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M.S. in Computer Science

• Cumulative GPA: 3.88/4.00
• Relevant coursework:
  • Data Mining
  • Scalable Distributed System
  • Natural Language Processing
  • Information Retrieval
  • Database Management Systems

B.S. in Financial Actuarial Mathematics

• Cumulative GPA: 3.58/4.00
• Minor in Statistics
• Relevant coursework:
  • Probability Theory
  • Linear Algebra
  • Stochastic Process
  • Mathematical Statistics
  • Monte Carlo Methods
  • Time Series Analysis
  • Econometrics

Backend & ML Engineer

• Collaborated with frontend engineer and UI/UX designer to deliver multiple new features weekly in a fast-paced agile environment
• Tech Stack: Python, LangChain, CrewAI, GCP: (Vertex, Gemini, Cloud Storage), Azure: (Container Apps, Service Bus, OpenAI), Redis, WebSocket, gRPC, Flask, MongoDB

NLP Research Intern

• Contributed to the development of a question-answering model for complex tabular data using the ArXiv corpus
• Hosted by Raman Chandrasekar
• Tech Stack: Unix, Slurm, Python, PyTorch, Bash

Data Scientist Intern

• Enhanced the internet security products through data-driven improvements
• Tech Stack: Python, PySpark, SQL, AWS: (S3, Sagemaker), MLflow, Pandas, NumPy, Jupyter

AI Engineer Intern

• Played a key role in engineering an AI-based sensor monitoring system
• Tech Stack: Python, gRPC, RabbitMQ, PyTorch, Bash, OpenCV, HuggingFace, SQL, Airflow, Spark

Data Scientist Volunteer

Artificial Intelligence Graduate Certificate

• Relevant coursework: Deep Learning for Computer Vision, Reinforcement Learning, Deep Generative Models

Deep Learning Specialization

Machine Learning - Stanford