I am a postdoc researcher at a Sandia National Laboratories, where I design algorithms and tools for Bayesian inference, Machine Learning, and optimal experiment design.
My research aims to enhance problem solving in various fields including AI, controls, and power systems.
I am passionate about teaching people how to apply these techniques in their own work and to further advance our understanding of these areas.
ndas [at] sandia [dot] gov
nil.das.adri [at] gmail [dot] com
Education
Ph.D. in Aerospace Engineering, 2020. Texas A&M University, College Station, USA.
M.Tech. in Electrical Engineering, 2014. Indian Institute of Technology, Kanpur, India.
B.E.E. in Electrical Engineering, 2012. Jadavpur University, Kolkata, India.
Recent Publications
Metrics for Bayesian Optimal Experiment Design under Model Misspecification | Tommie A. Catanach and Niladri Das |
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| IEEE CDC 2023
Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions | Niladri Das, Jed A. Duersch, and Tommie A. Catanach |
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| IEEE CDC 2022 |
Adaptive n-ary Activation Functions for Probabilistic Boolean Logic | Jed A. Duersch, Thomas A. Catanach, and Niladri Das | 2022 |
| Submitted to Information Sciences
Utility and Privacy in Object Tracking from Video Stream using Kalman Filter | Niladri Das
and Raktim Bhattacharya | FUSION 2020 |
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Modeling and Optimal Control of Hybrid UAVs with Wind Disturbance | Sunsoo Kim, Niladri Das
, and Raktim Bhattacharya | ICSC 2020 |
Eigen Value Analysis in Lower Bounding Uncertainty of Kalman Filter Estimates | Niladri Das
and Raktim Bhattacharya | IFAC World Congress 2020 |
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Optimal Transport Based Filtering with Nonlinear State Equality Constraints | Niladri Das
and Raktim Bhattacharya | IFAC World Congress 2020 |
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Optimal Sensing Precision in Ensemble and Unscented Kalman Filtering | Niladri Das
and Raktim Bhattacharya | IFAC World Congress 2020 |
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On Neural Network Training from Noisy Data using a Novel Filtering Framework | V. Deshpande, Niladri Das
, V. Tadiparthi, and R. Bhattacharya | AIAA SciTech Forum and Exposition 2020 |
Privacy and Utility Aware Data Sharing for Space Situational Awareness from Ensemble and Unscented Kalman Filtering Perspective | Niladri Das
and Raktim Bhattacharya | IEEE Transactions on Aerospace and Electronic Systems | 2019 |
Talks and Posters
IEEE CDC, Cancun, Mexico | Dec 6-9, 2022 | Presentation
Society of Engineering Sciences Annual Technical Meeting, College Station, TX, USA | October 16-19, 2022 | RL in Material Science Research | Presentation
SIAM Annual Meeting, Pittsburg, Pennsylvania, USA | July 11-15, 2022 | Presentation
Won best poster award and travel grant at ISBA, Montreal, Canada | June 26-July 1, 2022
Organized Mini-symposium at SIAM UQ, Atlanta, Georgia, USA | April 11-15, 2022 | Presented on Variational Inference
21st IFAC World Congress, Germany | July 11-17, 2020 | 3 Online presentations
23rd International Conference on Information Fusion, South Africa | July 6-9, 2020 | Online presentation
U.S. Air Force Science and Technology 2030 | Space Situational Awareness | June 2018 | Poster
Texas Systems Day | Optimal Transport Based Satellite State Estimation | March 31, 2017 | Poster
Projects and Fundings
Graduate Research Assistantship | Dr.Kyle DeMars | Faculty Research Startup Fund Summer 2020
Graduate Teaching Assistantship | Spring 2020 (partial)
National Science Foundation | Grant Award No. NSF 1762825 | Spring 2020 (partial)
Graduate Teaching Fellowship | Department of Engineering at Texas A&M University | Fall 2019
Adaptive Markov Inference Game Optimization (AMIGO) for Rapid Discovery of Evasive Satellite Behaviors | PI: Raktim Bhattacharya, Intelligent Fusion Technology, Inc. | 2018
Cloud Computing Based Robust Space Situational Awareness | PI: Raktim Bhattacharya, Co-PI: Bani Mallick, AFOSR | 2015-2018