People of ACM - Bulletin Archive

Maria Soledad Pera is an Associate Professor in the Web Information Systems group at the Delft University of Technology. Her primary research interests include information retrieval and recommender systems as well as information access and web search. Pera was recently named (with George Neville-Neil) Co-Chair of the newly instituted ACM Globalization Board. The Board’s mission includes expanding ACM’s global footprint and supporting all computing professionals irrespective of their geographic location. In her interview, she discusses information retrieval, child-aware search environments, her role as Co-Chair of the ACM Globalization Board, and more.

Julia Gersey is a PhD student in Electrical and Computer Engineering at the University of Michigan, advised by Pei Zhang. Her research lies at the intersection of embedded & mobile computing, sensor networks and applied machine learning. Recently she has been building mobile sensing systems for real-world deployments. Gersey is the Editor in Chief of ACM XRDS, ACM’s magazine for students. In her interview, she discusses her interest in building mobile sensing systems, analyzing changing city conditions to better serve communities, her vision for ACM XRDS magazine, and more.

Sorelle Friedler is the Shibulal Family Professor of Computer Science at Haverford College and a Nonresident Senior Fellow at the Brookings Institution. The core focus of her work is the fairness, accountability and transparency of machine learning. During her tenure as Assistant Director for Data and Democracy in the White Office of Science and Technology Policy, she co-authored the Blueprint for an AI Bill of Rights. In her interview, she discusses the fairness and transparency of AI algorithms, abstraction as a basic building block of computer science, how emerging AI technologies present new challenges to AI responsibility efforts, and more.

Worawan Diaz Carballo (Marungsith) is an Assistant Professor at Thammasat University (Thailand). Her research focuses on HPC systems, AI workload efficiency, and hybrid HPC/AI/cloud integration for education and innovation. Diaz Carballo is also the principal investigator of the HPC Ignite Initiative, a capacity-building program supported by Thailand’s NRCT and ThaiSC. In her interview, she discusses the challenges of effective face detection, the ACM HPC Summer School in Barcelona, developing regions adopting AI-accelerated HPC safely, and more.

Norman P. Jouppi is a Vice President and Engineering Fellow at Google. He joined Google to develop ML accelerators, and is the tech lead for Google’s Tensor Processing Units (TPUs). Jouppi has served the ACM in many capacities, including as the Chair of SIGARCH and as a member of the ACM Council. He is an ACM Fellow and received the ACM-IEEE CS Eckert Mauchly Award for pioneering contributions to the design and analysis of high-performance processors and memory systems. In his interview, he discusses the development of the RISC and MIPS microprocessors, how his new buffers improved the memory of computer systems, TPUs vs. GPUs, his work in telepresence, and more.

Meeyoung (Mia) Cha is a Scientific Director with the Max Planck Institute for Security and Privacy (MPI-SP), as well as a Professor at the Korea Advanced Institute of Science and Technology (KAIST). At MPI-SP, she leads the Data Science for Humanity Group. Cha was named an ACM Distinguished Member for her contributions to computational social science research on misinformation, fraud detection, and poverty mapping. In her interview, she discusses integrating classical computing methods into the social sciences, the Data Science for Humanity Group, challenges in combating fake news, and more.

Guoliang Xing is a Professor and Director of the AIoT Lab at the Chinese University of Hong Kong (CUHK). His research spans embedded AI, AI for health, autonomous driving, and cyber-physical systems. Xing serves as an Associate Editor for ACM Transactions on Computing for Healthcare and ACM Transactions on Sensor Networks, and has served as general or program co-chair for multiple ACM conferences. In his interview, he discusses key hurdles we need to overcome for automated vehicles to become pervasive, developing digital biomarkers for Alzheimer’s disease, is integrating large language models (LLMs) into real-world sensing applications, and more.

Shota Yamanaka is a Senior Chief Researcher at LY Corporation Research​ (formerly Yahoo Japan Corporation). He founded LY Corporation Research’s Human-Computer Interaction team and still serves as its director. Yamanaka’s research interests include human-computer interaction, graphical user interfaces, and human-performance modeling. This year, Yamanaka received the IPSJ/ACM Award for Early Career Contributions to Global Research. In his interview, Yamanaka discusses LY Corporation Research’s Human-Computer Interaction team, how modeling human motor performance can improve graphical interfaces, air gestures as an alternative to touch screens, and more.

Richa Singh is a Professor of Computer Science & Engineering at IIT Jodhpur. She has published over 400 peer‑reviewed papers in areas including biometrics, pattern recognition, medical image analysis, and responsible AI. Her group’s work has been used during several significant events, including technology for injured‑face recognition during the 2023 Balasore train tragedy, and deepfake verification support for Indian newsrooms during the 2024 general elections. In her interview, Singh discusses the challenges and opportunities of a career in biometrics and pattern recognition, developing fusion algorithms, the importance of AILET, and more.

Brad A. Myers is a Professor and Director of the Human-Computer Interaction Institute at Carnegie Mellon University. He is also the principal investigator of CMU’s Natural Programming project. Myers has received the ACM SIGCHI Lifetime Achievement Award and the Alan J. Perlis Award for Imagination in Computer Science. He is also the co-recipient of the 2025 Charles Babbage Institute’s Human Computer Interaction History Prize for his book Pick, Click, Flick! The Story of Interaction Techniques. In his interview, he discusses the formation of HCII at Carnegie Mellon, barriers to the envisioned future of AI, why low-level details matter, and more.

Brian Harvey is Teaching Professor Emeritus at the University of California at Berkeley. His interests include computer science education, curricula, programming languages, and visual languages. Harvey is the author of Computer Science Logo Style and Simply Scheme (with Matthew Wright), an introduction to computer programming for non-majors. With his Berkeley colleague Dan Garcia, Harvey developed the Beauty and Joy of Computing (BJC) curriculum. In his interview, he discusses the inspiration behind his computer center at Lincoln-Sudbury Regional High School, the success of the Beauty and Joy of Computing curriculum, why grades are “evil,” and more

Carla Fabiana Chiasserini is a Professor at Politecnico di Torino. Her research interests include algorithm design and analysis, machine learning for networking, wireless networks, and power management for networked devices. Chiasserini was recently named an ACM Fellow for contributions to the design of high-performance mobile networks and services. In her interview, she discusses how computer networks benefit from machine learning, medical applications of the O-RAN project, full exploitation of connected car data, and more.

Ashish Sharma is a Senior Applied Scientist at the Microsoft Office of Applied Research after earning his PhD at the University of Washington. Sharma recently received the ACM Doctoral Dissertation Award for his dissertation ‘Human-AI Collaboration to Support Mental Health and Well Being” in which he developed fundamental advances in natural language processing to positively impact the mental health of large groups of people. In his interview, he discusses what drew him to the field of human-AI collaboration, how his technology works with differing mental health situations, its potential for long-term impact, and more.

Sewon Min is an Assistant Professor at the University of California, Berkeley and a research scientist at the Allen Institute for AI. At UC Berkeley, she is part of the Berkeley Artificial Intelligence Research Lab (BAIR) as well as the Berkeley NLP Group. Min recently received an Honorable Mention for the ACM Doctoral Dissertation Award for her dissertation “Rethinking Data Use and Large Language Models.”  In her interview, she discusses the limitations of large language model learning, LLMs and private information, designing models that align with data owner interests, and more.

Peter Stone is a Professor at The University of Texas at Austin, where he is the founder and director of the Learning Agents Research Group (LARG). He is also the Chief Scientist of Sony AI. He is an ACM Fellow and recently received the ACM-AAAI Allen Newell Award for significant contributions to the theory and practice of artificial intelligence. In his interview, he discusses utilizing intelligent agents at intersections, participating in the international RoboCup competitions, novel applications of AI in the future, and more.

Derek Dreyer is a Scientific Director at the Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken, Germany. At MPI-SWS, he leads the Foundations of Programming Group. His broad range of interests include type systems, semantics of programming languages, verification of concurrent programs, and interactive theorem proving. In his interview, he discusses the RustBelt project and its open-source development model, Iris separation logic, his lifelong appreciation of classical music, and more.

Since retiring from the National Science Foundation in 2011, Carl E. Landwehr has served in many positions, most recently as Visiting Professor at the University of Michigan, Ann Arbor, and lead research scientist at the Cyber Security and Privacy Research Institute, George Washington University. In his interview, he discusses developments in computer security during his career, trustworthy computing, teaching undergraduates to make good decisions in cybersecurity and public policy, and more.