Featured ACM Member: Shota Yamanaka
Shota Yamanaka is a Senior Chief Researcher at LY Research, LY Corporation (formerly Yahoo Japan Corporation). He founded LY 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. He was recognised for theoretical and empirical modeling for understanding human motor behaviours in graphical user interfaces. His papers have been presented at numerous conferences including CHI, UIST, UbiComp, ISS, DIS, as well as the IPSJ Interaction Symposium.
In his interview, Yamanaka discusses LY 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. Read Yamanaka’s interview here.
Featured ACM Member: Richa Singh
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.
Singh has been recognised with the NASSCOM AI Gamechangers Award and Facebook’s Ethics in AI (India) Research Award. She is also a Fellow of IEEE, IAPR, and INAE and an ACM Distinguished Member.
Her volunteer contributions to the community include serving as Founding Co Editor in Chief of ACM AI Letters (AILET), Associate Editor in Chief of Pattern Recognition, as well as a Program Co Chair of CVPR 2022. Colleagues also value her commitment to mentoring numerous graduate students and early career researchers.
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. Read Singh’s interview here.
ACM TechTalk: Mariia Mykhailova
View the recent ACM Techtalk, In “Quantum Programming in Depth: Bringing Software Engineering Practices to QC” from Mariia Mykhailova, Principal Quantum Software Developer at PsiQuantum. She was previously a quantum software engineer at Microsoft Quantum, joining the team in early 2017, just in time to participate in the development of the first version of the quantum programming language that became Q#.
Quantum computing is rapidly evolving from an area of theoretical research to that of practical development and experimentation. Implementing quantum algorithms as code improves our ability to reason about them compared to purely theoretical analysis.
In this talk, Mykhailova introduces quantum software development workflow, with particular focus on validating the correctness of quantum programs and estimating their performance on future fault-tolerant quantum computers.
ACM ByteCast: Torsten Hoefler
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 honours include the Max Planck-Humboldt Medal, an award for outstanding mid-career scientists; the IEEE CS Sidney Fernbach Award, which recognises outstanding contributions in the application of high-performance computers; and the ACM Gordon Bell Prize, which recognises 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 his 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, the intersection of HPC and recent innovations in AI, his key contributions in popularising 3D parallelism for training AI models, and offers advice to young researchers on balancing academic learning with industry exposure.
ACM ByteCast: Maja Matarić
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). Also Principal Scientist at Google DeepMind, she is a roboticist and AI researcher known for her work in human-robot interaction for socially assistive robotics, a field she pioneered.
Here, Matarić talks about moving to the US from Belgrade, Serbia and how her early interest in both computer and behavioural 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, why Generative AI is conducive to creating socially engaging robots. She also touches on the issues of privacy, bias, ethics and personalisation in the context of assistive robotics and more.