ACM ByteCast

• Ilias Diakonikolas - Episode 76

  In this episode of ACM ByteCast, Bruke Kifle hosts 2024 ACM Grace Murray Hopper Award recipient Ilias Diakonikolas, Professor at the University of Wisconsin, Madison, where he researches the algorithmic foundations of machine learning and statistics. Ilias received the prestigious award for developing the first efficient algorithms for high-dimensional statistical tasks that are also robust, meaning they perform well even when the data significantly deviates from ideal modelling assumptions. His other honors and recognitions include a Sloan Fellowship, the NSF CAREER Award, the best paper award at NeurIPS 2019, and the IBM Research Pat Goldberg Best Paper Award. He authored a textbook titled Algorithmic High-Dimensional Robust Statistics. In the interview, Ilias describes his early love of math as a student in Greece, which led him on a research journey in theoretical statistics and algorithms at Columbia University and, later, at UC Berkeley. He defines “robust statistics” and how it aids in detecting “data poisoning.” Ilias and Bruke explore statistical v. computational efficiency, the practical applications of this research in machine learning and trustworthy AI, and future directions in algorithmic design. Ilias also offers valuable advice to future researchers.

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• Cecilia Aragon - Episode 75

  In this episode of ACM ByteCast, Bruke Kifle hosts ACM Distinguished Member Cecilia Aragon, Professor in the Department of Human Centered Design and Engineering and Director of the Human-Centered Data Science Lab at the University of Washington (UW). She is the co-inventor (with Raimund Seidel) of the treap data structure, a binary search tree in which each node has both a key and a priority. She is also known for her work in data-intensive science and visual analytics of very large data sets, for which she received the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2008. Prior to her appointment at UW, she was a computer scientist and data scientist at Lawrence Berkeley National Laboratory and NASA Ames Research Center, and before that, an airshow and test pilot, entrepreneur, and member of the United States Aerobatic Team. She is a co-founder of Latinas in Computing. Cecilia shares her journey into computing, starting as a math major at Caltech with a love of the Lisp programming language, to vital work innovating data structures, visual analytics tools for astronomy (Sunfall), and augmented reality systems for aviation. She highlights the importance of making data science more human-centered and inclusive practices in design. Cecilia discusses her passion for broadening participation in computing for young people, a mission made more personal when she realized she was the first Latina full professor in the College of Engineering at UW. She also talks about Viata, a startup she co-founded with her son, applying visualization research from her lab to help people solve everyday travel planning challenges. We want to hear from you!

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• Torsten Hoefler - Episode 74

  In this episode of ACM ByteCast, Bruke Kifle hosts 2024 ACM Prize in Computing recipient Torsten Hoefler, a Professor of Computer Science at ETH Zurich (the Swiss Federal Institute of Technology), where he serves as Director of the Scalable Parallel Computing Laboratory. He is also the Chief Architect for AI and Machine Learning at the Swiss National Supercomputing Centre (CSCS). His honors include the Max Planck-Humboldt Medal, an award for outstanding mid-career scientists; the IEEE CS Sidney Fernbach Award, which recognizes outstanding contributions in the application of high-performance computers; and the ACM Gordon Bell Prize, which recognizes outstanding achievement in high-performance computing. He is a member of the European Academy of Sciences (Academia Europaea), a Fellow of IEEE, and a Fellow of ACM. In the interview, Torsten reminisces on early interest with multiple computers to solve problems faster and on building large cluster systems in graduate school that were later turned into supercomputers. He also delves into high-performance computing (HPC) and its central role in simulation and modeling across all modern sciences. Bruke and Torsten cover the various requirements that power HPC, the intersection of HPC and recent innovations in AI, and his key contributions in popularizing 3D parallelism for training AI models. Torsten highlights challenges, such as AI’s propensity to cheat, as well as the promise of turning reasoning models into scientific collaborators. He also offers advice to young researchers on balancing academic learning with industry exposure. We want to hear from you!

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• Maja Matarić - Episode 73

  In this episode of ACM ByteCast, Bruke Kifle hosts 2024 ACM Athena Lecturer and ACM Eugene L. Lawler Award recipient Maja Matarić, the Chan Soon-Shiong Chaired and Distinguished Professor of Computer Science, Neuroscience, and Pediatrics at the University of Southern California (USC), and a Principal Scientist at Google DeepMind. Maja is a roboticist and AI researcher known for her work in human-robot interaction for socially assistive robotics, a field she pioneered. She is the founding director of the USC Robotics and Autonomous Systems Center and co-director of the USC Robotics Research Lab. Maja is a member of the American Academy of Arts and Sciences (AMACAD), Fellow of the American Association for the Advancement of Science (AAAS), IEEE, AAAI, and ACM. She received the US Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring (PAESMEM) from President Obama in 2011. She also received the Okawa Foundation, NSF Career, the MIT TR35 Innovation, the IEEE Robotics and Automation Society Early Career, and the Anita Borg Institute Women of Vision Innovation Awards, among others, and is an ACM Distinguished Lecturer. She is featured in the documentary movie Me & Isaac Newton. In the interview, Maja talks about moving to the U.S. from Belgrade, Serbia and how her early interest in both computer and behavioral sciences led her to socially assistive robotics, a field she saw as measurably helpful. She discusses the challenges of social assistance as compared to physical assistance and why progress in the field is slow. Maja explains why Generative AI is conducive to creating socially engaging robots, and touches on the issues of privacy, bias, ethics, and personalization in the context of assistive robotics. She also shares some concerns about the future, such as the dehumanization of AI interactions, and also what she’s looking forward to in the field. We want to hear from you!

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• Alfred Spector - Episode 72

  In this episode of ACM ByteCast, Rashmi Mohan hosts ACM Fellow and 2016 ACM Software System Award recipient Alfred Spector, Professor of Practice in the MIT EECS Department. He was previously CTO of Two Sigma Investments, and before that Vice President of Research and Special Initiatives at Google. Alfred played a key role in developing the Andrew File System (AFS), a breakthrough in distributed computing that later became a commercial venture. He is also known for coining the term “CS + X.” He is a Fellow of the American Academy of Arts and Sciences, Hertz Foundation, and National Academy of Engineering, and recipient of the IEEE Kanai Award for Distributed Computing. Alfred recounts how he initially pursued programming out of personal enjoyment in college. He talks about developing AFS at Carnegie Mellon University, the challenges of turning academic research into commercial products, and the transition from academia to entrepreneurship, sharing some of the lessons learned along the way. Alfred touches on his time at IBM, which acquired his startup Transarc, and the differences between startups and large corporations. He also talks about some of his most notable work as a technical leader at Google, such as Google Translate. Finally, he offers a unique perspective on the rapid evolution of AI and advocates for a more multidisciplinary approach for developing responsible technology. “Google’s hybrid approach to research” paper “More Than Just Algorithms” (ACM Queue article)

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