CV

Education

• MSc in Applied Analytics (Expected), Columbia University, 2025
  • GPA: 4.0 (Projected)
  • Courses: Applied Text and Natural Language Analytics, Financial Data Science and ML, Anomaly Detection
• BASc in Arts and Sciences, UCL (First Class Honors), 2024
  • Focus: Mathematics, Computer Science, Philosophy

Research Experience

• Prakrit-to-English Translation via In-Context Learning
  • Columbia University, Mar 2024 – Present
  • Investigated low-resource LLM translation using TF-IDF vs. NMF example selection; evaluated with BLEU & SBERT
• Differential Privacy Mechanisms for Real-Time Data Streams
  • UCL, Jan 2023 – May 2024
  • Proposed exponential mechanism; improved latency by 35% and accuracy by 15%
• Structural Mediation Modeling in Urban Socioeconomics
  • UCL, Sep 2023 – Jan 2024
  • Led SEM on 27,376 cases; found housing costs mediate 77% of transit effect on employment
• Causal Inference in Geo-Political Economics
  • UCL, Sep 2022 – Jan 2023
  • Used RDiT and DiD to analyze conflict/oil price links; built reproducible Python pipeline
• Sustainable Transportation Accessibility Analysis
  • UCL, Jan 2022 – Apr 2022
  • Developed GIS framework to evaluate London cycle routes

Skills

• Programming: Python (NumPy, Pandas, Scikit-learn), Java, C++, LaTeX
• NLP & ML: LLMs, BLEU, SBERT, TF-IDF, NMF, Retrieval-Augmented Generation
• Analytics Software: Excel, Office Suite
• Research: Causal inference, SEM, technical writing, prompt engineering