Tianyu Wu

Upcoming Data Scientist, Master Student at Northwestern University

tianyuwu2024[at]northwestern[dot]edu

[CV]

About Me

I am a master student at Machine Learning and Data Science Program, Northwestern University (MLDS). I graduated with Latin honors from Duke Kunshan University in May 2023.

My career interest lies in growing into an interdisciplinatry data scientist and quantitative analyst.

Highlights

[Feb 2023] I got accepted from Northwestern's MLDS program, and decided to study there for the next 15 months, even though making a hard choice to decline offers from CMU, Oxford, ETH Zürich, and among others.
[Dec 2022] My co-authored paper Attitudes toward the Uptake of HPV Vaccine on Social Media in China: A Geospatial Analysis has just been accepted at the Consortium of Universities for Global Health (CUGH 2023), Washington DC, the United States, April 14-16.
[Aug 2022] I made an online oral presentation on behalf of my co-authored paper at the 5th IEEE International Conference on Blockchain, Espoo, Finland.
[Jun 2022] I was nominated as UN 🇺🇳 Millennium Fellow, DKU Campus Director. Check out the deliverable here!
[May 2022] I served as the Research Fellow of the project Understand Waiting Time in Ethereum Transaction Fee Mechanism, supported by Ethereum Academic Grants.
[Mar 2022] I was appointed as the member of Quant Department, Hedge Fund Association (HFA) headquartered at Peking University.
[Dec 2021] My start-up Mini Gap College received the grants from DKU Innovation Incubator (Dii).
[Sep 2021] I won National and Global Champion at the GE Lean Global Challenge.
[Aug 2021] Ich habe mit Herrn Tebbe angefangen, Deutsch zu lernen.
[May 2021] I was appointed as the interim Chair of Human Resources at SciEcon CIC, an Non-Profit Organization registered at the United Kingdom.
[Nov 2020] I received National Scholarship, first-ever recipient in DKU history.
[Oct 2020] I shared my story of dedicating myself to become a global citizen at DKU.
[Apr 2020] I was awarded as Honorable Mention of Mathematical Contest in Modeling (MCM).
[Aug 2019] I received full Merit-based Scholarship from the Kunshan Government.

Featured Projects

Understand Waiting Time in Ethereum Transaction Fee Mechanism

Fan Z., Luyao Z., Tianyu W. (Research Fellow)

We combine the techniques of Reinforcement Learning (RL) and batch auction to extend current theoretical framework of Transaction Fee Mechanism that can model the effect of policy change on the waiting time. Then with a hybrid approach combining the RL model and empirical data, we figure out the optimal policy based on the blockchain state.

[Grant Announcement]

How FinTech Empowers Asset Valuation: Theory and Applications

Luyao Z., Tianyu W. (1st Co-author), Saad L., Carlos-Gustavo S., Jiayi L.

We propose a generally applicable pipeline for designing, programming, and evaluating the algorithmic trading of stock and crypto assets. Moreover, we demonstrate how our data science pipeline works with respect to four conventional algorithms: the moving average crossover, volume-weighted average price, sentiment analysis, and statistical arbitrage algorithms.

[Publication][Presentation]

Pricing Model for Snowball Options

Tianyu W., Qi Z.

I apply Monte Carlo Simulation and Finite-difference PDE Methods separately to implement pricing models for the snowball options, with CSI Smallcap 500 Index as the target.

→ See Full List of Projects