Category Archives: Computer Science
JEE Advanced 2023: Last 5 years BTech Computer Science cut-off for admission in IIT Goa – The Indian Express
JEE Advanced 2023:The Indian Institute of Technology (IIT), Goa is one of the six new IITs that was incorporated by amending the The Institutes of Technology Act, 1961 by the Union Cabinet. The institute comes under the aegis of Ministry of Education, Government of India. The admissions to various BTech courses at IIT Goa are done on the basis of the ranks scored in JEE Advanced.
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First published on: 03-06-2023 at 09:52 IST
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Using computer science to mitigate earthquake impact – The Source – Washington University in St. Louis
Cyberphysical systems bridge the digital and physical worlds by integrating physical sensors with computational elements to analyze data, make decisions and control physical processes in real-time.
Christopher Gill, a professor of computer science and engineering at the McKelvey School of Engineering at Washington University in St. Louis, is working to improve these systems for applications in earthquake engineering. He won a $597,585 award from the National Science Foundation for his research to assure such systems safety and performance.
Read more on the McKelvey School of Engineering website.
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Raj Reddy, the AI pioneer from India – Moneycontrol
The US and China as frontrunners in the battle for supremacy in the development of artificial intelligence (AI) may be leaving India some distance behind, but an Indian-born scientist is still considered one of the pioneers of research in the area. Dr Dabbala Rajagopal "Raj" Reddy, who celebrates his 86th birthday this month, is currently the Moza Bint Nasser University Professor in the Carnegie Mellon Universitys computer science department. His research interests include the study of human-computer interaction and artificial intelligence while his current research projects include spoken language systems; gigabit networks; universal digital libraries; and distance learning on demand".
Born in Katur, a small village in Andhra Pradesh with a population of 500 people who lived without water or electricity or doctors, Reddy learnt writing on sand since there was neither paper nor pencil. His father was a farmer and after going to the villages one-room primary school, the young boy became the first member of his family to attend college. After getting his bachelors degree from Guindy College of Engineering, Madras (now Chennai), and a masters degree from the University of New South Wales, Sydney, he worked for IBM in Australia for a few years before moving to the US for his masters degree followed by a doctorate, both in computer science, from Stanford University. Three years of teaching at Stanford was followed by a move to Carnegie Mellon University, where he founded the schools Robotics Institute and where he teaches till date.
At a time when AI wasnt yet a buzzword, it caught the attention of the man whose great passion has been to make information technology accessible to poorer nations. Thus began a lifelong journey during which hes pushed thinking on the subject into newer dimensions. AI's use in looking for patterns amidst large sets of data, dates back several decades. What makes recent developments in the area, including products like ChatGPT and Bard, so exciting is that they are products of what is commonly referred to as generative AI.
And it is to this that much of Reddy's work over the last 50 years has been dedicated.
While he was on the computer science faculty at Carnegie Mellon in the 1970s, Reddy led a project to construct a computer program that could understand continuous human speech. The difficulties were enormous because of the differences with written text. Thats where Reddy came in with his insight that the issues in speech understanding were central to AI generally.
The result of his early work was Hearsay I, which comprised a set of cooperating parallel processes, each representing a different source of knowledge - acousticphonetic, syntactic, semantic - to predict what may appear in a given context or to verify a hypothesis resulting from a previous prediction. Effectively, Hearsay I was capable of continuous speech recognition. Along with its successors, it created the underlying basis for modern commercial speech recognition technology. An indirect consequence of his work was the famous blackboard model for assimilating and deploying multiple knowledge sources to address a defined problem statement. The model is now adopted across the spectrum of applied artificial intelligence.
In 1994, Reddy received the highest honor in computer science when he was given the A.M. Turing Award (jointly with Edward Feigenbaum) for pioneering the design and construction of large scale artificial intelligence systems, demonstrating the practical importance and potential commercial impact of artificial intelligence technology. Indeed, there isnt a major award that he hasnt won - the French Legion of Honour in 1984, the IBM Research Ralph Gomory Fellow Award in 1991, the Padma Bhushan in 2001, the Okawa Foundation Okawa Prize in 2004, the Honda Foundation Honda Prize in 2005, and the U.S. National Science Board Vannevar Bush Award in 2006.
Unaffected by his success, he still dreams of a world where those at the bottom of the pyramid can benefit from the technologies that he and others are helping to create. In a speech in 2021 when he was conferred the Computer History Museum Fellow Award for his lifes work on artificial intelligence, robotics, and computer science education, Reddy said Looking further in the future I see the emergence of personalized guardian angels that will get the right information to the right people at the right time in the right language with the right level of detail.
Sundeep Khanna is a senior journalist and the author of the recently released book 'Cryptostorm: How India became ground zero of a financial revolution'. Views are personal, and do not represent the stand of this publication.
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Opinion | It’s the End of Computer Programming as We Know It. (And I Feel Fine.) – The New York Times
Programming will be obsolete, Matt Welsh, a former engineer at Google and Apple, predicted recently. Welsh now runs an A.I. start-up, but his prediction, while perhaps self-serving, doesnt sound implausible:
I believe the conventional idea of writing a program is headed for extinction, and indeed, for all but very specialized applications, most software, as we know it, will be replaced by A.I. systems that are trained rather than programmed. In situations where one needs a simple program those programs will, themselves, be generated by an A.I. rather than coded by hand.
Welshs argument, which ran earlier this year in the house organ of the Association for Computing Machinery, carried the headline The End of Programming, but theres also a way in which A.I. could mark the beginning of a new kind of programming one that doesnt require us to learn code but instead transforms human-language instructions into software. An A.I. doesnt care how you program it it will try to understand what you mean, Jensen Huang, the chief executive of the chip-making company Nvidia, said in a speech this week at the Computex conference in Taiwan. He added: We have closed the digital divide. Everyone is a programmer now you just have to say something to the computer.
Wait a second, though wasnt coding supposed to be one of the cant-miss careers of the digital age? In the decades since I puttered around with my Spectrum, computer programming grew from a nerdy hobby into a vocational near-imperative, the one skill to acquire to survive technological dislocation, no matter how absurd or callous-sounding the advice. Joe Biden to coal miners: Learn to code! Twitter trolls to laid-off journalists: Learn to code! Tim Cook to French kids: Apprenez programmer!
Programming might still be a worthwhile skill to learn, if only as an intellectual exercise, but it would have been silly to think of it as an endeavor insulated from the very automation it was enabling. Over much of the history of computing, coding has been on a path toward increasing simplicity. Once, only the small priesthood of scientists who understood binary bits of 1s or 0s could manipulate computers. Over time, from the development of assembly language through more human-readable languages like C and Python and Java, programming has climbed what computer scientists call increasing levels of abstraction at each step growing more removed from the electronic guts of computing and more approachable to the people who use them.
A.I. might now be enabling the final layer of abstraction: the level on which you can tell a computer to do something the same way youd tell another human.
So far, programmers seem to be on board with how A.I. is changing their jobs. GitHub, the coders repository owned by Microsoft, surveyed 2,000 programmers last year about how theyre using GitHubs A.I. coding assistant, Copilot. A majority said Copilot helped them feel less frustrated and more fulfilled in their jobs; 88 percent said it improved their productivity. Researchers at Google found that among the companys programmers, A.I. reduced coding iteration time by 6 percent.
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UC Davis C-STEM trains Redlands teachers on bringing computer science into math – EurekAlert
image:Twenty-five teachers from Redlands Unified School District recently completed training by the UC Davis C-STEM Center and UC Riverside on integrating robotics and computing into math classes. view more
Credit: Redlands Unified School District
Twenty-five teachers from Redlands Unified School District in southern California recently completed training in integrating computer science into math education through a joint program offered by the University of California, Davis, and UC Riverside Extension. TheJoint Computer Science Supplementary Teaching Credential Authorization Programhas helped Redlands address gaps in student opportunity and achievement, and teachers skills.
Improving math instruction for student success is the most challenging task in education. Redlands partnered with UC Davis to make math instruction with computer science a reality for many of our students who have historically disconnected from learning math, said Ken Wagner, assistant superintendent of Redlands Unified School District. More students are demonstrating resilience and persistence in their math progression than ever before, which to us, is an immeasurable outcome.
Redlands is the first school district in the nation that has 25 teachers who have gone through four college-level courses needed to earn their credential. This innovative practice is transforming public K-12 math and computer science education.
C-STEM training and use of the robotics and programming skills that are taught has been the best professional development training of my 28-year career, said teacher Roland Hosch. I am very grateful to be a part of it and my classroom is a more efficient and more effective place to learn because of it.
The UC Davis Center for Integrated Computing and STEM Education, or C-STEM, program aims to transform K-12 math, computer science and STEAM (science, technology, engineering, arts and mathematics) education through integrated learning.Students learn to solve math and algebra problems through coding and by programming small, modular robots. TheC-STEM Math-ICT curriculumprovides up to 13 years of integrated math and computer science teaching from kindergarten through high school. C-STEM courses have UC A-G status, satisfying admissions requirements for the University of California and California State Universities.
Redlands USD implemented the C-STEM program in 2018 to narrow the achievement gap in math and address the opportunity gap in computing. The district has expanded from two middle school teachers initially to 35 teachers, including all the districts middle and high schools as well as six elementary schools, in 2022-23.
Redlands has seen results with the program. From the 2018-19 school year to 2021-22,average scores on the mathematics diagnostic testing project (MDTP) rose by more than 13% in C-STEM classescompared to peers in traditional math classes in the same schools. (Redlands students can choose either a C-STEM math track, plus a computer science class, or a traditional math class.)
C-STEM brings joy into the classroom, said Deepika Srivastava, STEAM coordinator for the Redlands school district. If you give a student a worksheet of math problems and they get 20 or 30% right, it tells the student Youre bad at this, she said.
But if they are trying to solve a problem by writing a program, they can get it 20 or 30% right, get some feedback, and improve. When youre solving a math problem by coding, its an iterative process, theres constant feedback, she said. It encourages students to keep trying and develops skills in critical thinking, problem solving and perseverance.
Further, she said that the C-STEM math classes have become more diverse, with more representation of girls, Black and Latinx students, and students from lower socioeconomic backgrounds. Perhaps most significantly, surveys of students entering and completing the program show a big swing from I hate math to I enjoy math.
Redlands is a good example of a school district working with C-STEM to address the opportunity gap in math education, said Harry Cheng, director of the C-STEM center and professor in the UC Davis Department of Mechanical and Aerospace Engineering. Schools are working to get students back on track after the pandemic. The students are doing better, closing the achievement gap and teachers are learning new skills, closing the skills gap.
Srivastava, who visits all the district classrooms using the C-STEM program, said that the program also has positive effects on student behavior.
When a kid fails at math, they get the message that theyre not good at math and then they dont give 100%. But when theyre building a robot, their entire attitude changes. I truly believe this is where the future is.
The UC Davis Center for Integrated Computing and STEM Education is a comprehensive program that includes the annual RoboPlay competition in which students compete with other schools to solve challenges with coding and robotics. In addition to K-12 curricula and professional development for teachers, the center also supports schools and districts to organize their afterschool and summer programs, including robotics camps, robotics-math camps, the Girls In Robotics Leadership (GIRL/GIRL+) camps, and Ujima GIRL Project for African American middle and high school girls.
Ever since the pandemic, we have been challenged to find new ways to engage our students, said teacher Noah Rosen. The investment that Redlands Unified has made in my continued training in C-STEM has provided me with a whole new treasure chest of tools that I can use to elevate the effectiveness of my classroom instruction through computer science.
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UC Davis C-STEM trains Redlands teachers on bringing computer science into math - EurekAlert
UC Davis C-STEM Trains Redlands Teachers on Bringing Computer … – University of California, Davis
Twenty-five teachers from Redlands Unified School District in southern California recently completed training in integrating computer science into math education through a joint program offered by the University of California, Davis, and UC Riverside Extension. The Joint Computer Science Supplementary Teaching Credential Authorization Program has helped Redlands address gaps in student opportunity and achievement, and teachers skills.
Improving math instruction for student success is the most challenging task in education. Redlands partnered with UC Davis to make math instruction with computer science a reality for many of our students who have historically disconnected from learning math, said Ken Wagner, assistant superintendent of Redlands Unified School District. More students are demonstrating resilience and persistence in their math progression than ever before, which to us, is an immeasurable outcome.
Redlands is the first school district in the nation that has 25 teachers who have gone through four college-level courses needed to earn their credential. This innovative practice is transforming public K-12 math and computer science education.
C-STEM training and use of the robotics and programming skills that are taught has been the best professional development training of my 28-year career, said teacher Roland Hosch. I am very grateful to be a part of it and my classroom is a more efficient and more effective place to learn because of it.
The UC Davis Center for Integrated Computing and STEM Education, or C-STEM, program aims to transform K-12 math, computer science and STEAM (science, technology, engineering, arts and mathematics) education through integrated learning. Students learn to solve math and algebra problems through coding and by programming small, modular robots. The C-STEM Math-ICT curriculum provides up to 13 years of integrated math and computer science teaching from kindergarten through high school. C-STEM courses have UC A-G status, satisfying admissions requirements for the University of California and California State Universities.
Redlands USD implemented the C-STEM program in 2018 to narrow the achievement gap in math and address the opportunity gap in computing. The district has expanded from two middle school teachers initially to 35 teachers, including all the districts middle and high schools as well as six elementary schools, in 2022-23.
Redlands has seen results with the program. From the 2018-19 school year to 2021-22, average scores on the mathematics diagnostic testing project (MDTP) rose by more than 13% in C-STEM classes compared to peers in traditional math classes in the same schools. (Redlands students can choose either a C-STEM math track, plus a computer science class, or a traditional math class.)
C-STEM brings joy into the classroom, said Deepika Srivastava, STEAM coordinator for the Redlands school district. If you give a student a worksheet of math problems and they get 20 or 30% right, it tells the student Youre bad at this, she said.
But if they are trying to solve a problem by writing a program, they can get it 20 or 30% right, get some feedback, and improve. When youre solving a math problem by coding, its an iterative process, theres constant feedback, she said. It encourages students to keep trying and develops skills in critical thinking, problem solving and perseverance.
Further, she said that the C-STEM math classes have become more diverse, with more representation of girls, Black and Latinx students, and students from lower socioeconomic backgrounds. Perhaps most significantly, surveys of students entering and completing the program show a big swing from I hate math to I enjoy math.
Redlands is a good example of a school district working with C-STEM to address the opportunity gap in math education, said Harry Cheng, director of the C-STEM center and professor in the UC Davis Department of Mechanical and Aerospace Engineering. Schools are working to get students back on track after the pandemic. The students are doing better, closing the achievement gap and teachers are learning new skills, closing the skills gap.
Srivastava, who visits all the district classrooms using the C-STEM program, said that the program also has positive effects on student behavior.
When a kid fails at math, they get the message that theyre not good at math and then they dont give 100%. But when theyre building a robot, their entire attitude changes. I truly believe this is where the future is.
The UC Davis Center for Integrated Computing and STEM Education is a comprehensive program that includes the annual RoboPlay competition in which students compete with other schools to solve challenges with coding and robotics. In addition to K-12 curricula and professional development for teachers, the center also supports schools and districts to organize their afterschool and summer programs, including robotics camps, robotics-math camps, the Girls In Robotics Leadership (GIRL/GIRL+) camps, and Ujima GIRL Project for African American middle and high school girls.
Ever since the pandemic, we have been challenged to find new ways to engage our students, said teacher Noah Rosen. The investment that Redlands Unified has made in my continued training in C-STEM has provided me with a whole new treasure chest of tools that I can use to elevate the effectiveness of my classroom instruction through computer science.
Excerpt from:
UC Davis C-STEM Trains Redlands Teachers on Bringing Computer ... - University of California, Davis
BlueSky Thinking Ranking of Computer Science Rankings 2022/23 – Forbes
BlueSky Ranking of Computer Science Rankings 2022/23
Sam Altman, the CEO of OpenAI received his first computer at the age of eight. He studied computer science at Stanford University, but dropped out after one year to co-found Loopt, a social networking application that was sold a few years later for $43.4 million.
He became a partner and then president at Y Combinator, the startup accelerator which has supported Airbnb, Coinbase, Dropbox, Quora, Stripe and more than 4,000 other companies with a combined valuation of more than $600 billion by January 2023.
In 2020, he left Y Combinator to focus full-time on OpenAI as CEO, and since the release of ChatGPT in November 2022 we have been talking about little else.
Now is the best time to start a career in tech, he said to an audience last week at the Technological University of Munich, Germanys top-ranked institution for computer science and engineering.
So whats the secret to kickstart your career in tech? For many the journey begins with studies in computer science, now one of the hottest majors on campus with the promise of six-figure starting salaries that used to be the preserve of MBAs.
BlueSky Thinking has compiled the Ranking of Computer Science Rankings 2023, aggregating the results of the four major global subject rankings published every year by Times Higher Education (THE), QS, US News and ARWU (Shanghai).
You can view the results for the worlds top 50 universities for computer science here.
While U.S. universities fill the top four places, and Harvard, Princeton, Cornell and U Washington also make the top 15, institutions in Europe, Canada and Asia Pacific represent close to 60% of the worlds top 50.
BlueSky Ranking of Computer Science Rankings 2022/23
Each university subject ranking uses a distinct methodology and measures different things with the inherent limitations of each assessment, so doing particularly well in one ranking and less well in another is reflected in the overall performance.
The University of Oxford is ranked #1 in the world by THE, but only #11 by US News, while Chinas Tsinghua University is ranked #1 by US News but only #15 by QS. But all four rankings consistently rate MIT, Stanford and Carnegie Mellon at the top.
However, they cannot agree on the University of Cambridge, the alma mater of Alan Turing who is widely considered to be the father of theoretical computer science and artificial intelligence. There are over 300 companies started by computer science and technology graduates and staff of the university, and research that continues to lead the field.
Though Cambridge is ranked #6 in computer science by THE and #7 by QS, US News has them at #41 and ARWU Shanghai only #62.
According to compensation data company, Payscale the average base salary in the U.S. with a Masters in computer science is $109k per year, quickly rising based on seniority. And demand is there. The International Monetary Fund (IMF) estimates that the worlds tech talent shortage will swell to more than 85 million tech workers by 2030.
Thats just as well, because tuition of a Computer Science program from one of the leading schools in the US can be over $60,000 per year. In Europe salaries are lower, but beyond the elite universities there are new entrants in Higher Education, such as the Open Institute of Technology (OPIT) that have brought together faculty from the likes of the University of Michigan, Northwestern and McGill to offer a BSc in Computer Science and a MSc in Applied Data Science & AI for as little as 300 per month. As an EU-accredited institution, international students will be able to apply for jobs in the EU, with salaries to match.
The Future Of Learning - Online Innovation For A Career In Tech
So now is a great time to start a career in tech, as OpenAIs Sam Altman insists. In his case, Altman never finished his undergrad at Stanford, joining an illustrious of computer science dropouts that include Mark Zuckerburg who left Harvard in his sophomore year to dedicate his time to Facebook, and Bill Gates who walked away from devising algorithms for pancake sorting as part of his mathematics and graduate level computer science courses at Harvard to start a software company with Paul Allen that is now Microsoft.
Now is the best time to start a career in tech. Sam Altman, CEO of OpenAI and founder of ChatGPT ... [+] (AP Photo/Alastair Grant)
When explaining his decision to leave Harvard, Gates said "if things hadn't worked out, I could always go back to school. I was officially on leave."
That wasnt quite the case for Apple co-founder, Steve Wozniak who was expelled from the University of Colorado, Boulder for hacking the universitys computer system. He later transferred to UC Berkeley, where Steve Jobs would visit him a few times a week. Wozniak dropped out of college soon after, this time to start a business together.
But for every entrepreneurial tech superstar who never finished school, there are plenty of others that used their computer science studies to incredible effect. While studying computer engineering at the University of Michigan, the co-founder of Google Larry Page created an inkjet printer made of Lego bricks. Meanwhile, his future business partner Sergey Brin was completing his computer science undergrad at the University of Maryland. They would both go on to get their MSc computer science at Stanford, and from there begin a computer science Ph.D., co-authoring a paper titled, The Anatomy of a Large-Scale Hypertextual Web Search Engine. Dorm rooms became laboratories and offices, and the rest is history.
Ginni Rometty, the former chairman and CEO of IBM the first woman to head the company - graduated with high honors from Northwestern University with a bachelors degree in computer science and electrical engineering. This was the same combination of majors for Jeff Bezos, founder of Amazon who graduated from Princeton in 1986.
Reed Hastings, the co-founder of Netflix was rejected from his first-choice MIT, and obtained a Masters in Computer Science at Stanford in 1988, a decade before the former CEO of Yahoo!, Marissa Mayer. The co-founder and CEO of Dropbox, Drew Houston was offered a place to study computer science at MIT and it was there that he met his future business partner, Arash Ferdowsi.
But for Barbara Liskov, whose pioneering contributions to programming languages and distributed computing was recognized with the 2008 Turing Award, the highest distinction in computer science, her graduate school application to Princeton was unsuccessful as the Ivy League school did not accept female students in mathematics. In March 1968 she became one of the first women in the U.S. to be awarded a Ph.D. from a computer science department when she was awarded her degree from Stanford University.
Anita Borg is celebrated for advocating for womens representation and professional advancement in technology, and founded the Institute for Women and Technology and the Grace Hopper Celebration of Women in Computing. Borg was awarded a Ph.D. in computer science by NYU in 1981.
The presence - or absence - of women in the computing and technological fields, as students, ... [+] inventors, creators and educators, will define our technological future. Anita Borg, Institute for Women and Technology (Photo by Jerry Telfer/San Francisco Chronicle via Getty Images)
Outside the U.S., Ma Huateng (Pony Ma), co-founder and CEO of Tencent, one of the most valuable companies in Asia, received a BSc in computer science from Shenzen University. He is the first citizen from China to enter Forbes top 10 richest list.
And when it comes to widely-used programming languages, Python was created by Guido Van Rossum who computer science at the University of Amsterdam, while University of Calgary and Carnegie Mellon University computer scientist, James Gosling founded and led the design of Java.
And if you do fancy combining undergraduate studies with an MBA, look no further than Satya Nadella, CEO of Microsoft who headed to the U.S. from India to study computer science at the University of Wisconsin Milwaukee and then got his MBA from Chicago Booth. There is also Jeremy Stoppelman, co-founder and CEO of Yelp with a BS computer engineering from Illinois at Urbana-Champaign and an MBA from Harvard Business School.
And lets not forget that Jimmy Fallon, the late-night talk show host was originally a computer science major at The College of Saint Rose in Albany, New York before switching to communications in his senior year.
So what about you? Whether at one of the worlds top 50 computer sciences schools, or a more affordable online alternative, are you ready to start your career in tech?
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BlueSky Thinking Ranking of Computer Science Rankings 2022/23 - Forbes
Cutting-Edge Algorithm Identifies Forest Fire Risk in Canada – Northeastern University
Where theres smoke, theres fireand with tools ranging from fire tower lookouts to satellites, a forest fire can be readily detected.
But what if we could easily predict where a forest fire will occur before the smoke appears? Thats the goal of Michal Aibin, a visiting associate teaching professor in the Khoury College of Computer Sciences at Northeastern Universitys campus in Vancouver, British Columbia.
Currently when we think about forest fires, and all the research that is happening around the world the majority of the worklike 90 percent of the workfocuses on the detection of the fire, Aibin says. But obviously when were detecting the fire, it means the fire is already there we want to predict the fires in the area.
Aibin and his team in Vancouver have developed a computer vision algorithm that assesses and classifies forests according to their fire risk. This enables foresters to see the most at-risk areas and preemptively direct appropriate fire-prevention efforts.
Our goal is to provide as much information as possible, so they can implement prevention strategiesmaintain the forest, do cleanup of debris, maybe a controlled cutting and in the event of a fire, this fire wont spread that far or wont be as devastating as if that fuel was there, Aibin says.
Its a timely project, Aibin says. Roughly 1,800 forest fires burned 135,000 hectares (a hectare contains roughly 2.5 acres) in Canada last year, costing $650 million, Aibin says. Worldwide, fires cost about $50 billion a year, according to the World Economic Forum.
That acreage and cost is likely to increase as the climate changes, cycles of drought become more extreme and carbon is released by wildfires. The WEF said wildfires released an estimated 645 million tons of carbon dioxide into the atmosphere in 2021.
Its become challenging more and more every year, Aibin says. Because of (fires) we release more carbon in the air and then the climate gets warmer, so its a kind of loop that we need to break.
Its also not just the forests or grasslands that are affected. Aibin says smoke from forest fires can travel long distances and degrade air quality, exacerbating human respiratory problems such as asthma.
But Aibins work occurs before the smoke starts to rise.
He uses a drone to scan woodland areas, collecting data such as the amount of flammable debris in the area, the species of trees and their respective flammability, the proximity of water sources, areas with diseases that weaken the trees and more.
The information is put into a mapping program which then displays the forest and assigns different color-coded classifications based on its flammability riskfrom low to extreme.
That information is then made available to foresters who can see the most fire-prone areas, learn why that area is particularly risky, and direct mitigation and prevention strategies.
So far, Aibin has focused on forests near the Thompson River in British Columbia, working with Natural Resources Canada and Transport Canada (government departments responsible for natural resources including forests, and transportation in Canada, respectively) to collect and analyze data.
But he sees a worldwide application for the program, and is working on expanding the amount and type of risk factors that it analyzes to make it more geographically specific.
Expand, expandget more data, more tree species, more risk factors involved, and get a system that can be applied in British Columbia, all of Canada, the States, and finally globally, Aibin says.
He also hopes his computer science students can be inspired to apply their skills beyond traditional programming.
We can make a difference, we can make an impact, Aibin continues. Not only learn these computing skills to be a programmer or tester or designer, we teach those skills, but also with that role comes the responsibility to make an impact in the world.
Cyrus Moulton is a Northeastern Global News reporter. Email him at c.moulton@northeastern.edu. Follow him on Twitter@MoultonCyrus.
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Cutting-Edge Algorithm Identifies Forest Fire Risk in Canada - Northeastern University
Taking the Time to Implement Trust in AI – Illinois Computer Science News
For years, but especially recently, the accelerated pace of development for new machine learning technology has caught the eye of researchers who also value security and privacy.
Vulnerabilities to these advancements and their AI applications do, of course, leave users open to attacks.
In response, Illinois Computer Science professor Bo Li has positioned her research career at the intersection of trustworthy machine learning, with an emphasis on robustness, privacy, generalization, and the underlying interconnections of these items.
As we have become increasingly aware, machine learning currently has been ubiquitous in the technology world through different domains ranging from autonomous driving, large language models, ChatGPT, etc., Li said. It is also a benefit found in many different applications, like face recognition technology.
The troubling aspect is that we have also learned threat these advancements are vulnerable to attack.
Earlier this month,Bo Li logged on to her computer and noticed several emails from colleagues and students congratulating her.
However, what exactly for, she wasnt sure.
I found out, eventually, the way we find out so much information these days on Twitter, Li said with a laugh.
There she saw several notifications stemming from IEEEs announcement of the AI 10 to Watch List for 2022 which included her name.
I was so pleased to hear from current and past students and collaborators, who said such nice things to me. Im also delighted to be a part of this meaningful list from IEEE, Li said.
The Illinois CS professors early-career in academia has become quite decorated already, with awards like the IJCAI Computers and Thought Award, Alfred P. Sloan Research Fellowship, NSF CAREER Award, AI's 10 to Watch List from IEEE, MIT Technology Review TR-35 Award, etc.
Lis work also includes research awards from tech companies such as Amazon, Meta, Google, Intel, MSR, eBay, and IBM, and best paper awards at several top machine learning and security conferences.
Each recognition and award signify a tremendous amount support for my research, and each have provided me confidence in the direction that Im working on, Li said. Im very glad and grateful to all the nominators and communities. Every recognition, including the IEEE AI 10 to Watch List, provide a very interesting and important signal to me that my work is valuable in different ways to different people.
Calling it a golden age in AI, San Murugesan, IEEE Intelligent Systems Editor in Chief, stressed the importance of this years recipients who are rising stars in a field that offers an incredible amount of opportunity.
Li thanked her mentor here at Illinois CS, professor David Forsyth, as well as influences from her time at the University of California, Berkely like Dawn Song and Stuart Russell.
Through their steady guidance, she has prepared her early academic career for success. And Li is ready to return the favor for the next generation of influential AI academicians.
The first piece of advice I would give is to read a lot of good literature and talk with senior people you admire. Therefore, develop your own deep and unique research taste, Li said. Great researchers provide insights that are both unique and profound. Its rare, and it takes hard work. But the work is worth it.
In an already successful start to her career focused on this problem, Li also earned $1 million to align her Secure learning Lab to DARPAs Guaranteeing AI Robustness Against Deception (GARD) program.
The project, she said, is purely research motivated. It will separate those involved into different teams; the red team presents the vulnerability or attack while the blue team attempts to defend against it.
Organizers believe the vulnerability to be too complex to solve during the duration of this project, but the value of the work goes well beyond simply solving the vulnerability.
For the students participating from my lab, this presents an opportunity to work on an ambitious project without the pressure of a leaderboard or competitive end result, Li said. Its ultimately an evaluation that can help us understand the algorithm involved. Its open source and structured with consistent meetings, so we can all work together to uncover advancements and understand them best.
The ultimate goal, for both her and her students, is to define this threat model in a more precise way.
We cannot say our system or machine learning system is trustworthy against any arbitrary attack that's almost impossible. So, we have to characterize our threat model in a precise way, Li said. And we must define trustworthy requirements. For instance, given a task, given a data set to provide a model, we have this different specific requirement.
And then we can optimize an end-to-end system, which can give you guarantees for the metrics you care about. At the same time, hopefully, we can provide tighter guarantees by optimizing the algorithm, optimizing the data, optimizing other components in this process.
This continues work Li has conducted with her students for years into the concept of Trustworthy AI.
For example, a previous breakthrough considered the consistent give-and-take between components that create Trustworthy AI.
Researchers felt that there were certain tradeoffs that had to occur between accuracy and robustness in their systems combating machine learning vulnerabilities.
But Li said that she and her group proposed a framework called Learning-Reasoning, which integrated human reasoning into the equation to help mitigate such tradeoffs.
What were striving for is a scenario in which the people responsible for developments in AI understand that both robustness and accuracy or safety are important to prioritize at the same time, Li said. Often times, processes simply prioritize performance first. Then organizers worry about safeguarding it later. I think both concepts can go together, and that will help the proper development of new AI and ML based technologies.
Additional work from her students has led to progress in related areas.
For example, Ph.D. student Linyi Li has built a unified toolbox to provide certified robustness for Deep Neural Networks.
Also, Ph.D. student Chejian Xu and masters student Jiawei Zhang have generated different safety-critical scenarios for autonomous vehicles. They will host a CVPR workshop on it in June.
Finally, Zhang and Ph.D. student Mintong Kang built the scalable learning-reasoning framework together.
These sorts of developments have also led to Lis involvement in the newly formed NSF AI Institute for Agent-based Cyber Threat Intelligence and OperatioN (ACTION).
Led by the University of California, Santa Barbara, the NSF ACTION Institute also aims to revolutionize protection for mission-critical systems against sophisticated cyber threats.
The most impactful potential outcomes from the ACTION Institute include a range of fundamental algorithms for AI and cybersecurity, and large-scale AI-enabled systems for cybersecurity tasks with formal security guarantees, which are realized by not only purely data-driven models, but also logic reasoning based on domain knowledge, weak human supervision, and instructions. Such security protection and guarantees will hold against unforeseen attacks, as well, Li said.
Its clear that, despite the speed with which AI and machine learning developments occur, Li and her students are providing a presence dedicated to stabilizing and securing this process moving forward.
Read more here:
Taking the Time to Implement Trust in AI - Illinois Computer Science News
OPINION: Teaching computer science requires a new approach – The Longmont Leader
A professor of learning technologies discusses the major hurdles to teaching computer science education in K-12 schools
The following article, written by Lauren Margulieux, Georgia State Universityoriginally appeared on The Conversation and is published here with permission:
Despite growing demand for computer science skills in professional careers and many areas of life, K-12 schools struggle to teach computer science to the next generation.
However, a new approach to computer science education called integrated computing addresses the main barriers that schools face when adding computer science education. These barriers include a lack of qualified computer science teachers, a lack of funds and a focus on courses tied to standardized tests.
Integrated computing teaches computer science skills like programming and computer literacy within traditional courses. For example, students can use integrated computing activities to create geometric patterns in math, simulate electromagnetic waves in science and create chatbots for literary characters in language arts.
As a professor of learning technologies, I have been designing integrated computing activities for K-12 students for the past five years. I work with faculty and students in teacher training programs to create and test integrated computing activities across all academic subjects.
In my research, I have found that integrated computing solves three major hurdles to teaching computer science education in K-12 schools.
Fitting a new academic discipline into an already crowded curriculum can be a challenge. Integrated computing allows computer science education to become part of learning in other classes, the way reading skills are also used in science, math and language arts classes.
Teacher knowledge is another difficulty when it comes to teaching computer science in K-12 schools. While people who specialize in computer science are often recruited to more lucrative careers than teaching, integrated computing develops all teachers computer science knowledge. Teachers do not need to become computer science experts to teach computer literacy and programming skills to their students.
In fact, the most surprising result of my research is how quickly teachers learn to teach integrated computing activities. In about two hours, teachers can use a pre-made computer science lesson in their classrooms. In the future, I will teach them to use artificial intelligence to create their own lessons for their students. For example, a science teacher recently asked me how she could create a data analysis activity for her class. AI tools would allow her to quickly design the technical aspects of this activity.
And finally, integrated computing also addresses students reluctance to take elective computer science classes when they have little knowledge of computer science. In 2022, over half of U.S. public high schools offered computer science, but just 6% of students took these classes. Students who do take computer science in high school typically have had early exposure to computer science. Integrated computing can give all students early exposure to computer science, which I believe will increase the number of students who take computer science courses later in school.
Early exposure to computer science in school is especially important for students from groups underrepresented in computer science. A 2022 report from Code.org, a nonprofit that advocates for more computer science education in K-12 schools, found that students who are Latino, female or from low-income or rural areas are less likely to be enrolled in foundational computer science courses.
Teachers who want to build their computer science knowledge and apply it to their classroom can try these free self-paced, online integrated computing courses that I developed, and which are tied to micro-credentials. Also, this sortable list of integrated computing activities provides free lesson plans. The activities require only a computer no prior knowledge is needed, and young learners can complete them outside of class, too.
Integrated computing provides a path to increase computer literacy for all K-12 students. As technology advances at an increasing rate, I believe schools must take care that our young people do not fall behind.
Lauren Margulieux, Associate Professor of Learning Technologies, Georgia State University
This article is republished from The Conversation under a Creative Commons license. Read the original article.
Excerpt from:
OPINION: Teaching computer science requires a new approach - The Longmont Leader