Quantitative
Developer & Researcher
Engineering ultra-low latency trading systems and alpha-generating models. Expertise in **FPGA/DPDK** infrastructure, **deterministic execution**, and statistical arbitrage strategies for high-frequency environments.
Education
Georgia Institute of Technology (Online)
Aug 2024 – Expected Dec 2026Coursework: High-Performance Computing, Distributed Computing, Database Management Systems, Bayesian Statistics.
Stevens Institute of Technology
Aug 2024 – May 2026Coursework: Market Microstructure, Quantitative Hedge Fund Strategies, Algorithmic Trading Strategies, Multivariate Statistics.
WorldQuant University
Dec 2021 – May 2024Coursework: Deep Learning for Finance, Financial Econometrics, Fixed Income, Equity, Portfolio Management, Risk Management.
Carnegie Mellon University, Tepper School of Business
Aug 2021 – Oct 2021Coursework: Investments, Statistical Machine Learning, Simulation Methods, Financial Computing, Algorithmic Optimization. (Program withdrawn due to father's illness)
Vellore Institute of Technology
Jul 2014 – Sept 2018Coursework: Data Structures and Algorithms, Computer Networks, Reinforcement Learning, Natural Language Processing (NLP).
Professional Experience
BNP Paribas CIB
Feb 2026 – Present- Developing high-performance C++ trading systems with FPGA for Automated Market Making strategies at BNP Paribas CIB.
- Collaborating with front-office to optimize latency and enhance execution performance in a hybrid on-site trading environment.
LogiNext Solutions Inc.
Mar 2023 – Jun 2025- Design and implementation of **Map Construction and Routing Algorithms** to solve complex NP-hard problems.
- Built a **Large Language Model (LLM)** for internal development and bug query resolution, reducing issue resolution time by 80%.
- Led a team of 12 to develop a high-performance **geospatial mapping application** using PostGIS, MongoDB, and AWS.
Versor Investments
Feb 2022 – Oct 2022- Developed ML-driven **Order and Execution Management Systems**, improving trade execution efficiency by 20%.
- Backtested and deployed **systematic merger arbitrage strategies**, increasing alpha capture by 15%.
- Engineered **risk-adjusted return models** for optimizing portfolio risk exposure and factor analysis.
- Managed a combined **AUM of $8.5 Billion** across merger arbitrage and stock selection portfolios.
Bank of America
Jan 2020 – Jul 2021- Engineered Python-based trading services to enhance the storage, processing, matching, and execution of trades on QUARTZ.
- Integrated C++ pipelines to store trades in the object-oriented database SANDRA, reducing trade processing latency by 50%.
- Led migration of 1 million+ lines of code to Python 3.8, enhancing system scalability and execution efficiency by 40%.
Bank of America
Jun 2018 – Dec 2019- Architected and developed an ML/AI platform to deploy predictive models, increasing decision-making accuracy by 67%.
- Designed machine learning models for data validation rules prediction, reducing close to 36 Full-Time Equivalents (FTEs).
Technical Arsenal
Quantitative Finance
Mathematics & Stats
Programming
Machine Learning
Data Engineering
Systems & DevOps
Research
AI-Integrated FPGA for Market Making in Volatile Environments
Engineering a sub-10µs trading platform with a custom-built limit order book, FPGA market data handlers, kernel bypass (DPDK), hardware timestamping, and lock-free data structures for deterministic, microsecond-level execution performance.
Dynamic Portfolio Optimization
Built a real-time portfolio optimization system using convex and non-convex optimization methods, enhancing risk-adjusted returns via adaptive asset rebalancing and multi-factor modeling, managing interest rate, FX, credit, and market risks.
Key Projects
Adaptive Volatility Regime Based Execution and Risk Framework
Developed adaptive volatility regime switch framework dynamically selecting among passive, TWAP, and aggressive strategies. Achieved 20.0% increase in Sharpe Ratio, 6.1% transaction cost reduction, and 20.1% CVaR decrease.
Statistical Arbitrage Reversal and Momentum Strategies
Designed and backtested a 120-day volume-momentum-based crypto portfolio strategy, yielding a 155.76% annualized return and 1.94 Sharpe Ratio, significantly outperforming the Bitcoin benchmark.
Awards & Certifications
Awards
- Global Recognition Gold Award (Bank of America) - Led enterprise-wide AI/ML campaign identifying 64 high-impact use cases.
- Global Recognition Silver Award (Bank of America, 2x) - For Total Return Swap Bonds contributions and AI/ML framework.
- 1st Place - Vanguard ETF Trading Challenge (Personal Portfolio), 6th Place for the team portfolio.
- State Rank Holder - International Science Olympiad & International Math Olympiad.
- President - Stevens Graduate Financial Association.
Certifications
Finance
- CFA Level 1
- Bloomberg Market Certification (BMC)
- Financial Engineering & Risk Mgmt Part I & II (Columbia)
- Investment Foundations Program (CFA Institute)
- The Complete Financial Analyst Training & Investing Course
- ML for Trading Specialization (Google Cloud/NYIF)
- Investment Management Specialization (Geneva/UBS)
- Trading Strategies in Emerging Markets (ISB)
- Finance & Quant Modeling for Analysts (Wharton)
- Corporate Finance and Valuation (NYU Stern/Damodaran)
Computer Science
Essential Reading
A curated collection of books that have influenced my trading philosophy and technical approach. From stochastic calculus to Eastern philosophy.
GitHub Impact
