- Ai - Engineering Mailing Lists

AI Seminar: "From Pixels to Measurements: Understanding the Dynamic World" by Dr. Adam Harley
by Abou Mrad, Christian 05 Dec '24

05 Dec '24

Dear all, Our next AI seminar is scheduled for Friday, December 6th. Talk details: AI Seminar: From Pixels to Measurements: Understanding the Dynamic World Speaker: Dr. Adam Harley, Postdoctoral Scholar, Stanford University Time: 2:00 PM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: In computer vision, “video understanding” typically concerns summarization: tracking the main objects, or describing the main actions. While progress here has been impressive, many practical applications require extracting information which is much more fine-grained. For example, biologists are highly interested in tracking specific key points of organisms in long video recordings. Algorithms for such tasks require the generality and precision of low-level vision methods (e.g., optical flow), but benefit from knowledge about the 3D physical world (e.g., things continue to exist while they are occluded). In this talk, I will present our progress on this crucial space of problems. Our central contribution is to widen the window of “temporal context” used for inference: instead of tracking entities from one frame to the next, we inspect dozens of frames simultaneously, and return an answer that makes sense for the full clip. I will discuss the methods and datasets that we have created to drive progress along these lines, and highlight natural science applications of the work. Finally, I will introduce our ongoing effort to produce a “foundation model” of motion, aiming to deliver reliable arbitrary-granularity tracking for the huge variety of real-world situations where this is required. Speaker Bio: Adam Harley is a postdoctoral scholar at Stanford University, working with Leonidas Guibas. He received a Ph.D. in robotics from Carnegie Mellon University, where he worked with Katerina Fragkiadaki. He received his M.S. in Computer Science at Toronto Metropolitan University, working with Kosta Derpanis. Adam is a recipient of the NSERC PGS-D scholarship, and the Toronto Metropolitan University Gold Medal. His research interests lie in Computer Vision and Machine Learning, particularly for 3D understanding and fine-grained tracking. If you would like to meet with the speaker one-on-one, please email tadepall(a)oregonstate.edu<mailto:tadepall@oregonstate.edu> by Tuesday. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: "Principles for AI Governance"
by Abou Mrad, Christian 25 Nov '24

25 Nov '24

Dear all, A special AI seminar is scheduled for Tuesday, November 26. Talk details: AI Seminar: "Principles for AI Governance" Speaker: Kendrea Beers, Horizon Junior Fellow, Georgetown University, Center for Security and Emerging Technology Time: 12:00 PM Location: BEXL 321 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Event Description: Researchers at Georgetown University’s Center for Security and Emerging Technology (CSET) have identified three principles for effective AI governance: policymakers should 1) monitor the landscape of AI risk, 2) promote AI literacy among themselves and the public, and 3) develop policies that can adapt to rapid technological changes. Kendrea will unpack these principles and share insights on their implementation, highlighting topics such as sociotechnical AI safety and if-then commitments. Speaker Bio: Kendrea Beers is a Horizon Junior Fellow at Georgetown University’s Center for Security and Emerging Technology (CSET), where she works on the Foundational Research Grants team and the CyberAI Project. While completing her MS in Artificial Intelligence at Oregon State University, she conducted research in AI safety and co-led the AI Graduate Student Association. She also holds a BS in Philosophy with minors in Mathematics and Computer Science from the Oregon State University Honors College. She has conducted AI governance research at Cornell University and computer science research at Galois and the University of Notre Dame. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou-Mrad Graduate Student Oregon State University

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AI Seminar: "Challenges and Trade-Offs for Graph Neural Networks" by Dr. Mitchell Black
by Abou Mrad, Christian 22 Nov '24

22 Nov '24

Dear all, Our next AI seminar is scheduled for Friday, November 22. Talk details: AI Seminar: "Challenges and Trade-Offs for Graph Neural Networks" Speaker: Dr. Mitchell Black, NSF EnCORE Postdoctoral Scholar, University of California San Diego Time: 2:00 PM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: Since their introduction around a decade ago, graph neural networks (GNNs) have quickly become the state-of-the-art method for many graph learning tasks. However, existing graph neural networks are known to suffer from various problems. For example, no known graph neural network are known to be perfectly expressive, so designing a graph neural network can be a matter of managing different trade-offs. In this talk, I will discuss several problems affecting graph neural networks. First, I will discuss a recent work on a problem called oversquashing, where a GNN struggles to send information between different nodes in the graph due to certain bottlenecks in the graph's topology. Our work presents a way to quantify which graphs are most susceptible to oversquashing and proposes techniques to remedy oversquashing by altering the graph's topology. After that, I will discuss challenges for using transformers as graph neural networks. Graph transformers rely on positional encodings to represent the graph, but the number of competing positional encodings has outpaced our ability to understand their differences. I will discuss ways of comparing these positional encodings and our recent work aimed at unifying some recent trends in the design of positional encodings. Speaker Bio: Mitchell Black is an NSF EnCORE Postdoctoral Scholar at the University of California San Diego. His research aims to understand problems in machine learning using the tools of theoretical computer science. He is particularly interested in the fields of graph neural networks, spectral graph theory, topology, and their intersections. He completed his PhD in Computer Science from Oregon State University in 2024. If you would like to meet with the speaker one-on-one, please email tadepall(a)oregonstate.edu<mailto:tadepall@oregonstate.edu> by Tuesday. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou-Mrad Graduate Student Oregon State University

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AI Seminar: "Curious Embeddings, Hazy Oracles, and the Path to Safe, Cooperative AI" by Dr. Jason Corso
by Abou Mrad, Christian 15 Nov '24

15 Nov '24

Dear all, Our next AI seminar is scheduled for Friday, November 15. Talk Details: * AI Seminar: "Curious Embeddings, Hazy Oracles, and the Path to Safe, Cooperative AI" * Speaker: Dr. Jason Corso, Professor of Robotics, Electrical Engineering, and Computer Science, University of Michigan * Time: 2:00 PM * Location: KEC 1001 and Zoom * Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: Cooperation through safe and trustworthy communication and interaction is fundamental to how human teams accomplish complex tasks. Yet, despite significant--and sometimes revolutionary--advances in AI, we have barely begun to unlock the potential of safe, cooperative AI. This may stem from our limited understanding of how multimodal, large-scale AI models function, the one-sided nature of contemporary, fully-supervised AI approaches, or social concerns about human-AI collaboration. In this talk, I will delve into these layers of inquiry, beginning with a principled exploration of what the embeddings in large-scale foundation models reveal about the underlying problem and data, including new results disentangling sample-size from Bayes error and decision-boundary complexity. I will then introduce the concept of the human collaborator as a “hazy oracle”--a fallible partner rather than an omniscient information source--and establish a framework for modeling human-supplied error during collaboration. Building on these foundational insights, I will conclude with applications of these ideas to foster safe and effective human-AI collaboration in the health sciences. Speaker Bio: Jason Corso is Professor of Robotics, Electrical Engineering and Computer Science at the University of Michigan and Co-Founder / Chief Scientist of the AI startup Voxel51. He received his PhD and MSE degrees at The Johns Hopkins University in 2005 and 2002, respectively, and the BS Degree with honors from Loyola College In Maryland in 2000, all in Computer Science. He is the recipient of a U Michigan EECS Outstanding Achievement Award 2018, Google Faculty Research Award 2015, the Army Research Office Young Investigator Award 2010, National Science Foundation CAREER award 2009, SUNY Buffalo Young Investigator Award 2011, a member of the 2009 DARPA Computer Science Study Group, and a recipient of the Link Foundation Fellowship in Advanced Simulation and Training 2003. Corso has authored more than 150 peer-reviewed papers and hundreds of thousands of lines of open-source code on topics of his interest including computer vision, robotics, data science, machine learning, AI, and general computing. He is a member of the AAAI, ACM, MAA and a senior member of the IEEE. If you would like to meet with the speaker one-on-one, please email tadepall(a)oregonstate.edu<mailto:tadepall@oregonstate.edu> by Tuesday. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou-Mrad Graduate Student Oregon State University

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AI Seminar: Responsible AI with International Standards
by Abou Mrad, Christian 04 Nov '24

04 Nov '24

Dear all, Our next AI seminar is scheduled for Friday, November 8th. Talk details: AI Seminar: Responsible AI with International Standards Speaker: Rohit Israni, Founder and CEO, Certient AI Time: 2:00 PM Location: KEC 1001 and Zoom Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: As artificial intelligence rapidly advances and becomes more pervasive in society, developing responsible AI practices and standards is crucial. This talk by Rohit Israni, Chair of INCITS/Artificial Intelligence (US AI standards national body that participates in ISO/IEC), will explore the current landscape of AI standards and guidelines for ethical AI development, with a focus on ISO/IEC 42001. The presentation will cover key aspects of ISO/IEC 42001, the world's first AI management system standard. It will examine important areas addressed by the standard, including AI governance, risk management, data protection, and continuous improvement. The talk will discuss how ISO/IEC 42001 provides a comprehensive framework for organizations to establish, implement, and improve their AI management systems. Students will gain insights into how ISO/IEC 42001 can help organizations navigate the complexities of AI management, ensuring that their AI systems are not only effective but also ethical, secure, and aligned with global standards. Speaker Bio: Rohit Israni is the founder and CEO of Certient AI<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fcertient.…>. He is also the Chair AI Standards for the US national body responsible for developing US positions and contributions to international AI standards being developed by ISO/IEC (ISO/IEC JTC 1/SC 42). SC 42 is the preeminent global committee with participation from 50 countries on developing horizontal ICT AI Standards. Rohit is also the liaison for SC 42 with Organization of Economic Cooperation and Development (OECD). Prior to founding Certient AI, he led Intel’s global scale ecosystem enabling programs in the Developer Relations Division for AI, Datacenter and Network, of which he co-founded the AI partnership program (Intel AI Builders). Israni earned a master’s degree in engineering with a specialization in robotics and AI from Tulane University. He also holds a master’s degree in management science & engineering from Stanford University where he was a part of the Stanford Technology Ventures Program. If you would like to meet with the speaker one-on-one, please email tadepall(a)oregonstate.edu<mailto:tadepall@oregonstate.edu> by Tuesday. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: What I Learned Serving as an AI Expert in the U.S. Congress
by Abou Mrad, Christian 24 Oct '24

24 Oct '24

Dear all, Reminder that our next AI seminar is scheduled for tomorrow, October 25th (Friday). Talk details: AI Seminar: What I Learned Serving as an AI Expert in the U.S. Congress Speaker: Kiri Wagstaff, AAAI Fellow Time: 2:00 PM, October 25 Seminar Location: KEC 1001 Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: What is Congress doing about artificial intelligence? I will share what I learned during a one-year position inside a U.S. Senate office as an AI expert through the AAAS Science and Technology Policy Fellowship program. There is a high demand for technical expertise within Congress, especially for AI. More than 300 AI-related bills have been introduced in the current congressional session; we’ll look at the key AI topics getting attention. I’ll describe how I developed a consumer AI literacy bill and then worked for months with a talented team to achieve the bill’s introduction in the Senate in July. I’ll also suggest ways that you can contribute your expertise and make a difference locally and nationwide. Speaker Bio: Kiri Wagstaff is a AAAI Fellow with a focus on deployed machine learning systems that help us explore, understand, and learn about the universe. She recently returned to Corvallis from Washington, D.C., after serving as an artificial intelligence expert in the U.S. Senate for a year. She previously served as a principal researcher in machine learning at the NASA Jet Propulsion Laboratory and an associate research professor and senior instructor at Oregon State University. She earned her Ph.D. in Computer Science from Cornell University, followed by an M.S. in Geological Sciences (University of Southern California) and an MLIS in Library and Information Science (San Jose State University). She received the Lew Allen Award for Excellence in Research and two NASA Exceptional Technology Achievement Medals. She serves on the AAAI U.S. Policy Committee and the OSU AI Program Executive Committee. She will teach “Machine Learning Challenges in the Real World” at OSU in Spring 2025. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: What I Learned Serving as an AI Expert in the U.S. Congress
by Abou Mrad, Christian 21 Oct '24

21 Oct '24

Dear all, Our next AI seminar is scheduled for October 25th (Friday). Talk details: AI Seminar: What I Learned Serving as an AI Expert in the U.S. Congress Speaker: Kiri Wagstaff, AAAI Fellow Time: 2:00 PM, October 25 Seminar Location: KEC 1001 Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: What is Congress doing about artificial intelligence? I will share what I learned during a one-year position inside a U.S. Senate office as an AI expert through the AAAS Science and Technology Policy Fellowship program. There is a high demand for technical expertise within Congress, especially for AI. More than 300 AI-related bills have been introduced in the current congressional session; we’ll look at the key AI topics getting attention. I’ll describe how I developed a consumer AI literacy bill and then worked for months with a talented team to achieve the bill’s introduction in the Senate in July. I’ll also suggest ways that you can contribute your expertise and make a difference locally and nationwide. Speaker Bio: Kiri Wagstaff is a AAAI Fellow with a focus on deployed machine learning systems that help us explore, understand, and learn about the universe. She recently returned to Corvallis from Washington, D.C., after serving as an artificial intelligence expert in the U.S. Senate for a year. She previously served as a principal researcher in machine learning at the NASA Jet Propulsion Laboratory and an associate research professor and senior instructor at Oregon State University. She earned her Ph.D. in Computer Science from Cornell University, followed by an M.S. in Geological Sciences (University of Southern California) and an MLIS in Library and Information Science (San Jose State University). She received the Lew Allen Award for Excellence in Research and two NASA Exceptional Technology Achievement Medals. She serves on the AAAI U.S. Policy Committee and the OSU AI Program Executive Committee. She will teach “Machine Learning Challenges in the Real World” at OSU in Spring 2025. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: Illuminating the Future of Lithography: AI-Powered Simulation and Optimization
by Abou Mrad, Christian 17 Oct '24

17 Oct '24

Dear all, Reminder that our next AI seminar is scheduled for tomorrow , October 18th (Friday). Talk details: AI Seminar: Illuminating the Future of Lithography: AI-Powered Simulation and Optimization Speaker: Dr. Haoyu Yang, Senior Research Scientist, NVIDIA Research Time: 2:00 PM, October 18 Seminar Location: KEC 1001 Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: Lithography, the process of transferring chip designs onto silicon wafers, is a critical stage in semiconductor manufacturing. Computational lithography models the lithography system's behavior, focusing on resolution enhancement in response to the aggressive scaling dictated by Moore’s Law. This field encompasses two core challenges: system modeling and photomask optimization, both of which demand high-quality results and face immense computational overhead in terms of time and memory. In this talk, we will explore the key challenges in modern computational lithography and how AI is reshaping its landscape. Topics include: 1) AI-accelerated lithography simulations, 2) AI-assisted inverse design, 3) LLM-powered agents for lithography recipe development, and 4) future directions in AI semiconductor manufacturing and research. Speaker Bio: Haoyu Yang is a Senior Research Scientist at NVIDIA Research, specializing in AI and large language models (LLM) for Electronic Design Automation (EDA), GPU-accelerated EDA, AI-driven MultiPhysics simulation, and AI applications in semiconductor manufacturing. Before joining NVIDIA, he was a Postdoctoral Fellow in the Department of Computer Science and Engineering at the Chinese University of Hong Kong, where he also earned his Ph.D. His accolades include the Best Paper Award from IEEE Transactions on Semiconductor Manufacturing (TSM) in 2022 and a Best Paper Nomination at IEEE ASPDAC in 2019. He was also the sole recipient of the prestigious 2019 Nick Cobb Memorial Scholarship, awarded by SPIE & Mentor Graphics for his groundbreaking work in AI for lithography. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: Illuminating the Future of Lithography: AI-Powered Simulation and Optimization
by Abou Mrad, Christian 14 Oct '24

14 Oct '24

Dear all, Our next AI seminar is scheduled for October 18th (Friday). Talk details: AI Seminar: Illuminating the Future of Lithography: AI-Powered Simulation and Optimization Speaker: Dr. Haoyu Yang, Senior Research Scientist, NVIDIA Research Time: 2:00 PM, October 18 Seminar Location: KEC 1001 Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: Lithography, the process of transferring chip designs onto silicon wafers, is a critical stage in semiconductor manufacturing. Computational lithography models the lithography system's behavior, focusing on resolution enhancement in response to the aggressive scaling dictated by Moore’s Law. This field encompasses two core challenges: system modeling and photomask optimization, both of which demand high-quality results and face immense computational overhead in terms of time and memory. In this talk, we will explore the key challenges in modern computational lithography and how AI is reshaping its landscape. Topics include: 1) AI-accelerated lithography simulations, 2) AI-assisted inverse design, 3) LLM-powered agents for lithography recipe development, and 4) future directions in AI semiconductor manufacturing and research. Speaker Bio: Haoyu Yang is a Senior Research Scientist at NVIDIA Research, specializing in AI and large language models (LLM) for Electronic Design Automation (EDA), GPU-accelerated EDA, AI-driven MultiPhysics simulation, and AI applications in semiconductor manufacturing. Before joining NVIDIA, he was a Postdoctoral Fellow in the Department of Computer Science and Engineering at the Chinese University of Hong Kong, where he also earned his Ph.D. His accolades include the Best Paper Award from IEEE Transactions on Semiconductor Manufacturing (TSM) in 2022 and a Best Paper Nomination at IEEE ASPDAC in 2019. He was also the sole recipient of the prestigious 2019 Nick Cobb Memorial Scholarship, awarded by SPIE & Mentor Graphics for his groundbreaking work in AI for lithography. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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AI Seminar: Change Point Detection with Localization
by Abou Mrad, Christian 10 Oct '24

10 Oct '24

Dear all, Reminder that our next AI seminar is scheduled for tomorrow, October 11th (Friday). Talk details: AI Seminar: Change Point Detection with Localization Speaker: Prof. Sharmodeep Bhattacharyya, Associate Professor in the Department of Statistics and AI Degree Program, EECS Department, Oregon State University Time: 2:00 PM, October 11 Seminar Location: KEC 1001 Zoom link: https://oregonstate.zoom.us/s/98357211915<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Foregonsta…> Talk Abstract: Changepoint detection methods for networks and precision matrices, fall into two extremes. At one extreme, global changepoint detection methods identify when matrices differ in terms of overall properties, such as their L-infinity norms. This global approach is very coarse-grained in terms of dimensions and may not identify the locations of the changes if they take place on a subset of the dimensions. On the other extreme, local changepoint detection methods inspect individual pairwise components of a precision or adjacency matrix. These methods can identify changes in individual dimensions, but they are generally computationally expensive in higher dimensions, require careful handling of a large number of hypothesis tests simultaneously, and do not identify subsets in which a change takes place. Our work aims to fill a gap in the middle of these two extremes by efficiently detecting and localizing changepoints caused by changes to a subset of dimensions. Our approach for networks is based on CUSUM statistic for rooted subgraphs. Our approach for precision matrices, which we refer to as LD-CPD (Linear Decomposition Changepoint Detection), uses a linear decomposition of the precision matrix and tests for changes to the components of this decomposition, where these components correspond to a group of dimensions. We benchmark our algorithm on several simulation studies with changes involving groups of dimensions, as well as on real-world sensor networks and stock market data. We show that our approach is effective at identifying changepoints in both regimes in a computationally efficient manner while providing a convenient interpretation of the changes through this linear framework. Speaker Bio: Sharmodeep Bhattacharyya is an Associate Professor in the Department of Statistics and AI Degree Program, EECS Department at Oregon State University. His research interests lie in several fields of statistics, including statistical inference of networks, high-dimensional statistical inference, clustering, semiparametric inference, and hypothesis testing. He is also interested in the application of statistical methods in neuroscience, epidemiology, public health, and public policy. Before joining Oregon State University, Dr. Bhattacharyya completed his Ph.D. in Statistics at the University of California, Berkeley, under the supervision of Prof. Peter J. Bickel. Before that, he completed a B.Stat and M.Stat at the Indian Statistical Institute in Kolkata. For future AI seminars, please visit: https://engineering.oregonstate.edu/EECS/research/AI-seminars<https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fengineeri…>. Best, Christian Abou Mrad Graduate Student Oregon State University

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