Hello, my name is Haoxiang (Steven) Yu (于浩翔). I’m currently a Ph.D. Student at the University of Texas at Austin, where I work under the guidance of Dr. Christine Julien. My research is in the field of pervasive/ubiquitous computing & Machine Learning.
My research is focus on the collaboration between machine learning models, the interaction between models and the environment, and the synergy between models and humans. On the application front, my work pertains to distributed learning, blockchain, IoT/V, and human activity recognition.
Prior to joining academia, I honed my skills in the tech industry as one of the leading researcher for a startup company. There, I applied my expertise in computer and data science towards medical Natural Language Processing (NLP) and personalized risk assessment.
In addition to my core research and professional work, I’ve delved into research related to quantitative trading. I consider “real” quantitative trading strategies can be divided into two categories: automating existing trading strategies and using computers to analyze extensive data sets beyond human capability. I believe that a good quantitative trader can find alpha by using both directions.
Outside of my research pursuits, I enjoy cooking , baking , and participating in outdoor activities . While I haven’t had the opportunity to travel extensively, I’ve experimented with creating diverse dishes from around the globe.
Here’s an intriguing fact about me: I almost never play any video games.
Thank you for taking the time to get to know me better. If you want to connect, please don’t hesitate to reach out!
(It’s challenging to keep my CV up to date on this website. If you’d like a new one, please send me an email.)
|Jun 18, 2022||One Papers Accepted at IEEE Transactions on Artificial Intelligence|
|Jan 5, 2022||Two Papers Accepted at Percom 2022 (Workshop and Demo)|
|Nov 11, 2021||Win [Best Student Paper Award] at Mobiquitous|
|Aug 25, 2021||Join The University of Texas at Austin as a Ph.D. Student|
|May 15, 2021||Graduated from M.S. in Computer Science, Miami University|