Curriculum Vitae

MSc in Data Science (EPFL) with a background in quantitative research for fixed-income markets and building enterprise-scale AI workflows and agentic systems for law firms. Experienced in orchestrating LLM-powered document analysis pipelines, investment strategy research, and data-driven tooling. Passionate about building AI systems that leverage existing data, learn alongside their users, and evolve into trusted analytical partners.

Education

École polytechnique fédérale de Lausanne (EPFL)
MSc in Data Science · Grade: 5.67/6 · Research Scholars Program
Sep 2022 – Mar 2025
Lausanne, Switzerland
Indian Institute of Technology Madras
BTech in Engineering Physics
Jul 2017 – May 2021
Chennai, India

Technical Skills

Languages & Tools

PythonCJavaJavaScriptGitDocker

ML & AI Frameworks

PyTorchvLLMOllamaDSPyOpenAI Agents SDK

Data & Infrastructure

PySparkPostgreSQLQdrantChromaDBPandas

Visualization

StreamlitPlotlyDash

Professional Experience

AI Workflow Architect
DeepJudge
Jul 2025 – Mar 2026 · Zurich, Switzerland
  • Architected and deployed production AI workflows and agentic systems that search 2M+ legal-document indexes to automate complex document-analysis tasks.
  • Built 10+ workflows orchestrating semantic search, LLM calls, document parsing, and JavaScript for custom transformations.
ML Research Intern (Master's Thesis)
Logitech Innovation Centre
Aug 2024 – Feb 2025 · Lausanne, Switzerland
  • Benchmarked 11 Small Language Models for on-device deployment, achieving ≤100 ms latency and 30+ tokens/s on a 4 GB GPU.
  • Compiled a technical report on latency–context-length relationships, needle-in-a-haystack performance, and memory-scaling for SLMs.
Quantitative Research Intern
Garda Capital Partners
Aug 2023 – Jan 2024 · Geneva, Switzerland
  • Developed a deep RL model for portfolio construction using returns, volatility, and market-context features.
  • Delivered research on risk-aversion, market-neutral, and trend-following strategies within fixed-income products.
Data Science Research Intern
Adobe Media and Data Science Research Lab
May 2020 – Jul 2020 · Bangalore, India
  • Developed a hybrid quantum-classical clustering algorithm (Q-means) using variational quantum feature embedding for large-scale data segmentation.
  • Offered a full-time position post-internship.

Research Projects

Ethical Alignment of LLMs with RL from AI Feedback
Semester Project, EPFL · Guide: Alexander Rusnak
Feb 2024 – Jun 2024
  • Encoded a virtue-ethics framework into LLMs via supervised fine-tuning and RL training using PyTorch and Hugging Face.
Predator–Prey Simulation using Reinforcement Learning
Course Project, EPFL · Guide: Prof. Amir Zamir
Feb 2023 – Jul 2023
  • Studied emergent predator–prey dynamics through simulated vision and RL across different vision types.
  • Received Best Course Project Award → sponsored trip to ICML 2024.
Online Estimation and Optimization of Shortfall Risk
IIT Madras · Guides: Prof. L.A. Prashanth & Prof. K. Jagannathan
Aug 2020 – Jul 2021
  • Proposed SGD-based algorithms for shortfall risk estimation and optimization. Published in Mathematics of Operations Research.

Publications

Online Estimation and Optimization of Utility-Based Shortfall Risk
Mathematics of Operations Research, 48(4), 2444–2470 · 2023
Q-means using Variational Quantum Feature Embedding
arXiv Preprint · 2021

Awards

🏆
EPFL Research Scholars MSc Program — Research scholarship awarded alongside MSc admission.
🥇
HackUPC 2024 Winner and two-time LauzHack winner (2022, 2024). See Devpost.
🎓
Best Course Project Award — "Visual Intelligence: Machine and Minds" at EPFL → sponsored trip to ICML 2024 in Vienna.

Relevant Coursework

Data Science & ML

  • Modern NLP
  • Optimization for Machine Learning
  • Neural Networks & Reinforcement Learning
  • Large-Scale Data Science
  • Applied Data Analysis
  • Advanced Topics in AI
  • Data Structures and Algorithms

Mathematics & Statistics

  • Information Theory
  • Causal Inference
  • Estimation Theory
  • Applied Statistics
  • Mathematics of Data
  • Probability Theory
  • Applied Linear Algebra