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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Diptesh Das - Research Portfolio</title>
<link rel="stylesheet" href="styles.css">
</head>
<body>
<header>
<h1>Diptesh Das</h1>
<p>Researcher at the Department of Computational Biology and Medical Sciences, The University of Tokyo.</p>
<nav>
<ul>
<li><a href="index.html">Home</a></li>
<li><a href="https://www.tsudalab.org/en/members/" target="_blank">Lab</a></li>
<li><a href="project.html">Projects</a></li>
<li><a href="https://scholar.google.co.in/citations?user=8DWrGBwAAAAJ&hl=en" target="_blank">Google Scholar</a></li>
</ul>
</nav>
</header>
<section id="bio">
<h2>Bio</h2>
<p style="text-align:justify;">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.</p>
</section>
<section id="supervisors">
<h2>Academic Advisors</h2>
<p style="text-align:justify;">I have been fortunate to work with the following researchers at different stages of my professional career: Professor <a href="https://scholar.google.com/citations?user=HvVqBmkAAAAJ&hl=en">Koji Tsuda</a> (PhD Advisor), Professor <a href="https://scholar.google.de/citations?user=IwBHa3gAAAAJ&hl=en">Ichiro Takeuchi</a> (Postdoc Advisor), Professor <a href="https://scholar.google.com/citations?user=7p6iOO4AAAAJ&hl=en">Julian Gough</a> (MSc Advisor), Professor <a href="https://scholar.google.com/citations?user=s1F23CAAAAAJ&hl=en">Amit Konar</a> (Research Advisor at TATA Consultancy Services Ltd.).</p>
</section>
<section id="education">
<h2>Education</h2>
<ul>
<li>PhD, Computational Biology and Medical Sciences, The University of Tokyo, Japan.</li>
<li>MSc, Advanced Computing (Distinction), University of Bristol, Uk.</li>
<li>BTech, Applied Physics (First Class), University of Calcutta, India.</li>
<li>BSc, Physics (First Class with Honors), University of Calcutta, India.</li>
</ul>
</section>
<section id="experience">
<h2>Work Experience</h2>
<ul>
<li>Postdoc Researcher, The University of Tokyo.</li>
<li>Postdoc Researcher, Nagoya University.</li>
<li>Project Assistant Professor, Nagoya Institute of Technology.</li>
<li>Postdoc Researcher, The University of Tokyo.</li>
<li>IT Analyst, TATA Consultancy Services Ltd., India.</li>
</ul>
</section>
<section id="funding">
<h2>Research Funding</h2>
<p>
My research is partially funded by the JSPS KAKENHI Young Scientist Research Grant for FY2023-2025.
</p>
</section>
<section id="award">
<h2>Corporate Award</h2>
<p>
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.
</p>
</section>
<section id="teaching">
<h2>Teaching and Mentorship</h2>
<p style="text-align:justify;">
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.
</p>
</section>
<!-- <section id="patents">
<h2>Patents</h2>
<ul>
<li>
Method and system for implementation of an interactive television application, D Das, A Ghose, P Sinha, P Biswas, <a href="https://www.google.com/patents/US9185462">US Patent 9,185,462</a>.
</li>
<li>
Method and system for automatic tagging in television using crowd sourcing technique, P Sinha, RK Gupta, A Ghose, B Chirabarata, D Das, <a href="http://www.google.com/patents/US9357242"> US Patent 14/125,011 </a>
</li>
<li>
Identification of people using multiple skeleton recording devices, K Chakravarty, A Sinha, D Das, R Banerjee, A Konar, S Dutta, <a href="https://www.google.com/patents/US9208376">US Patent 9,208,376</a>.
</li>
<li>
System and method for evaluating a cognitive load on a user corresponding to a stimulus, D.Das, D.Chatterjee, A.Sinharay, A. Sinha, <a href="https://patents.google.com/patent/US10827981B2/en">US Patent 10,827,981</a>.
</li>
<li>
Selection of electroencephalography (eeg) channels valid for determining cognitive load of a subject, A.Sinharay, A.Sinha, D.Das, D.Chatterjee, <a href=" https://patents.google.com/patent/US10499823B2/en">US Patent 10,499,823</a>.
</li>
</ul>
</section> -->
<!-- <section id="recent_publications">
<h2>Recent Articles</h2>
<ul class="pub-list">
<li><b>Diptesh Das<sup>*</sup></b>, Ichiro Takeuchi, Koji Tsuda.
<a href="https://openreview.net/pdf?id=BL6vK8GeoR">"Statistically Robust Sparse High-order Interaction Model"</a>,
<a href="https://aaai.org/conference/aaai/aaai-26/main-technical-track/" style="color: red;">AAAI2026</a>
Main Technical Track (<u>17.6% overall acceptance rate</u>). Work in progress version accepted in
<a href="https://tractable-probabilistic-modeling.github.io/tpm2025/papers/" style="color: red;">UAI 2025</a> workshop (TPM2025).
</li>
<li>Xiaotian Xue, Chao Huang, Koji Tsuda, <b>Diptesh Das <sup>*</sup></b>.
<a href="https://dl.acm.org/doi/abs/10.1145/3787470.3787484">"DT-sampler: A SAT-based Decision Tree Ensemble"</a>,
<a href="https://kdd.org/explorations" style="color: red;">SIGKDD Explorations</a>
(<u>Impact Factor: 6.32 as of 2024</u>). Work in progress version accepted in
<a href="https://sites.google.com/view/safeai2025/schedule?authuser=0" style="color: red;">UAI 2025</a> workshop and also in
<a href="https://icml.cc/virtual/2023/27731" style="color: red;">ICML 2023</a> workshop.
</li>
<li>Chen Liang, <b>Diptesh Das</b>, Jiang Guo, Ryo Tamura, Zetian Mao, Koji Tsuda.
<a href="https://www.nature.com/articles/s42005-025-02380-y">"CRYSIM: Prediction of Symmetric Structures of Large Crystals with GPU-based Ising Machines"</a>,
<a href="https://www.nature.com/commsphys/" style="color: red;">Communications Physics, Nature</a>
(<u>Impact Factor: 5.8 as of 2024</u>).
</li>
<li>Mao, Zetian, Jiawen Li, Chen Liang, <b>Diptesh Das</b>, Masato Sumita, and Koji Tsuda.
<a href="https://pubs.acs.org/doi/full/10.1021/acs.jctc.5c00466">"Molecule Graph Networks with Many-body Equivariant Interactions"</a>,
<a href="https://pubs.acs.org/doi/full/10.1021/acs.jctc.5c00466" style="color: red;">Journal of Chemical Theory and Computation</a>
(<u>Impact Factor: 6.4 as of 2024</u>).
</li>
<li><b>Diptesh Das<sup>*</sup></b>, Eugene Ndiaye, and Ichiro Takeuchi.
<a href="https://onlinelibrary.wiley.com/doi/10.1002/sta4.633">"A confidence machine for sparse high-order interaction model"</a>,
<a href="https://onlinelibrary.wiley.com/doi/10.1002/sta4.633" style="color: red;">Stat, 2024</a>
(<u>Impact Factor: 0.8, 2024</u>), also accepted in
<a href="https://tractable-probabilistic-modeling.github.io/tpm2024/" style="color: red;">UAI 2024</a> Workshop.
</li>
<li>Jiawen Li, Jiang Guo, Yuanzhe Li, Zetian Mao, Jiaxing Shen, Tashi Xu, <b>Diptesh Das</b>, Jinming He, Run Hu, Yaerim Lee, Koji Tsuda, Junichiro Shiomi.
<a href="https://arxiv.org/pdf/2506.07083">"Inverse Design of Metamaterials with Manufacturing-Guiding Spectrum-to-Structure Conditional Diffusion Model"</a>,
arXiv:2506.07083.
</li>
<li>Haishan Zhang, <b>Diptesh Das<sup>*</sup></b>, and Koji Tsuda.
<a href="https://arxiv.org/pdf/2408.09976">"Preference-Optimized Pareto Set Learning for Blackbox Optimization"</a>,
arXiv:2408.09976 (2024).
</li>
</ul>
</section> -->
<section id="patents">
<h2>Patents</h2>
<ul class="patent-list">
<li>
<div class="patent-title">Method and system for implementation of an interactive television application</div>
<div class="patent-authors">D. Das, A. Ghose, P. Sinha, P. Biswas</div>
<div class="patent-ref"><a href="https://www.google.com/patents/US9185462">US Patent 9,185,462</a></div>
</li>
<li>
<div class="patent-title">Method and system for automatic tagging in television using crowd sourcing technique</div>
<div class="patent-authors">P. Sinha, R.K. Gupta, A. Ghose, B. Chirabarata, D. Das</div>
<div class="patent-ref"><a href="http://www.google.com/patents/US9357242">US Patent 14/125,011</a></div>
</li>
<li>
<div class="patent-title">Identification of people using multiple skeleton recording devices</div>
<div class="patent-authors">K. Chakravarty, A. Sinha, D. Das, R. Banerjee, A. Konar, S. Dutta</div>
<div class="patent-ref"><a href="https://www.google.com/patents/US9208376">US Patent 9,208,376</a></div>
</li>
<li>
<div class="patent-title">System and method for evaluating a cognitive load on a user corresponding to a stimulus</div>
<div class="patent-authors">D. Das, D. Chatterjee, A. Sinharay, A. Sinha</div>
<div class="patent-ref"><a href="https://patents.google.com/patent/US10827981B2/en">US Patent 10,827,981</a></div>
</li>
<li>
<div class="patent-title">Selection of electroencephalography (EEG) channels valid for determining cognitive load of a subject</div>
<div class="patent-authors">A. Sinharay, A. Sinha, D. Das, D. Chatterjee</div>
<div class="patent-ref"><a href="https://patents.google.com/patent/US10499823B2/en">US Patent 10,499,823</a></div>
</li>
</ul>
</section>
<section id="selected_publications">
<h2>Selected Publications</h2>
<div class="pub-legend"> *First and/or Main Corresponding Author </div>
<ol class="pub-list">
<li>
<div class="pub-title">Statistically Robust Sparse High-order Interaction Model</div>
<div class="pub-authors">Diptesh Das*, Ichiro Takeuchi, Koji Tsuda</div>
<div class="pub-venue">AAAI-26 Main Technical Track, 2026.</div>
<a href="https://openreview.net/pdf?id=BL6vK8GeoR">[PDF]</a>
<div class="pub-note"> * Work-in-progress version accepted at <a href="https://tractable-probabilistic-modeling.github.io/tpm2025/papers/">UAI 2025 Workshop (TPM)</a>. </div>
</li>
<li>
<div class="pub-title">DT-sampler: A SAT-based Decision Tree Ensemble</div>
<div class="pub-authors">Xiaotian Xue, Chao Huang, Koji Tsuda, Diptesh Das*</div>
<div class="pub-venue">ACM SIGKDD Explorations, 2025.</div>
<a href="https://doi.org/10.1145/3787470.3787484">[PDF]</a>
<div class="pub-note"> * Work-in-progress version accepted at <a href="https://sites.google.com/view/safeai2025/schedule?authuser=0">UAI 2025 Workshop (Safe AI)</a> and also at <a href="https://openreview.net/group?id=ICML.cc/2023/Workshop/IMLH#tab-accept-poster-short-paper">ICML 2023 Workshop (IMLH)</a>. </div>
</li>
<li>
<div class="pub-title">CRYSIM: Prediction of Symmetric Structures of Large Crystals with GPU-based Ising Machines</div>
<div class="pub-authors">Chen Liang, Diptesh Das, Jiang Guo, Ryo Tamura, Zetian Mao, Koji Tsuda</div>
<div class="pub-venue">Communications Physics, Nature, 2025.</div>
<a href="https://www.nature.com/articles/s42005-025-02380-y">[PDF]</a>
</li>
<li>
<div class="pub-title">Molecule Graph Networks with Many-body Equivariant Interactions</div>
<div class="pub-authors">Zetian Mao, Chuan-Shen Hu, Jiawen Li, Chen Liang, Diptesh Das, Masato Sumita, Kelin Xia, Koji Tsuda</div>
<div class="pub-venue">Journal of Chemical Theory and Computation, 2025.</div>
<a href="https://pubs.acs.org/doi/full/10.1021/acs.jctc.5c00466">[PDF]</a>
</li>
<li>
<div class="pub-title">A confidence machine for sparse high-order interaction model</div>
<div class="pub-authors">Diptesh Das*, Eugene Ndiaye, Ichiro Takeuchi</div>
<div class="pub-venue">Stat, 2024.</div>
<a href="https://onlinelibrary.wiley.com/doi/pdf/10.1002/sta4.633">[PDF]</a>
</li>
<li>
<div class="pub-title">Fast and More Powerful Selective Inference for Sparse High-order Interaction Model</div>
<div class="pub-authors">Diptesh Das*, Vo Nguyen Le Duy, Hiroyuki Hanada, Koji Tsuda, Ichiro Takeuchi</div>
<div class="pub-venue">AAAI 2022 Main Technical Track.</div>
<a href="https://ojs.aaai.org/index.php/AAAI/article/view/21238">[PDF]</a>
</li>
<li>
<div class="pub-title">An interpretable machine learning model for diagnosis of Alzheimer's disease</div>
<div class="pub-authors">Diptesh Das*, Junichi Ito, Tadashi Kadowaki, Koji Tsuda</div>
<div class="pub-venue">PeerJ 7 (2019), e6543.</div>
<a href="https://peerj.com/articles/6543/">[PDF]</a>
</li>
<li>
<div class="pub-title">Feature selection by Differential Evolution algorithm -- A case study in personnel identification</div>
<div class="pub-authors">Kingshuk Chakravarty, Diptesh Das, Aniruddha Sinha, Amit Konar</div>
<div class="pub-venue">IEEE Congress on Evolutionary Computation, 2013.</div>
<a href="https://ieeexplore.ieee.org/abstract/document/6557662">[PDF]</a>
</li>
<li>
<div class="pub-title">Stabilization of cluster centers over fuzziness control parameter in component-wise Fuzzy c-Means clustering</div>
<div class="pub-authors">Diptesh Das*, Aniruddha Sinha, Kingshuk Chakravarty, Amit Konar</div>
<div class="pub-venue">IEEE International Conference on Fuzzy Systems (FUZZ), 2013.</div>
<a href="https://ieeexplore.ieee.org/abstract/document/6622461">[PDF]</a>
</li>
</ol>
</section>
<section id="preprints">
<h2>Preprints</h2>
<ol class="pub-list">
<li>
<div class="pub-title">Inverse Design of Metamaterials with Manufacturing-Guiding Spectrum-to-Structure Conditional Diffusion Model</div>
<div class="pub-authors">Jiawen Li, Jiang Guo, Yuanzhe Li, Zetian Mao, Jiaxing Shen, Tashi Xu, Diptesh Das, Jinming He, Run Hu, Yaerim Lee, Koji Tsuda, Junichiro Shiomi</div>
<div class="pub-venue">arXiv:2506.07083 (2025).</div>
<a href="https://arxiv.org/pdf/2506.07083">[PDF]</a>
</li>
<li>
<div class="pub-title">Preference-Optimized Pareto Set Learning for Blackbox Optimization</div>
<div class="pub-authors">Haishan Zhang, Diptesh Das*, Koji Tsuda</div>
<div class="pub-venue">arXiv:2408.09976 (2024).</div>
<a href="https://arxiv.org/pdf/2408.09976">[PDF]</a>
</li>
</ol>
</section>
<!-- <section id="publications">
<h2>Publications (Selected)</h2>
<ul>
<li><b>Diptesh Das<sup>*</sup></b>, Ichiro Takeuchi, Koji Tsuda.
<a href="https://openreview.net/pdf?id=BL6vK8GeoR">"Statistically Robust Sparse High-order Interaction Model"</a>,
<a href="https://aaai.org/conference/aaai/aaai-26/main-technical-track/" style="color: red;">AAAI2026</a>
Main Technical Track (<u>17.6% overall acceptance rate</u>).
</li>
<li><b>Diptesh Das<sup>*</sup></b>, Eugene Ndiaye, and Ichiro Takeuchi.
<a href="https://onlinelibrary.wiley.com/doi/10.1002/sta4.633">"A confidence machine for sparse high-order interaction model"</a>,
<a href="https://onlinelibrary.wiley.com/doi/10.1002/sta4.633" style="color: red;">Stat, 2024</a>
(<u>Impact Factor: 0.8 as of 2024</u>).
</li>
<li>
Diptesh Das, Vo Nguyen Le Duy, Hiroyuki Hanada, Koji Tsuda, and Ichiro Takeuchi. 2021. <a href="https://ojs.aaai.org/index.php/AAAI/article/view/21238"> "Fast and More Powerful Selective Inference for Sparse High-order Interaction Model"</a>. <a href="" style="color: red;">AAAI 2022</a> Main Techinical Track (<u>15% overall acceptance rate</u>).
</li>
<li>
Diptesh Das, Junichi Ito, Tadashi Kadowaki, and Koji Tsuda. 2019. <a href="https://peerj.com/articles/6543/"> "An interpretable machine learning model for diagnosis of Alzheimer’s disease"</a>. <a style="color: red;">PeerJ (2019)</a>.
</li>
<li>
Diptesh Das, Anirudhha Sinha, Kingshuk Chakravarty and Amit Konar, <a href="https://ieeexplore.ieee.org/abstract/document/6622461"> "Stabilization of cluster centers over fuzziness control parameter in component-wise Fuzzy c-Means clustering"</a>, <a style="color: red;">IEEE FUZZ (2013)</a>.
</li>
<li>
Chakravarty, Kingshuk, Diptesh Das, Aniruddha Sinha, and Amit Konar, <a href="https://ieeexplore.ieee.org/abstract/document/6557662"> "Feature selection by Differential Evolution algorithm - A case study in personnel identification"</a>, <a style="color: red;">IEEE CEC (2013)</a>.
</li>
<li>
Aniruddha Sinha, Diptesh Das, Kingshuk Chakravarty, Amit Konar and Sudeepto Dutta. <a href="https://ieeexplore.ieee.org/abstract/document/7295077">Kinect based people identification system using fusion of clustering and classification"</a>. Computer Vision Theory and Applications (VISAPP), 2014 International Conference on, Lisbon, Portugal, 2014, pp. 171-179.
</li>
<li>
Diptesh Das, Debatri Chatterjee and Aniruddha Sinha. <a href="https://ieeexplore.ieee.org/abstract/document/6701686">"Unsupervised approach for measurement of cognitive load using EEG signals"</a>. In Bioinformatics and Bioengineering (BIBE), 2013 IEEE 13th International Conference on, Chania, Greece, 2013, pp. 1-6.
</li>
</ul>
</section> -->
<section id="pr">
<h2>Peer Review Experience</h2>
<p>
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.
</p><br/><br/><br/>
</section>
<footer>
<p>Contact: [firstname].[lastname]@edu.k.u-tokyo.ac.jp</p>
</footer>
</body>
</html>