Degree:
M.A. in Applied Mathematics and Computational Science
Graduation: Dec 2025
Degrees:
B.S. in Applied Mathematics and Computational Science (DKU)
B.A. in Interdisciplinary Studies: Applied Mathematics (Duke)
Graduation: May 2024
Shanghai Primequant Asset Management Co., Ltd.
Quantitative Researcher Intern
May 2024 – Aug 2024, Shanghai, China
-Led event-driven/NLP alpha research for A-share equities; delivered an end-to-end pipeline from data ingestion to backtesting.
-Built a news & exchange-announcement sentiment pipeline (Python, pandas, scikit-learn/PyTorch) with ticker-day feature alignment, timestamp lag control, deduplication, and leakage checks; stored features in SQL for reuse.
-Conducted ablation studies on headline/body, event types (earnings, buybacks, pledges, M&A, management changes) and sentiment models; achieved average daily IC of 0.010-0.015 on large-/mid-cap universe in 2018-2024 backtests with realistic costs.
-Integrated the event signal as an overlay to the desk’s multifactor baseline, improving portfolio Information Ratio by +0.15 and annual return by +1.2% at comparable volatility (backtest); turnover and capacity analyzed under live constraints.
-Supported a 4-week paper-trading pilot: gross daily Sharpe ~1.0, hit rate 53%, max drawdown 2.3%; produced handover docs and research memos adopted by the PM for further validation.
Shanghai Pinestone Asset Management Co., Ltd.
Quantitative Trader Intern
May 2023 – Jul 2023, Suzhou, China
-Executed and monitored daily trades for equity long/short portfolios via broker EMS; handled stock lending/short borrow, cash/stock settlement (T+1), corporate actions, and exception handling under PB risk limits.
-Built reconciliation scripts (Python/SQL) to match OMS fills with broker/PB statements; reduced end-of-day close time by ~60% and eliminated recurring breaks through auto-flagging and audit trails.
-Helped stabilize auto-trading scripts and broker APIs (order throttling, retry/backoff, heartbeat/resubscription); decreased reject/cancel ratio and improved average order acknowledgement latency by ~30 ms.
-Collaborated with the quant to tune the portfolio optimizer (exposure/turnover constraints, borrow utilization); cut realized turnover by ~8% with negligible impact on factor exposure and risk targets.
-Designed lightweight real-time monitors (positions, borrow utilization, price/size checks) and on-call playbooks; resolved incidents (duplicate orders, partial fills, trade breaks) with brokers and operations before end-of-day cutoffs.
