معرفی
Prof. Andrey Ustyuzhanin is an Adjunct Professor of Computer Science at Constructor University's School of Computer Science & Engineering and a Visiting Research Professor at the National University of Singapore (NUS), affiliated with the Institute for Future Intelligent Machines (IFIM). He holds a PhD in Computer Science from the Institute of System Programming (Russian Academy of Sciences) and advanced degrees from Moscow Institute of Physics and Technology (MIPT). His research focuses on developing machine learning methods to address complex scientific challenges in particle physics, materials science, and data-driven discovery. He has contributed to projects like the LHCb experiment at CERN, optimizing online triggers and BDT-based processing, and has pioneered initiatives like the Tracking Machine Learning Challenge and the Code4ML dataset. His work bridges AI and fundamental science, emphasizing interdisciplinary applications. He is also the Director of AI/ML Research at Acronis and a co-organizer of international summer schools in machine learning for particle physics.
Education
- PhD in Computer Science, Institute of System Programming (RAS), 2007
- M.Sc. in Applied Mathematics & Physics (Autonomous Control Systems), MIPT, 1994–2000
- M.Sc. in Innovative Management, MIPT, 1998–1999
- B.Sc. in Applied Mathematics, MIPT, 1994–1998
- Mathematics & Physics, Moscow Chemical Lyceum, 1991–1994
Research Interests
Prof. Ustyuzhanin specializes in machine learning for scientific discovery, including particle physics (LHCb experiment), materials science (defect analysis in 2D materials), and AI-driven experimental optimization. His work also explores symbolic expression generation, code semantics classification (Code4ML), and cybersecurity frameworks like EAGLEEYE for malicious event detection. He advocates for reproducible science and end-to-end optimization of experimental designs using differentiable programming.
Key Projects & Contributions
- Co-developed the Tracking Machine Learning Challenge to advance high-throughput physics analysis
- Co-created the Code4ML dataset for annotated machine learning code
- Designed algorithms for LHCb’s online triggers and scintillator tracking systems
- Co-founded the annual summer schools on ML in particle physics
Labs & Collaborations
- Director of AI/ML Research at Acronis
- Head of the LAMBDA Lab at HSE University
- PI at IFIM, NUS
- Collaborator on CERN-Yandex research programs
