ACM ByteCast

In this episode of ACM ByteCast, Bruke Kifle hosts ACM Fellow and ACM Distinguished Service Award recipient Jennifer Chayes, Dean of the College of Computing, Data Science, and Society at UC Berkeley. Before joining Berkeley, she co-founded the Theory Group at Microsoft Research Redmond and later founded and led three interdisciplinary labs: Microsoft Research New England, New York City, and Montreal. Her research areas include phase transitions in CS, structural and dynamical properties of networks including graph algorithms, and applications of ML. Jennifer is one of the inventors of the field of graphons, widely used for the ML of large-scale networks. Her recent work includes generative AI and ML theory in areas like cancer, immunotherapy, climate change, and ethical decision making, with more than 150 scientific papers authored and 30 patents she co-invented. Her honors and recognitions include the Anita Borg Institute Women of Vision Leadership Award, SIAM’s John von Neumann Lecture Award (the highest honor bestowed by SIAM), and election to the American Academy of Arts and Sciences and the National Academy of Sciences. She serves on numerous boards and advisory committees and has served on the ACM A.M. Turing Award Selection Committee. Jennifer shares her early experience as the child of Iranian immigrants, dropping out of high school and learning to embrace risk. She describes her journey from being a pre-med biology major to a PhD in mathematical physics, and how her love of theory and an interest in interdisciplinary work led her to start a Theory Group at Microsoft Research. She also relates how her later interest in economics and game theory led to the founding of Microsoft Research New England, and highlights some of her work there. She and Bruke talk about the challenges she has navigated throughout her career, and how that has influenced her approach to interdisciplinary research. Jennifer also shares her vision and goals for the College of Computing, Data Science, and Society at UC Berkeley. Finally, she opines on the skills needed for future leaders in computing, some of the urgent problems of our time, and offers some advice to young computing professionals.

Roger Dannenberg, Professor Emeritus at Carnegie Mellon University, is a trailblazer in computer music and co-creator of Audacity. He explores the fusion of sound, mathematics, and AI, discussing how technology has transformed music creation. Roger highlights the dual role of AI as both a challenge and an opportunity for musicians. He also shares his passion for making music accessible through open-source tools and emphasizes the importance of pursuing one's passions in tech fields. Tune in for insights on the future of music and technology!

Xin Luna Dong, Principal Scientist at Meta Reality Labs and a renowned expert on knowledge graphs, shares the spark behind her early fascination with computing in China. She dives into the structure and significance of knowledge graphs, detailing their roles at Google and Amazon. The conversation reveals how advancements in ML and AI are transforming data integration methods. Luna also discusses Retrieval-Augmented Generation (RAG) and its potential to enhance personalized experiences in information retrieval, alongside valuable career insights for aspiring data professionals.

Nashlie Sephus, Principal Tech Evangelist at Amazon AI, is a trailblazer in AI fairness and bias mitigation. She dives into her early love for math and music, which informed her doctoral work in digital signal processing. Nashlie discusses her role in developing visual search technology that revolutionized part identification at Amazon. She also shares insights on the importance of responsible AI, community empowerment through her nonprofit Bean Path, and the necessity for diversity within tech to drive innovation.

Wen-Mei Hwu, a Senior Distinguished Research Scientist at NVIDIA and Professor Emeritus at the University of Illinois, shares insights into processor architecture evolution. He discusses the impact of Moore’s Law and Dennard Scaling on efficiency in chip design. The conversation delves into the early days of specialized processors, the rise of GPUs, and the complexities of full-stack development. Wen-Mei also speculates on future innovations in computing and his vision for technology aimed at enhancing human relationships.

In this episode of ACM ByteCast, Harald Störrle hosts ACM Fellow and Software System Award recipient Xavier Leroy, professor at Collège de France and member of the Académie des Sciences. Best known for his role as a primary developer of the OCaml programming language, Xavier is an internationally recognized expert on functional programming languages and compilers, focusing on their reliability and security, and has a strong interest in formal methods, formal proofs, and certified compilation. He is the lead developer of CompCert, the first industrial-strength optimizing compiler with a mechanically checked proof of correctness, with applications to real-world settings as critical as Airbus aircraft. In the past, he was a senior scientist at INRIA, a leading French research institute in computer science, where he is currently a member of the Cambium research team. His honors and recognitions also include the ACM SIGPLAN Programming Languages Achievement Award and the Milner Award from the Royal Society. Xavier shares the evolution of Ocaml, which grew out of Caml, an early ML (Meta Language) variant, and how it came to be adopted by Jane Street Capital for its financial applications. He also talks about his interest in formal verification, whose adoption in the software industry is still low due to high costs and the need for mathematical specifications. Harald and Xavier also dive into a discussion of AI tools like Copilot and the current limitations of AI-generated code in software engineering. The conversation also touches on ACM’s efforts to become a more global and diverse organization and opportunities to bridge the gap between academia and industry.

In this episode of ACM ByteCast, Bruke Kifle hosts ACM Fellow Ramón Cáceres, a computer science researcher and software engineer. His areas of focus have included systems and networks, mobile and edge computing, mobility modeling, security, and privacy. Most recently he was at Google, where he built large-scale privacy infrastructure. Previously, Ramón was a researcher at Bell Labs, AT&T Labs, and IBM Research. He also held leadership positions in several startup companies. In addition to being the first ACM Fellow from the Dominican Republic, he is an IEEE Fellow and has served on the board of the CRA Committee on Widening Participation in Computing Research. He holds a PhD in Computer Science from the University of California at Berkeley. Ramón, who took an indirect path to computer science, shares how he started in computer engineering but grew more interested in software, and how his strong background in hardware helped throughout his scientific and engineering career. He identifies some of the most significant challenges facing privacy and security and sheds lights on his work with the Google team that developed Zanzibar, Google's global authorization system supporting services used by billions of people. Ramón looks toward the future of mobile and edge computing in the next 5-10 years and his particular interest in federated machine learning, which brings together AI and mobile and edge computing. In the wide-ranging interview, he also reflects on growing up in the Dominican Republic and later discovering a love for sailing while in Silicon Valley, shares his efforts to bring underrepresented groups into the field of computing, and offers advice for aspiring software engineers.

In this episode of ACM ByteCast, our special guest host Scott Hanselman (of The Hanselminutes Podcast) welcomes ACM Fellow Juan Gilbert, the Andrew Banks Family Preeminence Endowed Professor and Chair of the Computer & Information Science & Engineering Department at the University of Florida where he leads the Computing for Social Good Lab. The lab’s innovations include open-source voting technology to help make elections more secure, accessible, and usable; making voting technologies more transparent; increasing fairness and reducing bias in ML algorithms used in admissions and hiring decisions; and reducing conflicts during traffic stops. Gilbert’s many honors and recognitions include the Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring, the CRA A. Nico Habermann Award, and the National Medal of Technology and Innovation (NMTI). Juan shares with Scott his surprise at being nominated for the NMTI, which he received in 2023 from President Joe Biden for pioneering a universal voting system that makes voting more reliable and accessible for everyone and for increasing diversity in the computer science workforce. He talks about his lab’s mission to change the world by solving real-world problems, and principles such as “barrier-free design” that he and his collaborators applied to his lab’s voting machine technology. They also discuss how his Application Quest (AQ) technology uses AI to help make fairer hiring decisions, and how his students’ Virtual Traffic Stops app helps protect both drivers and law enforcement safe during traffic stops. Juan also explains how he and his lab choose which projects they work on and teases the promise of brain-computer interaction technology.

In this episode of ACM ByteCast, Rashmi Mohan hosts ACM A.M. Turing Award laureate Yoshua Bengio, Professor at the University of Montreal, and Founder and Scientific Director of MILA (Montreal Institute for Learning Algorithms) at the Quebec AI Institute. Yoshua shared the 2018 Turing Award with Geoffrey Hinton and Yann LeCun for their work on deep learning. He is also a published author and the most cited scientist in Computer Science. Previously, he founded Element AI, a Montreal-based artificial intelligence incubator that turns AI research into real-world business applications, acquired by ServiceNow. He currently serves as technical and scientific advisor to Recursion Pharmaceuticals and scientific advisor for Valence Discovery. He is a Fellow of ACM, the Royal Society, the Royal Society of Canada, Officer of the Order of Canada, and recipient of the Killam Prize, Marie-Victorin Quebec Prize, and Princess of Asturias Award. Yoshua also serves on the United Nations Scientific Advisory Board for Independent Advice on Breakthroughs in Science and Technology and as a Canada CIFAR AI Chair.  Yoshua traces his path in computing, from programming games in BASIC as an adolescent to getting interested in the synergy between the human brain and machines as a graduate student. He defines deep learning and talks about knowledge as the relationship between symbols, emphasizing that interdisciplinary collaborations with neuroscientists were key to innovations in DL. He notes his and his colleagues’ surprise in the speed of recent breakthroughs with transformer architecture and large language models and talks at length about about artificial general intelligence (AGI) and the major risks it will present, such as loss of control, misalignment, and nationals security threats. Yoshua stresses that mitigating these will require both scientific and political solutions, offers advice for researchers, and shares what he is most excited about with the future of AI.

In this episode, part of a special collaboration between ACM ByteCast and the American Medical Informatics Association (AMIA)’s For Your Informatics podcast, hosts Sabrina Hsueh and Karmen Williams welcome Francesca Rossi, IBM Fellow and AI Ethics Global Leader, and current President of the Association for the Advancement of Artificial Intelligence (AAAI). Rossi works at the Thomas J. Watson IBM Research Lab in New York. Her research interests focus on artificial intelligence, especially constraint reasoning, preferences, multi-agent systems, computational social choice, and collective decision making. She is also interested in ethical issues in the development and behavior of AI systems. She has published more than 200 scientific articles in journals and conference proceedings and is a fellow of both AAAI and EurAI. Rossi has been the president of the International Joint Conference on AI (IJCAI), an Executive Counselor of AAAI, the Editor-in-Chief of the Journal of AI Research, and serves n the Board of Directors of the Partnership on AI. She has also served as a program co-chair and steering committee member of the AAAI/ACM Conference on AI Ethics and Society (AIES). Francesca shares how experiences with multidisciplinary work in computer science drew her to AI and ethics, and the challenges of synchronizing with people from a variety of different backgrounds at IBM. She also talks about her involvement in the development of AI ethics guidelines in Europe. She walks through some of her concerns around building ethical and responsible AI, such as bias, lack of availability, transparency of AI developers, data privacy, and the accuracy of generated content. Francesca emphasizes the importance of researchers working more closely with policymakers and the important role of conferences such as AIES (a collaboration between AAAI and ACM). She also offers suggestions for those interested in getting more engaged in AI ethics and recommendations for people interested in an AI career path, and advocates for common benchmarks that can help evaluate AI.