Category Archives: Computer Science

Academic Career & Executive Search (ACES) Selected by East Tennessee State University for Tenure-Track Assistant Professor of Computing Computer…

PRESS RELEASES Academic Career & Executive Search (ACES) Selected by East Tennessee State University for Tenure-Track Assistant Professor of Computing Computer Science Search

(June 2024, WEST HARTFORD, CT) Academic Career & Executive Search (ACES), a leading higher education focused executive search firm, has been selected to recruit the next Tenure-Track Assistant Professor of Computing Computer Science at Eastern Tennessee State University. Jennifer Muller, Managing Partner, will be leading the search.

An exceptional opportunity awaits an educator passionate about teaching, mentoring and fostering student success at both the undergraduate and graduate level at East Tennessee State University (ETSU). Working with a strong research foundation at ETSU, the Assistant Professor of Computing Computer Science will help shape and build an innovative, nationally recognized research program in the Department of Computing. The ideal candidate has a Ph.D. in computer science with the ability to break down and teach complex subject matter to enhance student understanding. Equally important is a passion and drive to promote student success by guiding them in research, sharing knowledge and making meaningful connections. Successful applicants will also engage in service activities in the department, university, and community. This is a nine-month position (mid-August through mid-May), with opportunities to conduct independent studies and supervise undergraduate and graduate research and thesis activities available.

Nestled in the Appalachian Highlands, ETSU is a thriving R2 research university spanning over 350 acres in Johnson City, Tennessee. The University has a diverse student body of 14,000 students from 71 countries and all 50 states, and 800 full-time faculty. ETSU has 160+ academic programs to choose from at the bachelors, masters, and doctoral levels housed across eleven colleges and schools. The Department of Computing began as a program in the Department of Mathematics in 1972 and became a standalone Department in 1977. The Department is housed within the College of Business and Technology (CBAT), which includes programs in Accountancy, Digital Media, Economics and Finance, Engineering/Engineering Technology, Interior Architecture, Management, Marketing, and Surveying. The Department has more than 500 undergraduate majors, 150 graduate majors, and 25 faculty members. All in-person Computing courses are taught in the recently renovated Brinkly Center, which includes four computer labs, four lecture rooms, and two auditorium-style classrooms. ETSU was named the states best Bachelor of Science in Computing for the Information Systems Concentration by CollegeFactual.com and Universities.com.

Affordable Excellence Academic Career & Executive Search, a higher education focused search firm, specializes in affordable excellence, providing perfectly matched candidates to institutions quickly and accurately. Their methodologies, based on frequent touchpoints, pinpoint ideal candidates with speed and meticulous care resulting in highly successful placements.

They offer flexible service/pricing levels for all positions, ensuring affordability.

Contact Jennifer Muller, Managing Partner, at 860-740-2600 or Jennifer@ACESrch.com, or visit https://acesrch.com/.

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Academic Career & Executive Search (ACES) Selected by East Tennessee State University for Tenure-Track Assistant Professor of Computing Computer...

UC computer science engineer works to improve AI explainability – University of Cincinnati

The personal and professional growth I have experienced during my time at UC has been remarkable. One achievement I'm proud of is my research project on developing provenance-based solutions for explainable machine learning models. I have presented this work at prestigious conferences like the Institute of Electrical and Electronics Engineers International Conference on Data Engineering, American Association for the Advancement of Science Annual Meeting, and the Greater Chicago Area Systems Research Workshop.

In addition, I have had the honor of contributing to the scholarly community by serving as a program committee member and a reviewer on the research paper track for various conferences.

I take great pride in my contributions to professional organizations in science and engineering such as the Institute of Electrical and Electronics Engineers. Currently, I am serving a two-year leadership commitment on the Society of Women Engineers' national organization and was honored to speak at two panel sessions dedicated to advancing graduate engineering at the 2023 conference.

Equally fulfilling has been my role in nurturing the next generation of scientists and engineers. I served as a mentor for the UC McNair Scholars, the Society of Women Engineers'"Invent It, Build It" program for K-12 students, and as a judge at events such as the Ohio Academy of Science District Science Day and State Science Day. I was also a counselor at various CEAS summer camps and a professional reviewer of research posters at the 2023 UC Undergraduate Scholarly Showcase.

Reflecting on my journey, I am grateful for the consistency and excellence that have marked my experience. Earning my master's degree in 2023 from UC was a significant milestone towards completing my doctorate. I am also honored by the accolades I have received, including being named Graduate Student Engineer of the Month, and receiving the 2023 Cadence Diversity in Technology Scholarship Award.

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UC computer science engineer works to improve AI explainability - University of Cincinnati

More people are turning to mental health AI chatbots. What could go wrong? – National Geographic

Chatbots replace talk therapy

The accessibility and scalability of digital platforms can significantly lower barriers to mental health care and make it available to a broader population, said Nicholas Jacobson, who researches the use of tech to enhance the assessment and treatment of anxiety and depression at Dartmouth College.

Swept up by a wave of Generative AI, tech companies have been quick to capitalize. Scores of new apps like WHOs digital health worker, Sarah offer automated counseling, where people can engage in cognitive behavioral therapy sessionsa psychotherapeutic treatment thats proven to assist users in identifying and changing negative thought patternswith an AI chatbot.

The arrival of AI, Jacobson adds, will enable adaptive interventions and allow healthcare providers to continuously monitor patients, anticipate when someone may need support, and deliver treatments to alleviate symptoms.

Its not anecdotal either: A systematic review of mental health chatbots found AI chatbots could dramatically cut down symptoms of depression and distress, at least in the short term. Another study used AI to analyze more than 20 million text conversations from real counseling sessions and successfully predicted patient satisfaction and clinical outcomes. Similarly, other studies have been able to detect early signs of major depressive disorder from unguarded facial expressions captured during routine phone unlocks and peoples typing patterns.

Most recently, Northwestern University researchers devised a way to identify suicidal behaviour and thoughts without psychiatric records or neural measures. Their AI model estimated self-harm likelihood in 92 out of 100 cases based on data from simple questionnaire responses and behavioral signals like ranking a random sequence of pictures on a seven-point like-to-dislike scale from 4,019 participants.

Two of the studys authors, Aggelos Katsaggelos and Shamal Lalvani expectonce the model clears clinical trialsspecialists to use it for support, such as scheduling patients depending on perceived urgency and eventually, roll out to the public in at-home settings.

But as was evident in Smiths experience, experts urge caution over treating tech solutions as the panacea since they lack the skill, training, and experience of human therapists, especially Generative AI, which can be unpredictable, make up information, and regurgitate biases.

When Richard Lewis, a Bristol-based counselor and psychotherapist, tried Woebota popular script-based mental health chatbot that can only be accessed via a partner healthcare providerto help a topic he was also exploring with his therapist, the bot failed to pick up on the issues nuances, suggested he "stick to the facts, while removing all the emotional content from his replies, and advised reframing his negative thoughts as a positive.

As a therapist, Lewis said, correcting or erasing emotions is the last thing I would want a client to feel and the last thing I would ever suggest.

Our job is to form a relationship that can hold difficult emotions, Lewis added, and feelings for our clients to make it easier for them to explore, integrate, or find meaning in them and ultimately know themselves better.

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More people are turning to mental health AI chatbots. What could go wrong? - National Geographic

Computer Science head shares Google encryption research at International Technologies Conference – Grambling State University

Dr. Bharat Rawal

Professor and head of Grambling State Universitys Department of Computer Science and Digital Technologies Dr. Bharat S. Rawal recently discussed a pair of papers hes authored as he appeared at the 15th International Conference on Computing, Communication and Networking Technologies) ICCCNT is a premier IEEE conference organized at IIT-Mandi, India.

The two papers Dr. Rawal wrote and discussed during the conference were titled Quantum and AI-Enhanced Digital Twin Systems and EUDRL: Explainable Uncertainty-Based Deep Reinforcement Learning for Portfolio Management.

Dr. Rawal said the goal of his papers and conference appearance was to create a unique handshake (authentication procedure RLP protocol) and security (cryptography) mechanism to enable secure communication across several cloud platforms.

The proposed encryption technique (Quantum Safe / Post Quantum Cryptosystem) will withstand attacks from quantum computers, Dr. Rawal said. In addition, we are looking into the issues of shifting to next-generation post-quantum crypto systems in cloud infrastructure. We created an RLP protocol using our own No-Sum (NS) difficult mathematical sequence.

Finding the element of an NS sequence is a challenging task known as NP hard in computer science. The solution exists; however, determining the correct value requires a significant amount of processing power and time. Verification of the solution takes no time.

Dr. Rawal said Google can be greatly beneficial because it provides precise results.

Search results from Google are accurate because their algorithms are among the best in the world, Dr. Rawal said. To increase relevance, they make use of user behavior and latent semantic indexing. Improved AI-enabled search features facilitate finding rapid answers, Google provides response boxes and People Also Ask sections.

Google has a massive database. Its large user base allows it to filter results based on user behavior, which makes sure that relevant content appears first. Users should search for research papers that have been published in peer-reviewed journals, as these publications are subject to a high level of examination which helps to reduce inaccuracies.

But because Google gathers user data, privacy concerns should also be a consideration for users.

Google provides customized results that have the potential to produce filter bubbles, which restrict exposure to a range of viewpoints, Dr. Rawal said.

It also has commercial bias. Google depends on advertisements for its business, which could sway search results. It can also have algorithmic biases where content or opinions may be unintentionally favored by algorithms.

Dr. Rawal said his appearance at the international conference will hopefully spread knowledge of GSUs Science and Digital Technologies programs across the globe.

IIT and NIT are two of Indias most prestigious university systems, as well as internationally recognized educational institutions, Dr. Rawal said. Our goal is to collaborate with these two institutes to foster AI and quantum computing initiatives for all of our partner institutions.

Millions of Indian high school and college students apply to these two famous institutions. Becoming their academic and research partner will help us market our university to the worlds fastest-growing economy and the greatest source of international students to the United States.

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Computer Science head shares Google encryption research at International Technologies Conference - Grambling State University

How to assess a general-purpose AI models reliability before its deployed – MIT News

Foundation models are massive deep-learning models that have been pretrained on an enormous amount of general-purpose, unlabeled data. They can be applied to a variety of tasks, like generating images or answering customer questions.

But these models, which serve as the backbone for powerful artificial intelligence tools like ChatGPT and DALL-E, can offer up incorrect or misleading information. In a safety-critical situation, such as a pedestrian approaching a self-driving car, these mistakes could have serious consequences.

To help prevent such mistakes, researchers from MIT and the MIT-IBM Watson AI Lab developed a technique to estimate the reliability of foundation models before they are deployed to a specific task.

They do this by training a set of foundation models that are slightly different from one another. Then they use their algorithm to assess the consistency of the representations each model learns about the same test data point. If the representations are consistent, it means the model is reliable.

When they compared their technique to state-of-the-art baseline methods, it was better at capturing the reliability of foundation models on a variety of classification tasks.

Someone could use this technique to decide if a model should be applied in a certain setting, without the need to test it on a real-world dataset. This could be especially useful when datasets may not be accessible due to privacy concerns, like in health care settings. In addition, the technique could be used to rank models based on reliability scores, enabling a user to select the best one for their task.

All models can be wrong, but models that know when they are wrong are more useful. The problem of quantifying uncertainty or reliability gets harder for these foundation models because their abstract representations are difficult to compare. Our method allows you to quantify how reliable a representation model is for any given input data, says senior author Navid Azizan, the Esther and Harold E. Edgerton Assistant Professor in the MIT Department of Mechanical Engineering and the Institute for Data, Systems, and Society (IDSS), and a member of the Laboratory for Information and Decision Systems (LIDS).

He is joined on a paper about the work by lead author Young-Jin Park, a LIDS graduate student; Hao Wang, a research scientist at the MIT-IBM Watson AI Lab; and Shervin Ardeshir, a senior research scientist at Netflix. The paper will be presented at the Conference on Uncertainty in Artificial Intelligence.

Counting the consensus

Traditional machine-learning models are trained to perform a specific task. These models typically make a concrete prediction based on an input. For instance, the model might tell you whether a certain image contains a cat or a dog. In this case, assessing reliability could simply be a matter of looking at the final prediction to see if the model is right.

But foundation models are different. The model is pretrained using general data, in a setting where its creators dont know all downstream tasks it will be applied to. Users adapt it to their specific tasks after it has already been trained.

Unlike traditional machine-learning models, foundation models dont give concrete outputs like cat or dog labels. Instead, they generate an abstract representation based on an input data point.

To assess the reliability of a foundation model, the researchers used an ensemble approach by training several models which share many properties but are slightly different from one another.

Our idea is like counting the consensus. If all those foundation models are giving consistent representations for any data in our dataset, then we can say this model is reliable, Park says.

But they ran into a problem: How could they compare abstract representations?

These models just output a vector, comprised of some numbers, so we cant compare them easily, he adds.

They solved this problem using an idea called neighborhood consistency.

For their approach, the researchers prepare a set of reliable reference points to test on the ensemble of models. Then, for each model, they investigate the reference points located near that models representation of the test point.

By looking at the consistency of neighboring points, they can estimate the reliability of the models.

Aligning the representations

Foundation models map data points in what is known as a representation space. One way to think about this space is as a sphere. Each model maps similar data points to the same part of its sphere, so images of cats go in one place and images of dogs go in another.

But each model would map animals differently in its own sphere, so while cats may be grouped near the South Pole of one sphere, another model could map cats somewhere in the Northern Hemisphere.

The researchers use the neighboring points like anchors to align those spheres so they can make the representations comparable. If a data points neighbors are consistent across multiple representations, then one should be confident about the reliability of the models output for that point.

When they tested this approach on a wide range of classification tasks, they found that it was much more consistent than baselines. Plus, it wasnt tripped up by challenging test points that caused other methods to fail.

Moreover, their approach can be used to assess reliability for any input data, so one could evaluate how well a model works for a particular type of individual, such as a patient with certain characteristics.

Even if the models all have average performance overall, from an individual point of view, youd prefer the one that works best for that individual, Wang says.

However, one limitation comes from the fact that they must train an ensemble of large foundation models, which is computationally expensive. In the future, they plan to find more efficient ways to build multiple models, perhaps by using small perturbations of a single model.

This work is funded, in part, by the MIT-IBM Watson AI Lab, MathWorks, and Amazon.

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How to assess a general-purpose AI models reliability before its deployed - MIT News

Local teacher excels in 4Geeks bootcamp and lands new opportunity in data science and machine learning – Refresh Miami

By Krysten Brenlla

Eugene Cruz has spent a decade as an educator in Miami-Dade County, teaching future generations the fundamentals of mathematics and computer science. As a mathematics major, he knew numbers were always his thing. However, as he became more involved with computer science, he began looking for new ways to enhance his skills.

Thats when he discovered data science and machine learning, a new industry blending data, mathematics, statistics and programming to develop and enhance algorithms that solve real-world problems. His interest in using data science and machine learning led him to 4Geeks Academys Data Science and Machine Learning Bootcamp a connection made possible by the Miami Tech Talent Coalition, a collaboration of employers, academia and community organizations on a mission to fuel Miamis tech talent pipeline by creating new pathways into tech for residents. Its part of Miami Tech Works, an multi-year economic development initiative funded by a $10 million grant from the US government.

The boot camp at 4Geeks was so beneficial because it was just an awesome, structured program you go into it with a cohort of peers and support from teachers and mentors, said Cruz [pictured above]. Plus, the program also featured interview prep and job search preparation. They really offer mentorship for life.

In addition to mentorship, interview prep, and job search preparation, the 4Geeks Academys Data Science and Machine Learning Bootcamp also showed participants statistics and programs like Python, SQL, Looker (Google Data Studio), and StreamLit. Through the program, participants also have the opportunity to create predictive models using Python, Pandas and Numpy, while exploring algorithms like Close Neighbors and Decision Trees through supervised and unsupervised learning techniques.

At 4Geeks Academy, our mission is to help people launch successful tech careers and get better jobs. With no prior experience required, our students becomeFull Stack Developers,Data Scientists and Machine Learning Engineers, andCybersecurity Analystsin about four months. After graduation, they land high paying jobs in a matter of 3-6 months. On top of that, all 4Geeks students receive unlimited 1-1 coding mentorship and career support mentorship, said Alisa Landra, Miamis campus manager at 4Geeks Academy.

Our partnership with Miami Tech Works helps us to address one of the biggest barriers that those looking to launch new tech careers face the financial barrier, Landra continued. Through the Good Jobs Challenge Grant, 4Geeks was able to train 33 participants with scholarships. This allowed them to be placed in higher paying jobs without investment upfront on their end. We are looking forward to another year with Miami Tech Works, and training even more students.

Since participating in the program, Cruz used the skills he learned to land a new opportunity blending his experiences with mathematics, computer science, and now machine learning at Ransom Everglades School. Starting this August, Cruz will help teach Advanced Placement Computer Science and Mathematics courses, in addition to supporting students participating in different extracurricular computer science activities specifically contests and competitions in programming, data science, and machine learning.

Judging by where Ive been, theres a lot of interest in students because they know its a big topic and driving force in the tech field, Cruz continued. If students continue to be exposed at a younger age to the career possibilities of machine learning and data science, theyll be able to handle it.

For the future, Cruz is looking forward to teaching the next generation of advanced and gifted students the fundamentals of data science and machine learning. He hopes to continue building an interested community that will help him to build new programs, curriculum, and learning opportunities for students and the local Miami Tech community.

Im excited to grow in the same city I grew up in Miami is building up, Cruz said. Its all positive growth.

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Your involvement can make a significant difference in shaping the future of Miamis tech industry, creating a vibrant and sustainable tech talent ecosystem. Together, participants can continue to build Miami as an innovative hub and a desirable destination for businesses and tech talent.

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Refresh Miami is a proud partner of Miami Tech Works.

Krysten Brenlla is the Media Relations Specialist for Jackson Health System, where she manages media relations for the health system's cardiology, neurosurgery, rehabilitation, and Miami Transplant Institute service lines. Prior to her role at Jackson, Krysten worked at Florida International University as an Account Manager for FIU's Office of Engagement. In 2022, Krysten obtained her master's degree in Global Strategic Communication from FIU.

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Local teacher excels in 4Geeks bootcamp and lands new opportunity in data science and machine learning - Refresh Miami

IST researcher Sharon Huang named David Reese Professor – Penn State University

UNIVERSITY PARK, Pa. Sharon Huang, professor in the College of Information Sciences and Technology (IST), is the new holder of the David Reese Professorship of Information Sciences and Technology, effective Aug. 1, 2024, through June 30, 2027.

The professorship was established in 1999 with a generous gift from David Reese, who earned a bachelors degree in accounting from Penn State in 1978 and was an original member of the College of IST Deans Advisory Board. The endowment aims to provide the resources necessary to continue and further the recipients contributions to teaching, research and public service.The professorship was previously held for 24 years by C. Lee Giles, who retired on June 30.

The David Reese Professorship is one of the most prestigious endowed professorships in IST, and I feel extremely honored to be appointed, Huang said. With the additional resources from the esteemed professorship, I hope to expand my research program in artificial intelligence (AI), particularly in exploring the emotional intelligence of AI, privacy and security of data use in AI and translating my previous work in biomedical AI into practice. These resources will allow me to support graduate assistants in exploring these exciting areas and generate preliminary results to help secure external grants for further research.

Huang joined the college as a tenured associate professor in July 2018 and was promoted to full professor in 2022. Most recently from July 1, 2023, to July 31, 2024 she has served as ISTs first associate dean for undergraduate studies.

Sharon is a superstar and well-deserving of this honor, said Andrea Tapia, dean of the College of IST. Her work will continue to position Penn State as a leader in AI research and, ultimately, make the world a better place.

Huang earned her bachelor of engineering degree in computer science from Tsinghua University in China and her masters and doctoral degrees in computer science from Rutgers University. She is also a member of the Huck Institutes of the Life Sciences at Penn State.

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IST researcher Sharon Huang named David Reese Professor - Penn State University

Computer science projects teach eighth graders robotics and resilience – wvdispatch.com

Samantha Vargas and Emerson Dazi couldnt help but smile as the robot they programmed together drew hexagons on their paper.

On just their first day working with the robots, the students worked through initial challenges by trial and error to attain this success. Working with robots is fun and unique. I didnt know you could code a robot to draw whatever you want, shared Vargas.

This exercise is part of a 10-week project students in eighth grade computer science explorations have been working on with computer science and special education teacher Evan Lally.

The project started out with what the class calls robot curling; students had the goal of getting their robot to a target area and had to navigate around other robots. Second, students programmed the robots to draw, coming up with a variety of shapes and patterns. Using these new skills, students worked together to guide the robot through a maze. These sections of the project were completed using a Cue Robot, which allows students to practice increasingly advanced programming.

Next, students got comfortable with Edison Robots, which have more autonomous abilities including sensing lines and walls. Students added Lego-like pieces to customize their work. Some students completed a second maze, using the first robot to lead the second through a maze.

How do the students achieve this?

Its up to them, shared Lally. This is what I love about all kinds of robotics and computer science. There are a thousand ways to get from point A to point B. The students use their own creative process, teamwork, trial and error, and pattern recognition to find a unique solution.

In their sixth and seventh grade computer science classes, students focused on learning the basics through programs like Scratch, a visual programming language. This year, students enjoyed working hands-on with the new technology.

At first, I didnt want to take computer science, but Mr. Lally brings it to life, shared Dazi.

This is the first eighth grade class to attend computer science, and Lally is impressed with their progress and the resilience theyve built through trial and error.

He shared that some students even began working with micro:bit technology, programming the robots to follow a light. The program received a grant to bring more of this technology into the classroom next year. Eighth graders will continue to build their skills as the program expands to high school classes in the fall.

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Computer science projects teach eighth graders robotics and resilience - wvdispatch.com

Career Q&A with Computer Science Major Siddharthsinh Parmar – College of Computer, Mathematical, and Natural Sciences

Sid Parmar was invited to the White House during an India state visit through the UMD student organization Develop, Empower, and Synergize India (DESI). Image courtesy of Sid Parmar. Why did you decide to study computer science at UMD?

I initially enrolled at UMD as a mechanical engineering major, but the computer science (CS) program here really drew me in. After giving it a lot of thought, I decided to switch to CS because the world of artificial intelligence was becoming increasingly compelling to me. The challenging courses at UMD fueled my passion and made me eager to learn more.

My academic advisor encouraged me to minor in another field, which inspired me to take business courses. Combining my interests in computer science and business has been incredibly rewarding.

I've attended numerous webinars, seminars and networking booths. Volunteering at the computer science fall and spring career fairs allowed me to gain valuable insights into recruiters. Participating in coffee chats with companies through the University Career Center and Handshake has been beneficial, as they often lead to resume shortlisting for interviews.

Working as a peer advisor in the Department of Computer Science also keeps me informed about the latest happenings and opportunities within the department. Being a peer advisor also helped me develop strong mentoring skills and build meaningful connections with both students and faculty. Additionally, Ive taken advantage of the various workshops and hackathons hosted by the university, which have provided hands-on experience and helped me stay updated with the latest industry trends and technologies.

I scheduled numerous meetings with the University Career Center @ CMNS to get guidance on drafting my resume, preparing for mock interviews, writing cover letters and conducting job research. One particular mock interview with [University Career Center @ CMNS Program Director] Becca Ryan stands outI didn't do well initially, but it turned out to be incredibly beneficial for my main interview for my internship. I also had my resume and application materials reviewed multiple times by the Computer Science Department staff to ensure they were polished and effective.

It's tough for international students to secure jobs in this market, but resources like GoinGlobal, which I accessed through the Career Center, were really helpful in my job search. I highly recommend that students explore the resources section on Handshake.

I'm really enjoying the hands-on experience and collaborative environment at Spirent. In my role, I've been focused on enhancing machine learning systems, which involves a lot of research and practical application. One highlight has been demonstrating how new machine learning algorithms can be used in mobile and wireless networks.

I've been involved in developing and testing various machine learning algorithms, as well as analyzing large data sets to draw meaningful insights. Additionally, Spirent has a fantastic buddy program where interns interact with experienced employees formally and informally throughout the internship period. This has been a great way to gain insights, receive guidance and build strong professional relationships. The opportunity to work on real-world projects, see the tangible impact of my work and connect with seasoned professionals has been incredibly rewarding.

My advice is to network as much as possible. Building a diverse network by making friends from different majors and backgrounds can open up a lot of opportunities. Join clubs early in your college career and stay committed to them throughout your time at the universitysomething I missed out on but have come to recognize as important.

Start planning your internship and job search at least a year in advance. This means preparing your resume, practicing interview skills and researching potential employers early on. Building strong relationships with your professors can also be incredibly beneficial, as they can offer guidance, support, and even job referrals.

Make sure to attend all the career fairs and networking events on campus. These events are excellent opportunities to meet recruiters, learn about different companies and make a good impression. Additionally, look for events organized in Washington, D.C., as they can provide access to a broader range of industries and professionals.

If youre an international student, take advantage of your unique background by sharing your stories of stepping out of your comfort zone. These narratives can highlight your adaptability, resilience and global perspective, making you stand out to potential employers.

Overall, the key is to be proactive. Take advantage of every resource available to you, from the Career Center to student organizations, and don't hesitate to put yourself out there. The more you engage with the community and seek out opportunities, the better your chances of securing valuable internships and job offers.

CMNS students have access to career advisors and programs that are personalized to their unique career interests in STEM fields. In this Q&A series, we are spotlighting how Science Terps are capitalizing on the resources, support and guidance that theUniversity Career Center @ CMNSprovides.

Make an appointment with Becca or another member of the University Career Center team by visitingumd.joinhandshake.comor emailcmnscareers@umd.eduwith any career-related questions!

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Career Q&A with Computer Science Major Siddharthsinh Parmar - College of Computer, Mathematical, and Natural Sciences

Marking a milestone: Dedication ceremony celebrates the new MIT Schwarzman College of Computing building – MIT News

The MIT Stephen A. Schwarzman College of Computing recently marked a significant milestone as it celebrated the completion and inauguration of itsnew building on Vassar Street with a dedication ceremony.

Attended by members of the MIT community, distinguished guests, and supporters, the ceremony provided an opportunity to reflect on the transformative gift that initiated the biggest change to MITs institutional structure in over 70 years. The gift, made by Stephen A. Schwarzman, the chair, CEO, and co-founder of Blackstone, one of the worlds largest alternative investment firms, was the foundation for establishing the college.

MIT Stephen A. Schwarzman College of Computing Building Dedication

MIT President Sally Kornbluth told the audience that the success of the MIT Stephen A. Schwarzman College of Computing is a testament to Steves vision. She pointed out that the new building with capacity for 50 computing research groups will foster a remarkable confluence of knowledge and cross-pollination of ideas. The college will help MIT direct this expertise towards the biggest challenges humanity now faces, she added, from the health of our species and our planet to the social, economic, and ethical implications of new technologies.

Expressing gratitude for the chance to engage with MIT, Schwarzman remarked, You dont get many opportunities in life to participate in some minor way to change the course of one of the great technologies thats going to impact people.

Schwarzman said that his motivation for supporting the college stemmed in part from trips he had taken to China, where he witnessed increased investment in artificial intelligence. He became concerned that he didnt see the same level of development in the United States and wanted to ensure that the country would be at the leading edge of AI. He also spoke about the importance of advancing AI while prioritizing ethical considerations to mitigate potential risks.

He described his involvement with the college as the most marvelous adventure and shared how much he has enjoyed meeting the fascinating people at MIT and learning about what you do here and the way you think. He added: Youre really making enormous changes for the benefit of society.

Reflecting on the thought process during his tenure that culminated in the conceptualization of the college, MIT President Emeritus L. Rafael Reif recounted the conversations he had about the idea with Schwarzman, whom he called a perfect partner. He detailed their collaborative efforts to transform the vision into tangible reality and emphasized how Schwarzman has an amazing ability to look at what appears to be a hopelessly complex situation and distill it to its essence quickly.

After almost a year of engaging in discussions with Schwarzman as well as with members of MITs leadership and faculty, the Institute announced the formation of the MIT Stephen A. Schwarzman College of Computing in October 2018.

To honor Schwarzmans pivotal role in envisioning the college, Reif presented him with two gifts: A sketch of the early building concept by the architects and a photograph of the building lobby captured shortly after it opened in late January. Thank you, Steve, for making all of this possible, Reif said.

Appointed the inaugural dean of the MIT Schwarzman College of Computing in 2019, Dan Huttenlocher, who is also the Henry Ellis Warren Professor of Electrical Engineering and Computer Science, opened the festivities and spoke about the building as a physical manifestation of the colleges three-fold mission: to advance the forefront of computing with fields across MIT; fortify core computer science and artificial intelligence leadership; and advance social, ethical, and policy dimensions of computing.

He also conveyed his appreciation to all those whospent countless hours on the planning, design, and construction of Building 45, including key partners in MIT Campus Construction and Campus Planning; Skidmore, Owings & Merrill; and Suffolk Construction.

It fills me with immense satisfaction and pride to see the vibrant activity of the MIT students, researchers, faculty, and staff who spend time in this building, said Huttenlocher. Its really amazing to see this building come to life and become a resource for so many across the MIT campus and beyond.

In addition, Huttenlocher thanked Anantha Chandrakasan, MITchief innovation and strategy officer, dean of the School of Engineering, and the Vannevar Bush Professor of Electrical Engineering and Computer Science, for his early involvement with the college, and Asu Ozdaglar, deputy dean of the MIT Schwarzman College of Computing and head of the Department of Electrical Engineering and Computer Science, for her leadership throughout the colleges development.

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Marking a milestone: Dedication ceremony celebrates the new MIT Schwarzman College of Computing building - MIT News