I am a first-year ELLIS PhD student at the Probabilistic Machine Learning Group at Aalto University and ELLIS Unit Helsinki, where I am profoundly privileged to be under the mentorship of Professor Samuel Kaski. Under ELLIS, I am also fortunate to have Doctor Mingfei Sun at the University of Manchester as my co-supervisor. My PhD research focuses on computational rationality in AI-assisted decision making.
Previously, I was a thesis worker and research assistant at the Computational Behavior Lab in Aalto under the splendid supervision of Professor Antti Oulasvirta and Doctor Suyog Chandramouli, where I received invaluable guidance towards research in Human-Computer Interaction. During this experience, I was lucky enough to finally discover my passion in Interactive AI and Human-AI Collaboration after 5 years of exploration and exploitation. I obtained my Master’s degree with honors in Computer Science from Aalto University. During my undergraduate studies in Computer Science at Nanjing University of Aeronautics and Astronautics, I am grateful for the invaluable academic guidance received from Professor Kun Zhu. I was also a nominated visiting student to the University of Edinburgh, School of Informatics, where I initially discovered my deep interests in Machine Learning.
D.Phil. in Artificial Intelligence, Ongoing
Aalto University
M.Sc. in Computer Science, 2023
Aalto University
Visiting Student, 2019
University of Edinburgh, School of Informatics
B.Eng. in Computer Science, 2021
Nanjing University of Aeronautics and Astronautics
Main Work:
MCM 2020-Meritorious Winner
Given three products’ data of reviews and ratings, we utilized NLP, SVM, ARMA, Elastic Net Regression and developed influence factor model, TOPSIS model to identify their key patterns and measures. Then, we provided appropriate online sales strategy and design features for the Marketing Director.
Second Year - SRTP
By studying intellectual perception incentive mechanism and adopting USRP, we are able to collect data of network quality and then use the matrix filling recovery algorithm to construct network quality real-time visualization map,so that we could predict network quality and analyze network fault based on AI.
First Year - SRTP
By adopting crowdsourcing and crowd-sensing, we monitor the extreme driving behavior during the process of driving, trying to reduce the probability of traffic accidents.