We are pleased to announce the third annual MLCommons Rising Stars cohort of 38 junior researchers from 25 institutions globally! These promising researchers, drawn from over 150 applicants, have demonstrated excellence in Machine Learning (ML) and Systems research and stand out for their current and future contributions and potential. This year’s program has been expanded to include data systems research as an area of interest.
The MLCommons Rising Stars program provides a platform for talented young researchers working at the intersection of ML and systems to build connections with a vibrant research community, engage with industry and academic experts, and develop their skills. The program continues to promote diversity in the research community by seeking researchers from historically underrepresented backgrounds. We are pleased to welcome nine international Rising Stars to this year’s cohort.
As part of our commitment to fostering the growth of our Rising Stars, we organized the Rising Stars workshop at the Meta Headquarters in Menlo Park, CA, in May, where the cohort showcased their work, explored research opportunities, gained new skill sets via career building sessions, and had the opportunity to network with researchers across academia and industry.
“ML is a fast-growing field with rapid adoption across all industries, and we believe that the biggest breakthroughs are yet to come. By nurturing and supporting the next generation of researchers, both domestically and globally, we aim to foster an inclusive environment where these individuals can make groundbreaking contributions that will shape the future of ML and systems research. The Rising Stars program is our investment in the future, and we are excited to see the innovative ideas and solutions that these talented researchers will bring to the table,” said Vijay Janapa Reddi, MLCommons VP and Research Chair and steering committee member of the Rising Stars program.
This year’s program marked a pivotal step toward strengthening the community at the intersection of ML and systems, especially by connecting early-career researchers who share common challenges and goals. The shared experiences, discussions on generative AI, and connections forged at the workshop are expected to fuel new collaborations and research directions. As we reflect on this year’s success, we are more committed than ever to growing a supportive, interdisciplinary, and inclusive ecosystem for future Rising Stars.
As part of the two-day Rising Stars workshop held at Meta Headquarters in Menlo Park, our 2025 cohort engaged in dynamic sessions with leading researchers and alumni. One of the highlights was the Alumni Panel, moderated by Abdulrahman Mahmoud (MBZUAI), featuring Rising Stars ’23 alumni: Sercan Aygun (University of Louisiana at Lafayette), Muhammad Husnain Mubarik (AMD), Francisco Romero (Plix & Georgia Tech), and Zishen Wan (Georgia Tech). The panel shared valuable insights into their career journeys, academic-industry transitions, and lessons learned since completing the program. Attendees had the opportunity to ask questions about career growth, building a research identity, and balancing long-term research goals.
The workshops keynotes and invited talks came from distinguished leaders in ML and systems, including Vikas Chandra (Meta) on “Generative AI for Immersive Worlds”, Dan Fu (Stanford University) on “Kittens and Chipmunks: More Efficient ML Algorithms with Kernels”, Joel Emer (MIT) in a candid AMA session, Vijay Janapa Reddi (Harvard University) on “Architecture 2.0”, and Jason Cong (UCLA) on “Efficient LLMs: From Model Innovation to Customized Acceleration”. In addition, the AR/VR Panel, moderated by Muhammad Husnain Mubarik, brought together Huichu Liu (Meta) and Hyoukjun Kwon (UC Irvine) for an engaging discussion on immersive technologies. The program also spotlighted MLCommons Research Presentations by David Kanter (MLCommons) and Arun Tejusve Raghunath Rajan (Meta), offering a forward-looking perspective on collaborative benchmarking and infrastructure for ML innovation. This was followed by a moderated Q&A session on ML Systems at Meta, led by Abdulrahman Mahmoud (MBZUAI), with insights from Zachary DeVito (Meta), one of the first contributors to PyTorch, who shared his experiences in API design. Through lightning talks, poster sessions, breakout research discussions, and panels, the event fostered a vibrant environment for exchanging ideas and forging collaborations.
We extend our warmest congratulations to this year’s Rising Stars and express our gratitude to everyone who applied.
We would also like to thank Rising Stars organizers Udit Gupta (Cornell Tech), Abdulrahman Mahmoud (MBZUAI), Sercan Aygun (University of Louisiana at Lafayette) and Muhammad Husnain Mubarik (AMD), Lillian Pentecost (Amherst College), Akanksha Atrey (Nokia Bell Labs) and Vijay Janapa Reddi (Harvard University) for all their efforts in putting together the program and selecting an impressive cohort of recipients.
Finally, we would also like to extend our appreciation to Kelly Berschauer (MLCommons), Vikas Chandra (Meta), Petrina Mitchell (META), and David Scott (META), for their support in organizing the program and workshop.