Key Projects

All of my projects can be found on my GitHub profile. Below are brief descriptions of selected projects:

• Analyzing Selfish Mining and Eclipse Attack in a P2P Cryptocurrency Network

  Guide: Prof. Vinay Ribeiro | Course Project: Blockchains, Cryptocurrencies and Smart Contracts

  • Developed a P2P blockchain simulator with 100+ nodes, PoW mining and fork resolution under delays
  • Simulated Selfish Mining + Eclipse Attacks; showed >50% malicious nodes cause full chain takeover
  • Proposed a trust-based defence reducing malicious block acceptance by 95% with 40% malicious actors

• C Compiler Development

  Guide: Prof. Uday Khedker | Course Project: Implementation of Programming Languages

  • Built a simplified C compiler in C++ using Lex/Yacc with lexer, parser and context-free grammar
  • Engineered end-to-end compilation pipeline including abstract syntax tree construction, intermediate representation, basic optimizations and MIPS code generation in six incremental stages
  • Integrated robust error handling in all phases to detect and reject syntactic and semantic violations

• Automated Index Creation in a Database

  Guide: Prof. Sudarshan | Course Project: Database and Information Systems

  • Built an automated PostgreSQL indexer that adapts to query patterns, reducing execution time by 40%
  • Used attribute frequencies and planner feedback for adaptive indexing without DBA intervention
  • Designed a live query monitor with cost-aware filtering via hypopg and custom tracking structures

• Denoising Diffusion Probabilistic Models

  Guide: Prof. Sunita Sarawagi | Course Project: Advanced Machine Learning

  • Implemented and trained conditional and unconditional DDPMs with UNet, experimenting with linear/cosine/quadratic schedules and achieved KL = 0.30, EMD = 9.65 on 32k-sample Albatross dataset
  • Applied Classifier-Free Guidance and used conditional DDPM as a classifier (95% on 2-class tasks)
  • Used SVDD for reward-guided sampling from unconditional DDPMs using classifier-derived reward signals

• Socket-Based Trading Engine

  Guide: Prof. Ashutosh Gupta | Course Project: Data Structures and Algorithms

  • Built trading strategies using sockets and threads to improve execution speed and market response
  • Developed a dynamic market matching engine with arbitrage detection and prevention mechanisms
  • Implemented median trading and statistical arbitrage to exploit price anomalies for steady returns