Program - Data Science: Probabilistic and Optimization Methods II
ORGANIZERS: Jatin Batra (TIFR, Mumbai, India), Vivek Borkar (IIT Bombay, India), Sandeep Juneja (Ashoka University, Haryana, India), Praneeth Netrapalli (Google DeepMind, India) and Devavrat Shah (MIT, Cambridge, USA)
DATE & TIME: 04 August 2025 to 15 August 2025
VENUE: Chandrasekhar Auditorium, ICTS Bengaluru
Probability and Optimization are two of the core areas that underpin much of data science and machine learning. The current workshop, Data Science: Probabilistic and Optimization Methods, will focus on this field with a special focus on shedding light on the core principles that enable both current successes and future breakthroughs in data science and machine learning. The program begins with a bootcamp covering foundational topics in probability, statistics, and optimization, followed by tutorials and research talks highlighting innovative ideas and open challenges. The topics covered will include new theoretical developments in some of the areas likely to be key in upcoming data science research such as reinforcement learning, generative modelling, causal inference and advanced probability and optimization. Through these sessions, participants will see how rigorous theory can inform robust, adaptable systems—and have opportunities to propose fresh lines of inquiry.
A centerpiece of the event is the Infosys-ICTS Turing lectures, delivered by Andrea Montanari (Stanford University), whose work spans several areas including probability, statistical physics, statistics, theoretical computer science, information theory and machine learning. We warmly invite researchers, students, and practitioners from all backgrounds to join this collaborative exploration of data science’s evolving theoretical landscape—and help shape its next wave of discoveries.
Organized with support from Google, Microsoft Research India and Safexpress Centre for Data, Learning and Decision Sciences at Ashoka University.
CONTACT US: [email protected]
PROGRAM LINK: https://www.icts.res.in/program/dspom
Информация по комментариям в разработке