Apple | Frontier AI Organization

Anand Avati is a PhD candidate at the Stanford AI Lab. His homepage says he is the technical lead of the AI-Enabled ACP project deployed at Stanford Hospital, has served as principal instructor of Stanford's CS229 course, and previously was a distinguished engineer in Red Hat's CTO office after joining through the acquisition of Gluster, where he was a founding engineer and lead architect of GlusterFS.

Andrew Tulloch is a researcher at Meta working on superintelligence and a co-founder of Thinking Machines Lab. His public homepage says he previously worked on machine learning systems at Meta, helped train GPT-4o, GPT-4.5, and o3 at OpenAI, and studied mathematics at the University of Sydney and the University of Cambridge.

Ji Lin is a research scientist at OpenAI working on multimodal models, reasoning, and synthetic data. He previously completed his Ph.D. and M.Sc. in EECS at MIT under Song Han, earned a B.Eng. in Electronic Engineering from Tsinghua University, and has interned or worked at Adobe Research, OmniML, and NVIDIA Research.

Sanchit Gandhi is a research scientist at Mistral AI. His public Hugging Face and conference speaker profiles say he previously worked on open-source speech technology at Hugging Face and at Apple, helped popularize OpenAI's Whisper ecosystem, and earned a master's degree at the University of Cambridge.

Sebastian Gehrmann is the head of Responsible AI in the office of the CTO at Bloomberg. His homepage says he previously led Bloomberg's NLP work, earlier researched evaluation of large language models at Google, and earned a PhD from Harvard University. It also highlights research interests in natural language generation, model evaluation, and interpretability.

Ariana Mirian is a senior security researcher at Censys and a PhD student in computer science at UC Berkeley. Her public resume shows earlier AI/ML researcher and data scientist roles at Apple, as well as Stanford degrees in business administration and electrical engineering.

Haotian Zhang is a research scientist on Apple AI/ML's Visual Intelligence team. His homepage says he works on embodied agents that understand the world from 2D and 3D image data as well as natural language, previously interned at Microsoft Research and Azure AI, completed a PhD in electrical and computer engineering at the University of Washington in 2022, and earlier earned master's degrees at Washington and a bachelor's degree at Shanghai Jiao Tong University.

Kartik Sreenivasan is a machine learning researcher whose homepage says he was a final-year PhD student in computer science at the University of Wisconsin-Madison advised by Dimitris Papailiopoulos. The same page says he studies optimization, machine learning, and large-scale distributed settings, earned a B.Tech from the National Institute of Technology Karnataka, worked at Adobe Systems for three years in Bengaluru, and was preparing to join Databricks as a research scientist on the after-training team.

Zhengfeng Lai is an ML Research Scientist at Apple AI/ML. His self-authored CV lists a PhD in Electrical and Computer Engineering from the University of California, Davis, prior Apple internship work, and publications in multimodal and vision-language learning.

Eric P. Xing is president of Mohamed bin Zayed University of Artificial Intelligence and a professor in Carnegie Mellon University's Machine Learning Department, Language Technologies Institute, and Computer Science Department. His public homepage and biography say his work spans machine learning, statistical methodology, large-scale computational systems, large language models, world and agent models, and biology foundation models; he earned a bachelor's degree from Peking University and PhDs from Rutgers University and the University of Alberta.

Marzyeh Ghassemi is the Germeshausen Career Development Professor and an associate professor in electrical engineering and computer science and the Institute for Medical Engineering and Science at MIT, and a CIFAR AI Chair at the Vector Institute. MIT says she joined MIT in July 2021 after serving as an assistant professor at the University of Toronto in computer science and medicine and as a Vector Institute faculty member holding a Canadian CIFAR AI Chair and Canada Research Chair. MIT also lists a PhD in computer science from MIT, an MSc in biomedical engineering from Oxford University, and bachelor's degrees in computer science and electrical engineering from New Mexico State University.

Sanjiv Kumar is a Google Fellow and vice president at Google DeepMind. His homepage says he leads a machine learning team working on foundation models including LLMs and generative AI for Gemini, has also led research in deep retrieval and ranking, and earned a Ph.D. in computer science from Carnegie Mellon University in 2005.

Yacine Jernite leads the ML and Society team at Hugging Face. His personal site says he works on ML systems governance at the intersection of regulatory and technical tools, with a focus on NLP models, data curation, documentation, and governance, and that he completed a Ph.D. in computer science at New York University under David Sontag.

Ke Ye is a fifth-year PhD student in the Language Technologies Institute at Carnegie Mellon University. His homepage says his research spans natural language processing, machine learning, and artificial intelligence, including language models, speech and speech-language models, conversational AI, and reasoning, and notes that before Carnegie Mellon he worked at Apple Intelligence. His OpenReview profile lists Apple foundation-model work alongside earlier roles at Google, Roblox, and Capital One.

Aakanksha Chowdhery is an adjunct professor at Stanford and a researcher at Reflection AI working on agentic LLMs and reinforcement learning for self-improving agents. Her homepage says she previously led work on the 540B PaLM model and Gemini at Google, earlier led interdisciplinary research initiatives at Microsoft Research and Princeton University, and completed a PhD in electrical engineering at Stanford University.

Kanishka Rao is a researcher at Google. Public Google Research and OpenReview profiles connect Kanishka Rao to work in natural language processing, speech processing, robotics, and responsible AI, and list earlier student-research and internship roles at Carnegie Mellon University, Google Research, and Microsoft Research along with a master's degree in language technologies from Carnegie Mellon University.

Nandan Thakur is a PhD student at the University of Waterloo working on information retrieval, vision-language models, inference optimization, and agentic systems. His public homepage says he is currently affiliated with Apple and Stanford and previously worked with researchers at Meta AI and NVIDIA.

Jean-Baptiste Tristan works at Anthropic on alignment. His public website says he previously worked at Amazon AWS on generative AI, at OpenAI, and at Meta, and that he holds bachelor's and master's degrees from Rice University in electrical engineering and computer science plus a PhD in machine learning from UC Berkeley.

Horace He is a researcher at Meta working on PyTorch. His personal homepage says he works on machine learning and compilers, and his Google Scholar profile lists Cornell University with interests in machine learning, compilers, and algorithms.

Karan Singhal leads the Health AI team at OpenAI. His homepage says he works on LLMs for health and AI safety, with goals that include universalizing access to medical expertise, using health as a testbed for safety, and developing better plans for high-stakes AI deployment. The same page says his previous Google work included Med-PaLM and Med-PaLM 2.

Mingxing Tan is a staff research scientist at Google DeepMind in the San Francisco Bay Area. His public homepage says he works on efficient models and reasoning, was the lead author of EfficientNet, EfficientDet, and MobileNetV3, and earned a Ph.D. from the University of Washington.

Da-Cheng Juan is a software engineer at Google Research. His official Google Research profile says he has worked on large-scale semi-supervised learning with Expander and personalized recommendation for computational advertising, received a PhD from Carnegie Mellon University in 2014 before joining Google, and works on machine learning, convex optimization, and data mining.

Sven Gowal is a research scientist at Google DeepMind in Mountain View. His public Google Research profile describes work in robust machine learning, responsible AI, machine perception, and watermarking, and public profile text for that page notes previous postdoctoral work in statistical machine learning at UCL and a Ph.D. from EPFL.

Yingbo Mao is an assistant professor at the University of Hong Kong. His public homepage says he works on computer vision and multimodal large language models, completed his PhD at the Chinese University of Hong Kong in 2024 under Dahua Lin, and previously served as head of multimodal at Together AI and as a research scientist at UCLA.