[nom]
[lien] | [e-mail]
EDUCATION
STANFORD UNIVERSITY
MS IN COMPUTER SCIENCE
2023 - 2025 | GPA: 4+/4.0
[nom]
NATIONAL UNIVERSITY OF SINGAPORE
BCOMP IN COMPUTER SCIENCE
2017 - 2021 | GPA: 4.8/5.0
Turing Programme
Minor in Mathematics
COURSEWORK
Design and Analysis of Algorithms
Randomized Algorithms
Advanced Algorithms
Machine Learning
NLP with Deep Learning
Parallel Computing
Computer Networks
Operating System
Quantum Computing
Convex Optimization
Probabilistic Methods
Statistics
Advanced Linear Algebra
Game Theory
TA
Mining Massive Datasets †
Modern Algorithmic Toolbox †
Parallel & Distributed Algorithms ∗
Design & Analysis of Algorithms ∗
Data Structures & Algorithms ∗
† At Stanford
∗ At NUS
SKILLS
Programming Languages
Experienced:
•Modern C++ •Python •Ocaml
Familiar:
•Java •SQL •Solidity
•Javascript •Q
Tools and Frameworks:
•Numpy •Pandas •Scikit-learn
•Cuda •Kafka •Git •Vim •Bash
LINKS
LinkedIn : [lien] [nom]
Github : [lien] [nom]
DevPost:// [nom]
Codeforces:// [nom]
EXPERIENCES
TOWER RESEARCH CAPITAL | QUANT TRADER
June 2025 - Present | New York City
- Limestone Pod - Core Machine Learning (CML) Team
- As part of CML team, researched and developed novel modeling techniques (linear and non-linear) to improve overall strength of alpha across datasets on varying time-horizons spanning across asset classes.
TOWER RESEARCH CAPITAL | QUANT TRADING INTERN
June 2024 - August 2024 | New York City
- Improved correlation with the target by 11% (relative) over existing predictions in future markets (intra-day frequency) by integrating market conditions into an attention-based neural network.
- Resolved auto-correlation issues in market data sampling, increasing the entropy of sub-sampled training data.
CITADEL SECURITIES | DEV FULL TIME
August 2021 - June 2023 | London, New York City
- Built a real-time reconciliation service in C++ to process 100M+ daily orders, using lock-less data structures for parallelism and throughput.
- As part of options team, implemented the end-to-end pipeline for (i) absorbing speculated corporate actions from external third party sources, (ii) normalizing them and (iii) feeding them into trading strategies.
DRW | DEV INTERN
May 2020 - August 2020 | Singapore
- Developed tooling to compress market data received from the exchange.
- Engineered the command line feature conda compare in the open-source environment manager Conda, to enhance the daily workflow of researchers.
JANE STREET CAPITAL | DEV INTERN
May 2019 - August 2019 | Hong Kong
- Contributed to multiple projects in post trade and trading system teams.
- Worked extensively with Ocaml, a functional programming language.
RESEARCH
ALGORITHMIC MARKET DESIGN | STANFORD IMPACT LAB
March 2024 - March 2025 | Prof. Itai Ashlagi and Prof. Irene Lo
- Improved the existing multinomial-logit models (via feature engineering) to forecast student preferences for public school allocation in San Francisco.
- Simulated varying policy designs with trade-offs across metrics for distance, choice and diversity, and presented findings to SFUSD.
1-BIT COMPRESSED SENSING | NUS FINAL YEAR THESIS
April 2020 - Jan 2022 | Prof Arnab Bhattacharya
- Established a lower bound (tight up to logarithmic factor) for 1-bit compressed sensing in a specific setting.
- Published in IEEE ISIT 2022 and slides at [lien]
ACHIEVEMENTS
2020 · 22 · ACM-ICPC WORLD FINALIST (INVITATIONAL)
2019 · TOP 5% · DEAN'S LIST FOR FALL'19
2019 1 ST · ACM-ICPC KAULA LUMPUR REGIONAL CONTEST
2019 62 ND · ACM-ICPC WORLD FINALIST
2018 1 ST · ACM-ICPC YANGON REGIONAL CONTEST
2017 · BRONZE · INTERNATIONAL OLYMPIAD IN INFORMATICS (IOI)
