Diptesh Das

Bio

I am a researcher in the Department of Computational Biology and Medical Sciences at the University of Tokyo. My research focuses on statistical machine learning and its application in high-stakes decision-making problems. After finishing my PhD at the University of Tokyo, I worked as a post-doctoral researcher at the University of Tokyo, as a project assistant professor at the Nagoya Institute of Technology, and as a researcher at Nagoya University in Japan. My PhD thesis concentrated on interpretable machine learning models for medical data. In addition to my academic expertise, I have extensive industry experience. After earning a BSc in Physics and a BTech in Applied Physics from the University of Calcutta, India, I began my professional career at TATA Consultancy Services Ltd. in Kolkata, where I worked for several years. I later moved to the UK to pursue an MSc in Advanced Computing from the University of Bristol, where I embarked on a new journey in academia.

Academic Advisors

I have been fortunate to work with the following researchers at different stages of my professional career: Professor Koji Tsuda (PhD Advisor), Professor Ichiro Takeuchi (Postdoc Advisor), Professor Julian Gough (MSc Advisor), Professor Amit Konar (Research Advisor at TATA Consultancy Services Ltd.).

Education

• PhD, Computational Biology and Medical Sciences, The University of Tokyo, Japan.
• MSc, Advanced Computing (Distinction), University of Bristol, Uk.
• BTech, Applied Physics (First Class), University of Calcutta, India.
• BSc, Physics (First Class with Honors), University of Calcutta, India.

Work Experience

• Postdoc Researcher, The University of Tokyo.
• Postdoc Researcher, Nagoya University.
• Project Assistant Professor, Nagoya Institute of Technology.
• Postdoc Researcher, The University of Tokyo.
• IT Analyst, TATA Consultancy Services Ltd., India.

Research Funding

My research is partially funded by the JSPS KAKENHI Young Scientist Research Grant for FY2023-2025.

Corporate Award

I was awarded twice in two consecutive years at TATA Consultancy Services Ltd. One for the outstanding paper award by the CTO of TATA Consultancy Services Ltd. and the other for significant contribution towards intellectual property creation by the Corporate IPR group of TATA Consultancy Services Ltd.

Teaching and Mentorship

I have been actively involved in mentoring and guiding the research projects of both master and graduate students. During my tenure at the Nagoya Institute of Technology, I provided an online lecture for graduate students on the topic of Trustworthy AI for High-Stakes Decision-Making Problems.

Patents

• Method and system for implementation of an interactive television application, D Das, A Ghose, P Sinha, P Biswas, US Patent 9,185,462.
• Method and system for automatic tagging in television using crowd sourcing technique, P Sinha, RK Gupta, A Ghose, B Chirabarata, D Das, US Patent 14/125,011
• Identification of people using multiple skeleton recording devices, K Chakravarty, A Sinha, D Das, R Banerjee, A Konar, S Dutta, US Patent 9,208,376.
• System and method for evaluating a cognitive load on a user corresponding to a stimulus, D.Das, D.Chatterjee, A.Sinharay, A. Sinha, US Patent 10,827,981.
• Selection of electroencephalography (eeg) channels valid for determining cognitive load of a subject, A.Sinharay, A.Sinha, D.Das, D.Chatterjee, US Patent 10,499,823.

Recent Articles

• Diptesh Das, Ichiro Takeuchi, Koji Tsuda. "Statistically Robust Sparse High-order Interaction Model", The 8th Workshop on Tractable Probabilistic Modeling, UAI 2025.
• Xiaotian Xue, Chao Huang, Koji Tsuda, Diptesh Das. "DT-sampler: A SAT-based Decision Tree Ensemble", 1st Workshop on Safe AI, UAI 2025.
• Chen Liang, Diptesh Das, Jiang Guo, Ryo Tamura, Zetian Mao, Koji Tsuda. "CRYSIM: Prediction of Symmetric Structures of Large Crystals with GPU-based Ising Machines", arXiv:2504.06878
• Jiawen Li, Jiang Guo, Yuanzhe Li, Zetian Mao, Jiaxing Shen, Tashi Xu, Diptesh Das, Jinming He, Run Hu, Yaerim Lee, Koji Tsuda, Junichiro Shiomi. "Inverse Design of Metamaterials with Manufacturing-Guiding Spectrum-to-Structure Conditional Diffusion Model", arXiv:2506.07083
• Haishan, Zhang, Diptesh Das, and Koji Tsuda. "Preference-Optimized Pareto Set Learning for Blackbox Optimization", arXiv:2408.09976 (2024).
• Mao, Zetian, Jiawen Li, Chen Liang, Diptesh Das, Masato Sumita, and Koji Tsuda. "Molecule Graph Networks with Many-body Equivariant Interactions", arXiv:2406.13265 (2024).
• Diptesh Das, Eugene Ndiaye, and Ichiro Takeuchi. "A confidence machine for sparse high-order interaction model", The 7th Workshop on Tractable Probabilistic Modeling, UAI 2024.
• HUANG, CHAO, Diptesh Das, and Koji Tsuda. "Feature Importance Measurement based on Decision Tree Sampling", The 3rd Workshop on Interpretable Machine Learning in Healthcare, ICML, 2023.

Publications (Selected)

• Diptesh Das, Ichiro Takeuchi, Koji Tsuda. "Statistically Robust Sparse High-order Interaction Model", The 8th Workshop on Tractable Probabilistic Modeling, UAI 2025.
• Diptesh Das, Eugene Ndiaye, and Ichiro Takeuchi. "A confidence machine for sparse high-order interaction model". Stat 13.1 (2024): e633.
• Diptesh Das, Vo Nguyen Le Duy, Hiroyuki Hanada, Koji Tsuda, and Ichiro Takeuchi. 2021. "Fast and More Powerful Selective Inference for Sparse High-order Interaction Model". AAAI 2022.
• Diptesh Das, Junichi Ito, Tadashi Kadowaki, and Koji Tsuda. 2019. "An interpretable machine learning model for diagnosis of Alzheimer’s disease". PeerJ 7 (2019), e6543.
• Diptesh Das, Anirudhha Sinha, Kingshuk Chakravarty and Amit Konar, "Stabilization of cluster centers over fuzziness control parameter in component-wise Fuzzy c-Means clustering", Fuzzy Systems (FUZZ), 2013 IEEE International Conference on, Hyderabad, India, 2013, pp. 1-8.
• Chakravarty, Kingshuk, Diptesh Das, Aniruddha Sinha, and Amit Konar, "Feature selection by Differential Evolution algorithm - A case study in personnel identification", 2013 IEEE Congress on Evolutionary Computation,Cancun,Mexico,2013,pp.892-899.
• Aniruddha Sinha, Diptesh Das, Kingshuk Chakravarty, Amit Konar and Sudeepto Dutta. Kinect based people identification system using fusion of clustering and classification". Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014, pp. 171-179.
• Diptesh Das, Debatri Chatterjee and Aniruddha Sinha. "Unsupervised approach for measurement of cognitive load using EEG signals". In Bioinformatics and Bioengineering (BIBE), 2013 IEEE 13th International Conference on, Chania, Greece, 2013, pp. 1-6.

Peer Review Experience

I review papers for leading machine learning conferences. In 2022, the ICML organizing committee recognized me as one of the top 10% of reviewers of ICML'2022 for my significant contributions as a meta-reviewer.