Scholar

Xing Han (Aaron)

Google Scholar ID: Vejou24AAAAJ

Johns Hopkins University

Machine LearningMultimodalHealth AI

Citations & Impact

All-time

Citations

429

H-index

i10-index

Publications

Co-authors

list available

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Publications

20 items

Browse publications on Google Scholar (top-right) ↗

Resume (English only)

Academic Achievements

Papers accepted to NeurIPS 2023, ICML 2022, AISTATS 2021, and one paper accepted as a spotlight presentation at NeurIPS 2020. Conference reviewer for ICML 2021-2023, NeurIPS 2020-2023, ICLR 2020-2024, AISTATS 2021-2024, ICASSP 2024, ML4H 2023. Journal reviewer for Pattern Recognition.

Research Experience

Currently a Postdoctoral Fellow at the Department of Computer Science, Johns Hopkins University, working with Prof. Suchi Saria. Previously, a Research Intern at Google, Intuit AI, R&D Intern at Salesforce, and Applied Scientist Intern at CognitiveScale.

Education

Ph.D. from the University of Texas at Austin, advised by Prof. Joydeep Ghosh; B.S. in Electronics and Electrical Engineering from The University of Edinburgh.

Background

Broadly interested in developing principles and practice of trustworthy machine learning. Specifically focused on uncertainty quantification, robustness (defense against adversarial attacks, data poisoning, and distribution drift), interpretability (especially for non-i.i.d. data like time series or sequential data), and enhancing the predictive power of deep learning models in clinical contexts.

Miscellany