Chaosheng Dong
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Chaosheng Dong, Ph.D. |
Contact
Email: chaosd@amazon.com
Web: https://chaoshengdong.github.io
Google Scholar: https://scholar.google.com/citations?user=nPratvEAAAAJ&hl=en
I am actively seeking journal review opportunities!
If you'd like to collaborate in research, please shoot an email!
Recent News
Mar 13, 2024: Our paper Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning has been accepted by NAACL 2024.
Jan 16, 2024: Our paper Scalable and Effective Implicit Graph Neural Networks on Large Graphs has been accepted by ICLR 2024.
Sep 21, 2023: Our paper Federated Multi-Objective Learning has been accepted by NeurIPS 2023.
Aug 5, 2023: Our paper G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer has been accepted by CIKM 2023 as a long paper.
May 16, 2023: Our paper Querywise Fair Learning to Rank through Multi-Objective Optimization has been accepted by KDD 2023 Research Track.
May 16, 2023: Our paper Multi-Label Learning to Rank through Multi-Objective Optimization has been accepted by KDD 2023 Applied Data Science Track.
Jan 6, 2023: Our paper Learning Risk Preferences from Investment Portfolios Using Inverse Optimization has been accepted by the special issue of AI and ML in Finance, Research in International Business and Finance.
Dec 27, 2022: Our paper Personalized Complementary Product Recommendation was ranked Top-10 most viewed publications of 2022 at Amazon.
July 7, 2022: Our paper Multi-Label Learning to Rank through Multi-Objective Optimization is available online.
May 15, 2022: Our paper A multi-objective / multi-task learning framework induced by Pareto stationarity has been accepted by ICML 2022.
Mar 4, 2022: Our paper Multi-task GNN for Substitute Identification has been accepted by the Poster and Demo Track at the the Web Conference 2022.
Jan 29, 2022: Our paper Personalized Complementary Product Recommendation has been accepted by the the Web Conference 2022.
Jan 20, 2022: Our paper Bandit Learning with Joint Effect of Incentivized Sampling, Delayed Sampling Feedback, and Self-Reinforcing User Preferences has been accepted by ICLR 2022.
May 8, 2021: Our paper Incentivized Bandit Learning with Self-Reinforcing User Preferences has been accepted by ICML 2021.
April 1, 2021: Our paper One Backward from Ten Forward, Subsampling for Large-Scale Deep Learning has been accepted by the DeMaL Workshop at WWW 2021.
Dec 10, 2020: Our paper Heterogeneous Graph Neural Networks with Neighbor-SIM Attention Mechanism for Substitute Product Recommendation has been accepted by the Workshop on Deep Learning on Graphs: Methods and Applications at AAAI 2021.
Dec 1, 2020: Our paper Wasserstein Distributionally Robust Inverse Multiobjective Optimization has been accepted by AAAI 2021.
Nov 08, 2020: Our paper Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights, and Algorithms was selected as the Runner-up in the best theoretical paper competition in 15th INFORMS Workshop on Data Mining & Decision Analytics.
Oct 13, 2020: Our paper Inverse Multiobjective Optimization Through Online Learning is available online.
Oct 05, 2020: Our paper Learning Time Varying Risk Preferences from Investment Portfolios using Inverse Optimization with Applications on Mutual Funds is available online.
Sep 30, 2020: Our paper Wasserstein Distributionally Robust Inverse Multiobjective Optimization is available online.
May 31, 2020: Our paper Expert Learning through Generalized Inverse Multiobjective Optimization: Models, Insights and Algorithms has been accepted by ICML 2020.
Dec 20, 2019: Chaosheng Dong will join Amazon as an Applied Scientist in machine learning starting from June 15, 2020.
Oct 19, 2019: Our paper Generalized Inverse Optimization through Online Learning was selected as one of the four Finalists in the best paper competition in 14th INFORMS Workshop on Data Mining & Decision Analytics.
Oct 1, 2019: Our paper Wasserstein Distributionally Robust Inverse Multiobjective Optimization has been accepted by the OTML Workshop at NeurIPS 2019.
Mar 7, 2019: Chaosheng Dong will join ByteDance as an Applied Machine Learning Intern starting from Sep 9, 2019.
Feb 18, 2019: Chaosheng Dong will join Amazon as an Applied Scientist Intern in machine learning starting from May 20, 2019.
Sep 5, 2018: Our paper Generalized Inverse Optimization through Online Learning has been accepted by NIPS 2018.
Education
Ph.D., Operations Research, University of Pittsburgh, April 2020
B.S.c., Mathematics and Applied Mathematics, University of Science and Technology of China, June 2014
Presentations and Activities
DeMaL Workshop at World Wide Web Conference (WWW 2021), April 2021
Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021
Best theoretical paper competition in 15th INFORMS Workshop on Data Mining & Decision Analytics, November 2020
Thirty-seventh International Conference on Machine Learning (ICML 2020), July 2020
OTML Workshop at NeurIPS 2019, Vancouver, Canada, December 2019
Session chair, 2019 INFORMS Annual Meeting, Seattle, October 2019
Best theoretical paper competition in 14th INFORMS Workshop on Data Mining & Decision Analytics, October 2019
Jane Street Symposium, New York, January 2019
INFORMS Computing Society Conference, Knoxville, TN, January 2019
Thirty-second Conference on Neural Information Processing Systems (NeurIPS 2018), Montreal, Canada, December 2018
2018 INFORMS Annual Meeting, Phoenix, November 2018
University of Colorado Denver, 2018 INFORMS Optimization Society Conference, March 2018
2017 INFORMS Annual Meeting, Houston, October 2017
UC Berkeley, Optimization, Statistics and Uncertainty workshop, December 2017
2016 INFORMS Annual Meeting, Nashville, November 2016
IMA, New Directions Workshop on Mathematical Optimization, August 2016
Autonomous University of Nuevo Leon, 1st International Workshop on Bilevel Programming (IWOBIP’16), Mexico, March 2016
2015 INFORMS Annual Meeting, Philadelphia, November 2015
Professional Services
Program Committee Member: KDD 2021 Research Track, SDM 2022, TheWebConf 2022 Industrial Track, KDD 2022 Research Track
Reviewer: KDD 2021, AMLC 2021, NeurIPS 2021, ICLR 2022, TheWebConf 2022, ICML 2022, KDD 2022