I am a second-year PhD student in computer science at the University of Toronto, supervised by Prof. Chris Maddison and Prof. Nicolas Papernot. I am interested in broad areas of deep learning. My previous works focus on learning representations that can reason complex tasks and that are trustworthy for humans. Beforehand, I completed my MMath and BMath in computer science at the University of Waterloo, supervised by Prof. Pascal Poupart.
* below indicates equal contribution
Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models
Haonan Duan*, Adam Dziedzic*, Nicolas Papernot, Franziska Boenisch
Conference on Neural Information Processing Systems (NeurIPS), 2023.
Dataset Inference for Self-Supervised Models
Adam Dziedzic*, Haonan Duan*, Muhammad Ahmad Kaleem*, Nikita Dhawan, Jonas Guan, Yannis Cattan, Franziska Boenisch, Nicolas Papernot
Conference on Neural Information Processing Systems (NeurIPS), 2022.
Augment with Care: Contrastive Learning for Combinatorial Problems
Haonan Duan*, Pashootan Vaezipoor*, Max B. Paulus, Yangjun Ruan, Chris J. Maddison
International Conference on Machine Learning (ICML), 2022.
Distributional Reinforcement Learning with Monotonic Splines
Yudong Luo, Guiliang Liu, Haonan Duan, Oliver Schulte, Pascal Poupart
International Conference on Learning Representations (ICLR), 2022
Multiple Moment Matching Inference: A Flexible Approximate Inference Algorithm
Haonan Duan, Pascal Poupart
ICML 2021 Workshop on Uncertainty & Robustness in Deep Learning
Online Bayesian Moment Matching based SAT Solver Heuristics
Haonan Duan*, Saeed Nejati*, George Trimponias, Pascal Poupart and Vijay Ganesh
International Conference on Machine Learning (ICML), 2020.
Discriminative Training of Feed-Forward and Recurrent Sum-Product Networks by Extended Baum-Welch
Haonan Duan, Abdullah Rashwan, Pascal Poupart and Zhitang Chen
International Journal of Approximate Reasoning (IJAR), Volume 124, September 2020, Pages 66-81
Conference reviewer: ICLR (2020-2023), ICML(2021-2023), NeurIPS(2021-2023), AISTATS(2022)
Software Engineer Intern @
Jan. 2021 - Apr. 2021
Data Scientist Intern @
May. 2020 - Aug. 2021
Selected Honors & Awards
I am grateful for the organizations and people below to support my study and research: