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[lien] | [e-mail]

EDUCATION

STANFORD UNIVERSITY

MS IN COMPUTER SCIENCE

2023 - 2025 | GPA: 4+/4.0

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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)