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Aleksandra Faust
Serbian-American AI researcher and technology executive From Wikipedia, the free encyclopedia
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Aleksandra Faust is a Serbian-American computer scientist, AI researcher, and technology executive. She is the Chief AI Officer at Genesis Molecular AI, having previously served as a Research Director at Google DeepMind,[1] and a Principal Investigator at Sandia National Laboratories.[2]
Faust is recognized for establishing principles of AI-driven scalable autonomy, particularly in the field of Automated Reinforcement Learning (AutoRL).[3] Her research focuses on treating the entire system design pipeline as a learnable, sequential decision-making problem—an approach she has applied to scalable autonomy in robotics, generative AI, and drug discovery.[4] Contributions include the "Pearl" biomolecular foundation model,[5] the self-improvement training methods used in Google's Gemini models,[6] and the "Levels of AGI" framework.[7] In 2020, she received the IEEE Early Career Award in Robotics and Automation.[8]
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Education
Faust received her Bachelor of Science in Mathematics and Computer Science from the University of Belgrade.[2] She earned a Master of Science in Computer Science from the University of Illinois at Urbana-Champaign in 2004.[2] In 2014, Faust completed her Ph.D. in Computer Science at the University of New Mexico under the supervision of Lydia Tapia.[9] Her dissertation, "Reinforcement Learning and Planning for Preference Balancing Tasks," won the Tom L. Popejoy Dissertation Prize, the university's highest dissertation honor.[10]
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Career
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Perspective
Faust was a Senior R&D Engineer at Sandia National Laboratories (2006–2015).[2] She subsequently joined Waymo (Google's self-driving car project) in 2015, focusing on machine learning for motion planning.[11]
In 2017, Faust joined Google Brain,[12] eventually rising to Director of Research at Google DeepMind, where she led scalable autonomy and reinforcement learning research.[1]
In June 2025, Faust was appointed Chief AI Officer of Genesis Molecular AI (formerly Genesis Therapeutics).[13] In October 2025, she and her team released the technical report for the "Pearl" foundation model for atomic placement in biomolecular structures, reportedly the first model that outperforms AlphaFold 3.[5]
Automated Reinforcement Learning (AutoRL)
Faust co-authored the paper that founded Automated Reinforcement Learning (AutoRL), a term her research is credited with coining.[4] AutoRL automates the design of the learning agents themselves. She co-authored the field's first survey,[4] and served as the Program Chair for the AutoML conference in 2023.[14]
Sustainable Training Methodologies
A central tenet of Faust's work is the reliance on accessible, imperfect data to overcome scarcity in high-stakes fields.[15] Her research in robotics, web agents, and drug discovery utilizes synthetic, simulated, and noisy data to propel progress where expert demonstrations are rare or nonexistent.[12][16][5]
Robotics and Motion Planning
In robotics, Faust bridges the gap between sensing, motion planning, and control using machine learning.[12] She created "PRM-RL," a method that combines sampling-based planning with reinforcement learning to enable long-range autonomous navigation,[17] winning the Best Paper in Service Robotics award at ICRA 2018.[18]
Faust was also an early advocate for generalist robot models capable of navigating diverse physical spaces without retraining.[19] She established the theoretical foundations for this generalization[20] as well as self-supervised methods for a learning-based robotics stack without computationally expensive methods.[12] She later expanded this approach to hardware-software co-design, characterizing dependencies between sensors, compute, and machine learning models. This interdisciplinary work earned the Best of IEEE Computer Architecture Letters runner-up award (2020)[21] and an IEEE Micro Top Picks Honorable Mention (2023).[22] Her contributions to the field were recognized with the IEEE Early Career Award in Robotics and Automation in 2020.[8]
Generative AI and Autonomous Agents
Faust led the development of Web Agents, recognized as the first fully autonomous, open-ended task agents on the web.[23] This technology was integrated into Google Assistant.[citation needed] To measure industry progress, Faust co-authored "Levels of AGI," a framework operationalizing the path to artificial general intelligence (AGI).[7] The framework has been discussed in media outlets including Bloomberg News,[24] The Economist,[25] and Forbes.[26]
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Awards and honors
- Fellow of the IEEE, 2026 "for contributions to technical leadership in scalable learning-based autonomy and foundation models"[27]
- IEEE Micro Top Picks Honorable Mention (2023)[22]
- 50 Women in Robotics you need to know about, Women in Robotics (2023)[28]
- Best Paper of IEEE Computer Architecture Letters runner-up (2020)[21]
- IEEE Early Career Award in Robotics and Automation (2020)[8]
- ICRA Best Paper in Service Robotics (2018)[18]
- Distinguished Alumna, University of New Mexico School of Engineering (2018)[29]
- Tom L. Popejoy Dissertation Prize Winner, University of New Mexico (2015)[10]
Speaking engagements
Faust is a frequent speaker at international forums, including a 2025 keynote at the IAEA's Emerging Technologies Workshop[30] and a plenary panel at World Summit AI.[31] She has served as a panelist for the National Academy of Sciences[32] and addressed 15,000 attendees as a plenary speaker at the Society of Women Engineers WE17 conference.[33] Her academic speaking engagements include keynotes at premier robotics conferences such as IROS[34] and CoRL.
References
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