Shashank Kumar Roy, PhD

Incoming Postdoctoral Researcher — MIDS, Katholische Universität Eichstätt-Ingolstadt, Germany

Artificial Intelligence for Data Assimilation | Uncertainty Quantification

PhD Physics @ ICTS-TIFR · Former Postdoctoral Researcher @ IMT Atlantique, France

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Career at a Glance

Incoming · 2026

Postdoctoral Researcher

MIDS — Mathematical Institute for Machine Learning and Data Science, Katholische Universität Eichstätt-Ingolstadt · Ingolstadt, Germany

Nov 2023 — July 2026

Postdoctoral Researcher (Ingénieur de recherche)

Lab-STICC, IMT Atlantique · Brest, France

Uncertainty quantification and ensemble methods for 4DVarNet, a deep-learning-based data assimilation framework, with Prof. Ronan Fablet.


Education

Doctor of Philosophy in Physics — July 2020 – Jan 2024 (awarded 2025)
International Centre for Theoretical Sciences,
Tata Institute of Fundamental Research, Bangalore, India.
Advisors: Prof. Amit Apte & Prof. Samriddhi Sankar Ray. Thesis: A study of dynamical instability and filter stability using ensemble Kalman filter

Masters in Physics (coursework, Integrated-PhD) — 2017 – July 2020 · CPI 70.8 International Centre for Theoretical Sciences, Tata Institute of Fundamental Research, Bangalore, India.

Bachelors in Physics (Honors) — 2014 – 2017 · 84% Ramjas College, University of Delhi, New Delhi, India.


Publications

  1. Accepted Shashank Kumar Roy, Ronan Fablet. Spatiotemporal Coherent Displacements for Ensemble-Based Neural Data Assimilation. Environmental Data Science (EDS), special issue. hal-05585517

  2. Preprint Shashank Kumar Roy, Amit Apte. A note on sensitivity of Lyapunov vectors to trajectory perturbations. EGUsphere. doi:10.5194/egusphere-2023-2168

  3. Under review Pinak Mandal, Shashank Kumar Roy, Amit Apte. Probing robustness of nonlinear filter stability numerically using Sinkhorn divergence. Submitted to Physica D. arXiv:2208.10810

  4. Published Pinak Mandal, Shashank Kumar Roy, Amit Apte. Stability of nonlinear filters — numerical explorations of particle and ensemble Kalman filters. 2021 Seventh Indian Control Conference (ICC), IEEE, pp. 307–312. doi:10.1109/ICC54714.2021.9703185


Talks & Conferences

May 2026

Uncertainty Quantification in 4DVarNet via Spatiotemporal Coherent Displacements

Workshop on ML for Bi-Level Optimization, Data Assimilation and Uncertainty Quantification · Brest, France

April 2026

Spatiotemporal Coherent Displacements for Ensemble-Based Neural Data Assimilation

Climate Informatics 2026 · Lausanne, Switzerland

May 2025

Performance Gains and Advantages of 4DVarNet in End-to-End Learning for Data Assimilation

European Geosciences Union (EGU) General Assembly 2025 · Vienna, Austria

March 2025

Automatic Differentiation for 4DVar: Some Results in PyTorch with a QG Model

Space Applications Centre, ISRO · Ahmedabad, India

February 2025

4DVarNet: A Neural Network Model for Data Assimilation

Department of Data Science, IISER Pune · Pune, India

January 2025

Workshop: AI for Data Assimilation — 4DVar and 4DVarNet for Ocean Datasets

National Atmospheric Research Laboratory, Department of Space · Gadanki, India


Research Projects & Hackathons

GAN model for the distribution of Sea Surface Temperature — Hackathon Oct – Dec 2022
École Polytechnique, BNP Paribas, Fondation de l’École Polytechnique & Mercator Ocean

Modeled the distribution of sea surface temperature at six locations and interpolated to a new location using a GAN to perform regression.

LSTM model for spatial time series in climate model emulation — Hackathon Sep 2021
3rd NOAA AI Workshop — Climate Informatics Joint Hackathon

Predicted annual mean global distributions of temperature and precipitation from emissions and concentrations of key anthropogenic climate forcings: SO₂, BC, CH₄ and CO.

Winter Project — Sequential state estimation via Kalman filtering Oct – Dec 2019
International Centre for Theoretical Sciences, Bangalore

Sequential estimation of the conditional distribution of the state of a 40-dimensional nonlinear dynamical system with partial observations via Kalman filtering.

Summer Project — Stokes flow via Vector Spherical Harmonics Jun – Aug 2018
International Centre for Theoretical Sciences, Bangalore

Analytical calculation of Stokes flow inside a sphere generated by a given surface flow, using vector spherical harmonics; 3D flow visualizations built with the Python package mayavi.

Research Internship — Light pollution in the Indian context Oct 2015 – Nov 2016
University of Delhi Innovation Project

Project titled An Interdisciplinary Study of Light Pollution in the Indian Context (Extension): collection, analysis and quantification of light pollution from the Google light-pollution map.


Teaching Experience

Teaching Assistant — Computational Tools for Climate Science July 2023
Climatematch Academy (paid independent contract)

Supervised and assisted fellow students; conducted sessions on quantitative analysis of historical climate data using Python & Xarray, and led discussions of the underlying concepts.

Teaching Assistant — Time Series Analysis Jan – Apr 2023
Data Science Department, IISER Pune, India · Instructor: Dr. Tulasi Ram Reddy · course page

Curated Jupyter notebooks for demonstrations and conducted tutorial sessions.

Freelance — Advanced Physics Subject Matter Expert July 2020 – July 2021
Chegg India

Solved college- and university-level physics problems on an online platform.


Skills

Scientific

Bayesian Data Assimilation Ensemble Kalman Filtering Monte Carlo Methods Machine Learning Deep Learning Hidden Markov Models Reinforcement Learning Stochastic Processes Stochastic Differential Equations Nonlinear Dynamics Linear Algebra Probability & Statistics Mathematical Modeling Quantum Computation

Technical

Python PyTorch TensorFlow JAX SciPy scikit-learn Linux Git LaTeX HTML Hugo

Licenses & Certifications


Awards & Achievements


A CV is the evidence that ..

Life must be understood backwards but lived forwards.

— Søren Kierkegaard (a 19th-century Danish philosopher)