ACM ByteCast

Xin Luna Dong - Episode 60

In this episode of ACM ByteCast, Bruke Kifle hosts ACM and IEEE Fellow Xin Luna Dong, Principal Scientist at Meta Reality Labs. She has significantly contributed to the development of knowledge graphs, a tool essential for organizing data into understandable relationships. Prior to joining Meta, Luna spent nearly a decade working on knowledge graphs at Amazon and Google. Before that, she spent another decade working on data integration and cleaning at AT&T Labs. She has been a leader in ML applications, working on intelligent personal assistants, search, recommendation, and personalization systems, including products such as Ray-Ban Meta. Her honors and recognitions include the VLDB Women in Database Research Award and the VLDB Early Career Research Contribution Award.

Luna shares how early experiences growing up in China sparked her interest in computing, and how her PhD experience in data integration lay the groundwork for future work with knowledge graphs. Luna and Bruke dive into the relevance and structure of knowledge graphs, and her work on Google Knowledge Graph and Amazon Product Knowledge Graph. She talks about the progression of data integration methodologies over the past two decades, how the rise of ML and AI has given rise to a new one, and how knowledge graphs can enhance LLMs. She also mentions promising emerging technologies for answer generation and recommender systems such as Retrieval-Augmented Generation (RAG), and her work on the Comprehensive RAG Benchmark (CRAC) and the KDD Cup competition. Luna also shares her passion for making information access effortless, especially for non-technical users such as small business owners, and suggests some solutions.

Nashlie Sephus - Episode 59

In this episode of ACM ByteCast, Rashmi Mohan hosts Nashlie Sephus, Principal Tech Evangelist for Amazon AI focusing on fairness and identifying biases at AWS AI. She formerly led the Amazon Visual Search team in Atlanta, which launched visual search for replacement parts on Amazon Shopping using technology developed at her former start-up Partpic (acquired by Amazon), where she was the CTO. She is also CEO of Bean Path, a nonprofit startup developing the Jackson Tech District, a planned community and business incubator in Jackson, Mississippi. Nashlie earned her PhD from the School of Electrical and Computer Engineering at the Georgia Institute of Technology, where her core research areas were digital signal processing, ML, and computer engineering. She has been featured in The Atlanta Journal-Constitution, CBS kids’ show Mission Unstoppable, Black Enterprise, Ebony, Amazon Science, AWS re:Invent, Afrotech, and Your First Million podcast, among others. She also serves on several start-up and academic advisory boards along with mentoring others and investing in Atlanta-based start-ups. Her honors and recognitions include the BEYA 2024 Black Engineer of the Year Award, Mississippi Top 50, 2019 Ada Lovelace Award, and Georgia Tech Top 40 Under 40.

Nashlie describes her early love for mathematics and music and how these informed her later doctoral research in digital signal processing in music data mining. She shares a personal experience that deeply influenced her work in AI, particularly in responsible AI and fairness, which eventually led her to her current role mitigating bias at Amazon, notably in facial recognition technologies. Nashlie and Rashmi discuss the importance of building diverse teams to practicing responsible AI and building sound products, as well as collaboration with open consortia and organizations such as the Algorithmic Justice League and Black in AI. Nashlie describes the inception and growth of Partpic, an app she started developing while finishing school. She also talks about BeanPath, her nonprofit organization with a mission to bridge the tech gap in Jackson, Mississippi through makerspaces, networking, and community engagement.

Links:
BeanPath

Wen-Mei Hwu - Episode 58

In this episode of ACM ByteCast, our special guest host Scott Hanselman (of The Hanselminutes Podcast) welcomes 2024 ACM-IEEE CS Eckert-Mauchly Award recipient Wen-Mei Hwu, Senior Distinguished Research Scientist at NVIDIA and Professor Emeritus at the University of Illinois, Urbana-Champaign. He was recognized for pioneering and foundational contributions to the design and adoption of multiple generations of processor architectures. His fundamental and pioneering contributions have had a broad impact on three generations of processor architectures: superscalar, VLIW, and throughput-oriented manycore processors (GPUs). Other honors and recognitions include the 1999 ACM Grace Murray Hopper Award, 2006 ISCA Most Influential Paper Award, 2014 MICRO Test-of-Time Award, and 2018 CGO Test-of-Time Award. He is the co-author, with David Kirk, of the popular textbook Programming Massively Parallel Processors.

Wen-Mei discusses the evolution of Moore’s Law and the significance of Dennard Scaling, which allowed for faster, more efficient processors without increasing chip size or power consumption. He explains how his research group’s approach to microarchitecture at the University of California, Berkeley in the 80s led to advancements such as Intel’s P6 processor.  Wen-Mei and Scott discuss the early days of processors and the rise of specialized processors and new computational units. They also share their predictions about the future of computing and advancements that will be required to handle vast data sets in real time, and potential devices that would extend human capabilities.

Xavier Leroy - Episode 57

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.

Ramón Cáceres - Episode 56

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.

Juan Gilbert - Episode 55

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.

Yoshua Bengio - Episode 54

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.

Francesca Rossi - Episode 53

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.

Partha Talukdar - Episode 52

In this episode of ACM ByteCast, Bruke Kifle hosts Partha Talukdar, Senior Staff Research Scientist at Google Research India, where he leads a group focused on natural language processing (NLP), and an Associate Professor at the Indian Institute of Science (IISc) Bangalore. Partha was previously a postdoctoral fellow at Carnegie Mellon University’s Machine Learning Department and received his PhD in computer information science from the University of Pennsylvania. He is broadly interested in natural language processing, machine learning, and making language technologies more inclusive. Partha is a co-author of a book on graphs-based learning and the recipient of several awards, including the ACM India Early Career Researcher Award for combining deep scholarship of NLP, graphical knowledge representation, and machine learning to solve long-standing problems. He is also the founder of Kenome, an enterprise knowledge graph company with the mission to help enterprises make sense of big dark data.

Partha shares how exposure to language processing drew him to languages with limited resources and NLP. He and Bruke discuss the role of language in machine learning and whether current AI systems are merely memorizing and reproducing data or are actually capable of understanding. He also talks about his recent focus on inclusive and equitable language technology development through multilingual-multimodal Large Language Modeling, including Project Bindi. They discuss current limitations in machine learning in a world with more than 7,000 languages, as well as data scarcity and how knowledge graphs can mitigate this issue. Partha also shares his insights on balancing his time and priorities between industry and academia, recent breakthroughs that were impactful, and what he sees as key future achievements for language inclusion.

Rosalind Picard - Episode 51

In this episode of ACM ByteCast, our special guest host Scott Hanselman (of The Hanselminutes Podcast) welcomes ACM Fellow Rosalind Picard, a scientist, inventor, engineer, and faculty member of MIT’s Media Lab, where she is also Founder and Director of the Affective Computing Research Group. She is the author of the book Affective Computing, and has founded several companies in the space of affective computing, including the startups Affectiva and Empatica, Inc. A named inventor on more than 100 patents, Rosalind is a member of the National Academy of Engineering and a Fellow of the National Academy of Inventors. Her contributions include wearable and non-contact sensors, algorithms, and systems for sensing, recognizing, and responding respectfully to human affective information. Her inventions have applications in autism, epilepsy, depression, PTSD, sleep, stress, dementia, autonomic nervous system disorders, human and machine learning, health behavior change, market research, customer service, and human-computer interaction, and are in use by thousands of research teams worldwide as well as in many products and services.

In the episode, Rosalind talks about her work with the Affective Computing Research Group, and clarifies the meaning of “affective” in the context of her research. Scott and Rosalind discuss how her training as an electrical with a background in computer architecture and signal processing drew her to studying emotions and health indicators. They also talk about the importance of data accuracy, the implications of machine learning and language models to her field, and privacy and consent when it comes to reading into people’s emotional states.