I build statistical and machine-learning models for climate and health data.
I'm currently a Research Technician at the Environmental Health Research Group, Czech University of Life Sciences in Prague, where I model temperature–mortality relationships using distributed lag non-linear models (DLNMs) and GAMs on ERA5 reanalysis and European surveillance data.
Before moving to Prague I completed an M.Tech in Data Science (9.6/10). My thesis explored emulating Earth system models with Gaussian Process Regression and deep generative models. I've also taught Machine Learning, Deep Learning and Advanced Analytics with Python at university level.
🎓 MSc Environmental Sciences, CULS Prague — graduating mid-2027;
💼 Open to part-time data analytics work in Prague (~20 hrs/week);
Daily: Python (pandas, scikit-learn, PyTorch, xarray) · R (dlnm, mgcv) · Linux · Git· LaTeX
Learning: Power BI · advanced SQL
Peer-reviewed
- Chaure, A., Behera, A. K., & Bhattacharya, S. (2023). Finding the Perfect Fit: Applying Regression Models to ClimateBench v1.0. International Journal of Computer Applications. Preprint: arXiv:2308.11854
- Chaure, A., Behera, A. K., & Bhattacharya, S. (2023). Gaussian Process Regression for Climate Modeling: Potentials, Limitations, and Advances in Emulation Techniques. Journal of Emerging Technologies and Innovative Research, 10(5), a277–a288. JETIR2305040
Preprints
- Chopade, A., Chaure, A., Schantz, M.-C., Xia, R., Berthold, D. E., Lefler, F. W., Laughinghouse IV, H. D., & Bertin, M. J. (2026). Shared biosynthetic architectures generate diverse β-amino polyketide residues in cyanobacterial peptides. bioRxiv. 10.64898/2026.06.02.729631