Jiacheng Zhu

Postdoc Associate

Computer Science and Artificial Intelligence Laboratory (CSAIL)

Massachusetts Institute of Technology

zjc [AT] mit.edu

[CV]

About

I am currently a postdoc at MIT CSAIL, working with Justin Solomon and Marzyeh Ghassemi. I obtaiend my Ph.D. from Carnegie Mellon Univeristy, as well as an M.S. in Machine Learning. I am fourtunate to have Prof. Long Nguyen to be my academia advisor, and I work closely with Prof. Bo Li. My research has been supported by the Qualcomm Innovation Fellowship (QIF 2022). I have worked as a research intern at Apple AI/ML and AT&T Labs. Previously, I received my bachelor's in Computational Mechanics and a minor in Data Science from Fudan University.

My research focuses on developing generalizable machine learning methods, to ensure AI/ML in healthcare are trustworthy and can benefit large and diverse populations equitably. I extract insights from Bayesian statistics, probabilistic modeling, and particularly optimal transport, to investigate the underlying geometric structures within both data and models. Recently, my studies have pivoted towards exploring self-supervised learning and fine-tuning approaches for foundational models

News

Publications

Most recent publications on Google Scholar.

Asymmetry in Low-Rank Adapters of Foundation Models

Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon

ICML 2024: International Conference on Machine Learning. 2024

Functional optimal transport: map estimation and domain adaptation for functional data

Jiacheng Zhu*, Aritra Guha*, Dat Do*, Mengdi Xu, XuanLong Nguyen, Ding Zhao.

Under review by JMLR: Journal of Machine Learning Research

Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics

Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, XuanLong Nguyen, Bo Li, Ding Zhao

ICML 2023: International Conference on Machine Learning. 2023

Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation

Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Ding Zhao

NeurIPS 2022: Conference on Neural Information Processing Systems, 2022

GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Cardiovascular Prediction

Jiacheng Zhu*, Jielin Qiu*, Zhuolin Yang, Douglas Weber, Michael Rosenberg, Emerson Liu, Bo Li, Ding Zhao.

MLHC 2022: Machine Learnign for Healthcare, 2022

Earlier version at ICLR 2022 Workshop on Socially Responsible Machine Learning .

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, Xuanlong Nguyen, Shirley Ren

CHIL 2022: Conference on Health, Inference, and Learning, 2022

Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes

Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao

NeurIPS 2020: Conference on Neural Information Processing Systems, 2020

Asymmetry in Low-Rank Adapters of Foundation Models

Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon

ICML 2024: International Conference on Machine Learning. 2024

Functional optimal transport: map estimation and domain adaptation for functional data

Jiacheng Zhu*, Aritra Guha*, Dat Do*, Mengdi Xu, XuanLong Nguyen, Ding Zhao.

Under review by JMLR: Journal of Machine Learning Research

Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report

Jielin Qiu*, Jiacheng Zhu*, Shiqi Liu, William Han, Jingqi Zhang, Chaojing Duan, Michael A. Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao.

ML4H 2023: Machine Learnign for Health, 2023

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning

Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao

NeurIPS 2023: Conference on Neural Information Processing Systems, 2023

Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics

Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, XuanLong Nguyen, Bo Li, Ding Zhao

ICML 2023: International Conference on Machine Learning. 2023

Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation

Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Ding Zhao

NeurIPS 2022: Conference on Neural Information Processing Systems, 2022

GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Cardiovascular Prediction

Jiacheng Zhu*, Jielin Qiu*, Zhuolin Yang, Douglas Weber, Michael Rosenberg, Emerson Liu, Bo Li, Ding Zhao.

MLHC 2022: Machine Learnign for Healthcare, 2022

Earlier version at ICLR 2022 Workshop on Socially Responsible Machine Learning .

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, Xuanlong Nguyen, Shirley Ren

CHIL 2022: Conference on Health, Inference, and Learning, 2022

Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes

Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao

NeurIPS 2020: Conference on Neural Information Processing Systems, 2020

Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report

Jielin Qiu*, Jiacheng Zhu*, Shiqi Liu, William Han, Jingqi Zhang, Chaojing Duan, Michael A. Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao.

ML4H 2023: Machine Learnign for Health, 2023

Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation

Jielin Qiu*, Jiacheng Zhu*, Mengdi Xu, Peide Huang, Michael Rosenberg, Douglas Weber, Emerson Liu, Ding Zhao

ICASSP 2023: IEEE International Conference on Acoustics, Speech and Signal Processing 2023

Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models?

Jielin Qiu*, William Han*, Jiacheng Zhu, Mengdi Xu, Michael Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao

EACL 2023 Findings: Findings of the Association for Computational Linguistics, 2023

GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Cardiovascular Prediction

Jiacheng Zhu*, Jielin Qiu*, Zhuolin Yang, Douglas Weber, Michael Rosenberg, Emerson Liu, Bo Li, Ding Zhao.

MLHC 2022: Machine Learnign for Healthcare, 2022

Earlier version at ICLR 2022 Workshop on Socially Responsible Machine Learning .

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, Xuanlong Nguyen, Shirley Ren

CHIL 2022: Conference on Health, Inference, and Learning, 2022

Re-vibe: vibration-based indoor person re-identification through cross-structure optimal transport

Yiwen Dong, Jiacheng Zhu, Hae Young Noh

BuildSys 2022: The 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, 2022

Goats: Goal sampling adaptation for scooping with curriculum reinforcement learning

Yaru Niu, Shiyu Jin, Zeqing Zhang, Jiacheng Zhu, Ding Zhao, Liangjun Zhang

IROS 2023: International Conference on Intelligent Robots and Systems , 2023

Robustness Certification of Visual Perception Models via Camera Motion Smoothing

Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao

CoRL 2022: Conference on Robot Learning, 2022

Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling

Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao

IROS 2022, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Spatiotemporal learning of multivehicle interaction patterns in lane-change scenarios

Chengyuan Zhang, Jiacheng Zhu, Wenshuo Wang, Junqiang Xi

IEEE Transactions on Intelligent Transportation Systems, 2021

Context-aware safe reinforcement learning for non-stationary environments

Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Liang Li, Ding Zhao

ICRA 2021, IEEE International Conference on Robotics and Automation, 2021

A tempt to unify heterogeneous driving databases using traffic primitives

Jiacheng Zhu, Wenshuo Wang, Ding Zhao

ITSC 2018, 21st International Conference on Intelligent Transportation Systems, 2018

Asymmetry in Low-Rank Adapters of Foundation Models

Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi, Haitz Sáez de Ocáriz Borde, Rickard Brüel Gabrielsson, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Justin Solomon

ICML 2024: International Conference on Machine Learning. 2024

Functional optimal transport: map estimation and domain adaptation for functional data

Jiacheng Zhu*, Aritra Guha*, Dat Do*, Mengdi Xu, XuanLong Nguyen, Ding Zhao.

Under review by JMLR: Journal of Machine Learning Research, 2023

Automated Cardiovascular Record Retrieval by Multimodal Learning between Electrocardiogram and Clinical Report

Jielin Qiu*, Jiacheng Zhu*, Shiqi Liu, William Han, Jingqi Zhang, Chaojing Duan, Michael A. Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao.

ML4H 2023: Machine Learnign for Health, 2023

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning

Yihang Yao, Zuxin Liu, Zhepeng Cen, Jiacheng Zhu, Wenhao Yu, Tingnan Zhang, Ding Zhao

NeurIPS 2023: Conference on Neural Information Processing Systems, 2023

Goats: Goal sampling adaptation for scooping with curriculum reinforcement learning

Yaru Niu, Shiyu Jin, Zeqing Zhang, Jiacheng Zhu, Ding Zhao, Liangjun Zhang

IROS 2023: International Conference on Intelligent Robots and Systems , 2023

SCCS: Semantics-Consistent Cross-domain Summarization via Optimal Transport Alignment

Jielin Qiu, Jiacheng Zhu, Mengdi Xu, Franck Dernoncourt, Trung Bui, Zhaowen Wang, Bo Li, Ding Zhao, Hailin Jin

ACL 2023: Findings of the Association for Computational Linguistics

Cardiac Disease Diagnosis on Imbalanced Electrocardiography Data Through Optimal Transport Augmentation

Jielin Qiu*, Jiacheng Zhu*, Mengdi Xu, Peide Huang, Michael Rosenberg, Douglas Weber, Emerson Liu, Ding Zhao

ICASSP 2023: IEEE International Conference on Acoustics, Speech and Signal Processing 2023

Interpolation for Robust Learning: Data Augmentation on Wasserstein Geodesics

Jiacheng Zhu, Jielin Qiu, Aritra Guha, Zhuolin Yang, XuanLong Nguyen, Bo Li, Ding Zhao

ICML 2023: International Conference on Machine Learning. 2023

Transfer Knowledge from Natural Language to Electrocardiography: Can We Detect Cardiovascular Disease Through Language Models?

Jielin Qiu*, William Han*, Jiacheng Zhu, Mengdi Xu, Michael Rosenberg, Emerson Liu, Douglas Weber, Ding Zhao

EACL 2023 Findings: Findings of the Association for Computational Linguistics, 2023

Curriculum Reinforcement Learning using Optimal Transport via Gradual Domain Adaptation

Peide Huang, Mengdi Xu, Jiacheng Zhu, Laixi Shi, Ding Zhao

NeurIPS 2022: Conference on Neural Information Processing Systems, 2022

GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Cardiovascular Prediction

Jiacheng Zhu*, Jielin Qiu*, Zhuolin Yang, Douglas Weber, Michael Rosenberg, Emerson Liu, Bo Li, Ding Zhao.

MLHC 2022: Machine Learnign for Healthcare, 2022

Earlier version at ICLR 2022 Workshop on Socially Responsible Machine Learning .

PhysioMTL: Personalizing Physiological Patterns using Optimal Transport Multi-Task Regression

Jiacheng Zhu, Gregory Darnell, Agni Kumar, Ding Zhao, Bo Li, Xuanlong Nguyen, Shirley Ren

CHIL 2022: Conference on Health, Inference, and Learning, 2022

Robustness Certification of Visual Perception Models via Camera Motion Smoothing

Hanjiang Hu, Zuxin Liu, Linyi Li, Jiacheng Zhu, Ding Zhao

CoRL 2022: Conference on Robot Learning, 2022

Re-vibe: vibration-based indoor person re-identification through cross-structure optimal transport

Yiwen Dong, Jiacheng Zhu, Hae Young Noh

BuildSys 2022: The 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, 2022

Scalable Safety-Critical Policy Evaluation with Accelerated Rare Event Sampling

Mengdi Xu, Peide Huang, Fengpei Li, Jiacheng Zhu, Xuewei Qi, Kentaro Oguchi, Zhiyuan Huang, Henry Lam, Ding Zhao

IROS 2022, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Spatiotemporal learning of multivehicle interaction patterns in lane-change scenarios

Chengyuan Zhang, Jiacheng Zhu, Wenshuo Wang, Junqiang Xi

IEEE Transactions on Intelligent Transportation Systems, 2021

Context-aware safe reinforcement learning for non-stationary environments

Baiming Chen, Zuxin Liu, Jiacheng Zhu, Mengdi Xu, Wenhao Ding, Liang Li, Ding Zhao

ICRA 2021, IEEE International Conference on Robotics and Automation, 2021

Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes

Mengdi Xu, Wenhao Ding, Jiacheng Zhu, Zuxin Liu, Baiming Chen, Ding Zhao

NeurIPS 2020: Conference on Neural Information Processing Systems, 2020

Recurrent Attentive Neural Process for Sequential Data

Shenghao Qin*, Jiacheng Zhu*, Jimmy Qin, Wenshuo Wang, Ding Zhao

NeurIPS 2019, Workshop on Learning with Rich Experience, 2019

A tempt to unify heterogeneous driving databases using traffic primitives

Jiacheng Zhu, Wenshuo Wang, Ding Zhao

ITSC 2018, 21st International Conference on Intelligent Transportation Systems, 2018

Professional Service

Organizer
  • NeurIPS 2024 LLM Merging Competition
  • Conference on Health, Inference, and Learning (CHIL) 2024
  • Round Table Chiar of Machine Learning for Health 2023
  • Reviewer mentorship program of Machine Learning for Health 2023
  • ICRA 2023 Season Depth Challenge
Conference Reviewer

NeurIPS / ICLR / ICML / AISTATS(Top reviewer 2023) / AAAI / CHIL / MLHC / ML4H

Journal Reviewer

TPAMI / TMLR / RA-L / IEEE T-ITS / IEEE T-IV

Acknowledgement

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