CV

Education

Ph.D. in Mathematics, University of Potsdam (2021 – Present)
- Supervised by Prof. Dr. Sebastian Reich
- Research Exchange: Isaac Newton Institute, University of Cambridge (2023)
- Focus: Bayesian inference, data assimilation, uncertainty-aware ML
M.Sc. in Mathematics, VNIT Nagpur, India (2018 – 2020)
B.Sc. (Hons.) in Mathematics, University of Delhi (2015 – 2018)

Doctoral Researcher, University of Potsdam & SFB1294 (Sep 2021 – Present)
- Developed robust, scalable inference methods for simulation-based and deep learning models
- Focused on uncertainty quantification in computer vision and NLP systems
Lecturer – Theory of Machine Learning, University of Potsdam (Winter 2024–25)
- Designed and taught Master’s-level course on ML foundations and Python-based implementation
Academic Writer, Paperpedia Pvt. Ltd. (Aug 2020 – Jun 2021)
- Authored academic content in mathematics and related domains

Generalized Bayesian Inference for Generative Models
- Gradient-free, loss-based posterior methods for simulators; improved efficiency by 80%
Ensemble Kalman Filters for Language Comprehension
- Trained NLP models under ambiguity; improved predictive uncertainty by 30%
Affine-Invariant Ensemble Transform for Neural Nets
- Improved reliability of deep networks under data distribution shift
Newton-type Methods for Nonlinear Ill-posed Problems
- Developed regularization strategies and error estimates

Diksha Bhandari, Alessandro Lopopolo, Milena Rabovsky, Sebastian Reich.
Ensemble Kalman filter for uncertainty in human language comprehension.
Read preprint
Diksha Bhandari, Jakiw Pidstrigach, Sebastian Reich.
Affine invariant ensemble transform methods to improve predictive uncertainty in neural networks. Foundations of Data Science, 2025 Read

Lecturer, Theory of Machine Learning, University of Potsdam (Winter 2024–25)