Bhskr Agrwl

Lead a multidisciplinary team of ~10 data scientists and developers, setting technical priorities and mentoring team members. Define product and technical strategy for reusable AI/data products across energy, infrastructure, and industrial applications, from architecture through production delivery.

Led a 6-person technical team building and rolling out a production geospatial optimization platform across 7 countries, reducing OPEX by 10–30% (~€1–3M per country). Owned the product and technical lifecycle from PoC to production, delivering forecasting, classification, and internal AI products.

Co-founded and technically led development of a sustainability platform modelling company/product carbon footprints and decarbonisation pathways. Took the product from mathematical models to working software, translating early customer feedback into architecture and product priorities.

Technical lead for industry and research partners developing and optimizing AI workloads on Tier-0/Tier-1 supercomputers. Built distributed data/ML systems for real-world applications, including environmental forecasting pipelines and federated learning across independent institutions.

Developed ML and optimization systems for energy and public infrastructure, including real-time energy management, demand forecasting, and anomaly detection. Achieved a podium finish in the Ruhr Challenge 2018 for day-ahead gas-price forecasting.

Specialized in large-scale cosmic simulations, first-principles modeling, and data-intensive computing. Published 20+ peer-reviewed scientific papers.

Ph.D. in Astrophysics from LMU Munich and Max Planck Institute.