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ORCIDHaoran Zhang 0003
Person information
- affiliation: Massachusetts Institute of Technology, Cambridge, MA, USA
- affiliation (former): University of Toronto, Vector Institute for Artificial Intelligence, ON, Canada
Other persons with the same name
- Haoran Zhang — disambiguation page
- Haoran Zhang 0001 — Zhejiang Normal University, College of Mathematics, Physics and Information Engineering, China
- Haoran Zhang 0002
![[0000-0002-4641-0641]](https://dblp1.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-4641-0641")
— LocationMind Inc., Chiyoda-ku, Japan (and 3 more) - Ranran Haoran Zhang (aka: Haoran Zhang 0004) — Pennsylvania State University, State College, PA, USA
- Haoran Zhang 0005 — University of Pittsburgh, PA, USA
- Haoran Zhang 0006 — Harbin Institute of Technology, School of Software, China
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2020 – today
- 2024
[i13]Hyewon Jeong, Sarah Jabbour, Yuzhe Yang, Rahul Thapa, Hussein Mozannar, William Jongwon Han, Nikita Mehandru, Michael Wornow, Vladislav Lialin, Xin Liu, Alejandro Lozano, Jiacheng Zhu, Rafal Dariusz Kocielnik, Keith Harrigian, Haoran Zhang, Edward Lee, Milos Vukadinovic, Aparna Balagopalan, Vincent Jeanselme, Katherine Matton, Ilker Demirel, Jason A. Fries, Parisa Rashidi, Brett K. Beaulieu-Jones, Xuhai Orson Xu, Matthew B. A. McDermott, Tristan Naumann, Monica Agrawal, Marinka Zitnik, Berk Ustun, Edward Choi, Kristen Yeom, Gamze Gursoy, Marzyeh Ghassemi, Emma Pierson, George H. Chen, Sanjat Kanjilal, Michael Oberst, Linying Zhang, Harvineet Singh, Tom Hartvigsen, Helen Zhou, Chinasa T. Okolo:
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium. CoRR abs/2403.01628 (2024)- 2023
- [c9]Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi:
Change is Hard: A Closer Look at Subpopulation Shift. ICML 2023: 39584-39622 - [c8]Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi:
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. ICML 2023: 41550-41578 - [i12]Yuzhe Yang, Haoran Zhang, Dina Katabi, Marzyeh Ghassemi:
Change is Hard: A Closer Look at Subpopulation Shift. CoRR abs/2302.12254 (2023) - [i11]Yuzhe Yang, Haoran Zhang, Judy W. Gichoya, Dina Katabi, Marzyeh Ghassemi:
The Limits of Fair Medical Imaging AI In The Wild. CoRR abs/2312.10083 (2023) - 2022
- [j1]Ruian Shi, Haoran Zhang, Quaid Morris:
PAN-cODE: COVID-19 forecasting using conditional latent ODEs. J. Am. Medical Informatics Assoc. 29(12): 2089-2095 (2022) - [c7]Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Pfohl, Marzyeh Ghassemi:
Improving the Fairness of Chest X-ray Classifiers. CHIL 2022: 204-233 - [c6]Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi:
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. FAccT 2022: 1194-1206 - [i10]Haoran Zhang, Natalie Dullerud, Karsten Roth, Lauren Oakden-Rayner, Stephen Robert Pfohl, Marzyeh Ghassemi:
Improving the Fairness of Chest X-ray Classifiers. CoRR abs/2203.12609 (2022) - [i9]Aparna Balagopalan, Haoran Zhang, Kimia Hamidieh, Thomas Hartvigsen, Frank Rudzicz, Marzyeh Ghassemi:
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations. CoRR abs/2205.03295 (2022) - [i8]Haoran Zhang, Harvineet Singh, Marzyeh Ghassemi, Shalmali Joshi:
"Why did the Model Fail?": Attributing Model Performance Changes to Distribution Shifts. CoRR abs/2210.10769 (2022) - 2021
- [c5]Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi:
An empirical framework for domain generalization in clinical settings. CHIL 2021: 279-290 - [c4]Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi:
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CIKM 2021: 606-616 - [c3]Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi:
Learning Optimal Predictive Checklists. NeurIPS 2021: 1215-1229 - [i7]Haoran Zhang, Natalie Dullerud, Laleh Seyyed-Kalantari, Quaid Morris, Shalmali Joshi, Marzyeh Ghassemi:
An Empirical Framework for Domain Generalization in Clinical Settings. CoRR abs/2103.11163 (2021) - [i6]Imon Banerjee, Ananth Reddy Bhimireddy, John L. Burns, Leo Anthony Celi, Li-Ching Chen, Ramon Correa, Natalie Dullerud, Marzyeh Ghassemi, Shih-Cheng Huang, Po-Chih Kuo, Matthew P. Lungren, Lyle J. Palmer, Brandon J. Price, Saptarshi Purkayastha, Ayis Pyrros, Luke Oakden-Rayner, Chima Okechukwu, Laleh Seyyed-Kalantari, Hari Trivedi, Ryan Wang, Zachary Zaiman, Haoran Zhang, Judy W. Gichoya:
Reading Race: AI Recognises Patient's Racial Identity In Medical Images. CoRR abs/2107.10356 (2021) - [i5]Stephen R. Pfohl, Haoran Zhang, Yizhe Xu, Agata Foryciarz, Marzyeh Ghassemi, Nigam H. Shah:
A comparison of approaches to improve worst-case predictive model performance over patient subpopulations. CoRR abs/2108.12250 (2021) - [i4]Sindhu C. M. Gowda, Shalmali Joshi, Haoran Zhang, Marzyeh Ghassemi:
Pulling Up by the Causal Bootstraps: Causal Data Augmentation for Pre-training Debiasing. CoRR abs/2108.12510 (2021) - [i3]Haoran Zhang, Quaid Morris, Berk Ustun, Marzyeh Ghassemi:
Learning Optimal Predictive Checklists. CoRR abs/2112.01020 (2021) - 2020
- [c2]Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi:
Hurtful words: quantifying biases in clinical contextual word embeddings. CHIL 2020: 110-120 - [c1]Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi:
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. ML4H@NeurIPS 2020: 139-160 - [i2]Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi:
Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings. CoRR abs/2003.11515 (2020) - [i1]Taylor W. Killian, Haoran Zhang, Jayakumar Subramanian, Mehdi Fatemi, Marzyeh Ghassemi:
An Empirical Study of Representation Learning for Reinforcement Learning in Healthcare. CoRR abs/2011.11235 (2020)
Coauthor Index
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