WSAI Annual Research Showcase 2025
Explore the forefront of Data Science and AI research with us. Our WSAI Annual Research Showcase promises insightful discussions as researchers present their latest findings, shaping the future of technology
WSAI Summer Internship 2025
Wadhwani School of Data Science & AI (WSAI) Invites student for National Level Internships
RBCDSAI Post-Doctoral Fellow
Work on independent research problems in an interdisciplinary environment under exceptional guidance and with access to high-performance computing infrastructure
RBCDSAI Post Baccalaureate Fellow 2024
Gain hands-on experience, working on cutting edge discoveries, with some of the best minds in the country in Data Science and AI.
Robert Bosch Centre for Data Science and Artificial Intelligence
Inaugurated by Dr. Michael Bolle CTO and Member of the Board of Management, Robert Bosch GmbH In the presence of Prof. Bhaskar Ramamurthi Director, IIT Madras on 6th February 2019.
About us
The Robert Bosch Centre for Data Science and AI (RBCDSAI) aims to leverage data science to give insights to make actionable, reliable and impactful decisions for adoption in engineering, finance and healthcare domains. We are one of the pre-eminent interdisciplinary research centres for Data Science and AI in India with the largest network analytics, deep reinforcement learning, and the most active natural language processing and deep learning groups.
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Publications
Multi-Agent Learning of Efficient Fulfilment and Routing Strategies in E-Commerce
https://arxiv.org/abs/2311.16171
HODLRdD: A new black-box fast algorithm for N-body problems in d-dimensions with guaranteed error bounds: Applications to integral equations and support vector machines
https://doi.org/10.1016/j.jcp.2024.112786
Hybrid self-supervised learning-based architecture for construction progress monitoring
https://doi.org/10.1016/j.autcon.2023.105225
HODLR3D: hierarchical matrices or N-body problems in three dimensions.
https://doi.org/10.1007/s11075-024-01765-4
Event-Triggered Control for Nonlinear Systems With Center Manifolds
https://doi.org/10.1109/TAC.2024.3388912
Efficient and Near-Optimal Noise Generation for Streaming Differential Privacy
https://arxiv.org/pdf/2404.16706
Distributionally Robust Optimization with Bias and Variance Reduction
https://arxiv.org/pdf/2310.13863
Data Driven Monitoring of IOT enabled Water Distribution Networks
https://wdsa-ccwi2022.upv.es/
Cost-Sensitive Trees for Interpretable Reinforcement Learning
https://doi.org/10.1145/3632410.3632443
