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Ashutosh has completed a Master of Science in Quantitative Data Science Methods at the Eberhard Karls University of Tübingen. His research focuses on developing rigorous statistical and machine learning methods — with particular interest in causal inference, optimal transport, and probabilistic modelling — to understand the structure of complex systems.

He has conducted research at the Max Planck Institute for Intelligent Systems, where his master's thesis applies optimal transport theory to linear Independent Component Analysis (ICA). Prior to his graduate studies, he worked three years as a Software Engineer at HSBC (Global Cloud Economics). He has also completed an internship in the financial stability department of the Deutsche Bundesbank and an Erasmus Exchange at KU Leuven, where he focused on financial econometrics and causal machine learning.

Skills & Methods
Research Methods Optimal Transport Causal Inference & Discovery Bayesian Methods Independent Component Analysis Econometrics Time Series Analysis Probabilistic ML Programming & Frameworks Python PyTorch R MATLAB SQL Git Tools & Infrastructure Docker FastAPI LangChain GCP / AWS
Background
Education
Master Thesis: Optimal Transport in Linear ICA
Max Planck Institute for Intelligent Systems and University of Tuebingen
Present
Researching the application of Optimal Transport theory to linear Independent Component Analysis (ICA).
Supervisors: Dr. Simon Buchholz, Prof. Dr. Michel Besserve, Prof. Dr. Joachim Grammig
Project
Heilbronn Hackathon 2026: TuebiFit
Cursor Hackathon
March 2026
Architected a full-stack, LLM-powered agentic application utilizing LangChain, FastAPI, and retrieval-augmented generation (RAG) pipelines. View GitHub.
Experience
Intern Quantitative Analyst (Financial Stability)
Deutsche Bundesbank, Frankfurt
July 2025 – Sept 2025
  • Applied machine learning and time series forecasting to analyze investment fund portfolios.
  • Focused on financial stability insights for non-bank financial intermediaries.
Education
Erasmus Exchange (Financial Economics & ML)
KU Leuven, Belgium
Feb 2025 – June 2025
Focused on Financial Economics, Causal Machine Learning and Financial Engineering.
Experience
Graduate Research Assistant (Optics & Sensing)
Max Planck Institute for Intelligent Systems
July 2024 – June 2025
Developed computer vision algorithms (emotion/head orientation) for GitHub NICEToolbox.
Award
Winner - Best Pitch & Co-creation Prize
Neckarthon (Startup Center Tübingen)
November 2024
Won dual prizes for "Tue-bi-smart," an ML-enabled transport prototype developed for Stadtwerke Tübingen.
Education
M.Sc. Quantitative Data Science Methods
Eberhard Karls Universität Tübingen
Started Oct 2023
Specializing in Econometrics, Machine Learning, and Financial Economics.
Experience
Software Engineer (Cloud Economics)
HSBC Holdings PLC, Pune
Sept 2020 – Sept 2023
  • Built real-time ETL pipelines (improving latency by 4x) and designed FinOps frameworks.
  • Developed statistical models driving $500K in cloud cost savings.
Certifications
Professional Certifications (2022)
2022
Award
Star Performer Award
HSBC Technology
Q2 2021
Awarded for high performance in cloud billing automation.
View Award
Certifications
Professional Certifications (2021)
2021
Experience
Software Engineering Intern
Nvidia Corporation, Bengaluru
Aug 2019 – Dec 2019
Built a customer-facing Python tool with real-time Plotly visualizations to analyze SoC CPU usage.
Experience
Internship: Industrial Process Optimization
iCreate, Ahmedabad
May 2018 – July 2018
Analyzed manufacturing plants to identify automation opportunities and submitted a process optimization report.
Education
B.E. Electrical and Electronics Engineering
BITS Pilani, Goa Campus
2016 – 2020
Achievement: Awarded the Prime Minister's Scholarship Scheme (2017) for academic excellence.