I am a Ph.D. candidate at University of Grenoble Alpes supervised by Jérôme Malick, Franck Iutzeler, and Panayotis Mertikopoulos. My Ph.D. research centers around the mathematical aspects of decision-making in multi-agent systems, touching upon especially problems in online learning, distributed optimization, and learning in games. Apart from this, I am broadly interested in various topics in artificial intelligence, with notably a focus on generative models and efficient fine-tuning at the moment (check our LyCORIS project for parameter efficient fine-tuning of Stable Diffusion).
Before my Ph.D., I studied computer science at ENS Paris and got a double degree MSc from the CS department of ENS Paris and the Mathematics department of ENS Paris-Saclay. I am serving as a reviewer for ICML, NeurIPS, ICLR, and several optimization and machine learning journals.
Contact: cyberhsieh212 AT gmail DOT com
I was born in Taiwan, this beautiful island on which both western democracy and eastern lifestyle can be found. Yes, that is surprisingly rare. Moreover, Taiwan is also considered as one of the best places for expats living abroad and is the first in Asia that legalizes same-sex marriage. I am proud of being Taiwanese.
My passion for mathematics was already developed in my childhood. From 12 to 18 years old, I actively participated in math competitions and spent a lot of time on Olympiad type questions. Especially, during my second year of high school, I was so fortunate to become one of the six contestants representing Taiwan in IMO 2013 after passing multiple stages of selection.
The randomness of life brought me to France after I graduated from high school. I got this opportunity thanks to the CPGE Taiwan program which recruit Taiwanese students to study in French classe prepa through a maths exam. After 6 months of intensive French course in Taiwan, in July 2014, I embarked on the journey and started my study abroad life in France.
After two years of hard work. I was admitted to ENS Paris, being ranked 1bis of the computer science group in the entrance exam (bis as I am not French). Only during the first and half years we actually followed courses on the campus of ENS. Besides math and computer science, I also attended several cognitive science courses (which granted me a minor in cognitive science).
As a fan of Japanese Culture, I decided to go to Japan for my first-year master’s internship. Thanks to my kind internship advisors (Masashi Sugiyama and Gang Niu) and co-workers, this internship marked the beginning of my research career. My work centered around weakly-supervised learning and my first paper was written. I also enjoyed very much the time off from work. I benefited from these five months so much that I dare say that it was probably my greatest turning point after my arrival in France.
For my second year of master, I studied Mathematics, Vision, and Learning in ENS Paris-Saclay. I then came to Grenoble for the internship, before starting my Ph.D. with my current advisors in this “Capital of the Alps”.
To acquire industrial experience, I did a four-month applied science internship at Amazon in the third year of my Ph.D. During this internship, I had the great honor to work with my internship manager Shiva Kasiviswanathan and Principal Scientist Branislav Kveton on a stochastic bandit model (see this paper). Additionally, being part of the Causality team, led by Dominik Janzing and Yasser Jadidi, allowed me to gain an understanding of the basics of causality. Finally, the internship provided me with valuable experience in remote collaboration, as well as an enjoyable experience living in the beautiful medieval city of Tübingen, surrounded by nature.
I was fortunate to get a return internship at Amazon in the same team but at a different location. Impressed by the performance and flexibility of score-based diffusion models, I decided to investigate how it can be incorporated as prior in multi-armed bandit problems. This internship was thus an occasion for me to conduct a quite different type of research, in which algorithms and experiments prevail theory. I also enjoyed the four months in the Bay Area, where I got the opportunity to meet many old friends and gained new insignts into my future career.
After four years of hard work, the Ph.D. defense marked an import milestone of my academic journey. My Ph.D. Thesis deals with mathematical frameworks and algorithms for decision-making in multi-agent systems, making use of tools from online learning, game theory, and stochastic optimization. The four years also came with many great experiences, including workshops in Luminy, Les Houches, Singapore, and a lot more. I am deeply grateful for my Ph.D. advisors for their support and guidance along these years.