are people who loved this very much, and love the idea of having an AI that understands music and can help you finish your composition or have you explore different musical ideas.
But on the other side of the spectrum, there are people who just reject even the concept of being able to complete a Beethoven symphony using AI. They are afraid of AI taking their jobs and think that it has nothing to do with this kind of thing.
Yeah. I have no doubt about that, we did that in visual art a couple of years ago where we developed an almost autonomous AI artist we had look at, lets say, the last 500 years of western art. The task was basically to generate new artworks that didnt follow any existing style.
If the AI generated an impressionist or a Picasso kind of art or a Renaissance-style artwork, it could realise and so it would have to learn how to create something new.
The challenge with this project was actually the constraints the fact that the AI was not generating music by itself but generating music that is based on Beethovens genius and also following the sketches. This makes it even more difficult. The high bar, of course, of expectation was due to the sketches coming from Beethoven. But when it comes to generating music autonomously I think thats an easier task.
Listen to the symphony below:
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