Haocheng Dai

Applied Scientist-LLM / Ph.D. candidate

haocheng.dai@utah.edu

Vitae / GitHub / YouTube / Flickr / Instagram

I am an applied scientist at Amazon Science working on Rufus, the next generation GenAI-powered conversational shopping assistant. I am also a Ph.D. candidate in computer science, advised by Dr. Sarang Joshi with both SCI Institute and Kahlert School of Computing, 🏜️ University of Utah β€” the birthplace of computer graphics 🐰 and world's first packet-switched network (ARPANET) 🌐. I also work closely with researchers from FSU, UCLA, UVa, and Yale. I was an applied scientist intern at Amazon, focusing on 🎨 diffusion models for text inpainting (2023 summer) and πŸ“‹ multimodal transformers for document understanding (2022 summer).

Before I joined the U, I received my B.Eng. in computer science from Tongji University and have studied at ✑️ Israel Institute of Technology and πŸ₯ Institut de MathΓ©matiques de Toulouse as an exchange student, focusing on image analysis and Riemannian geometry, respectively.

My interest lies in developing specialized and trustworthy machine learning tools tailored for computer vision problems in πŸ§‘β€βš•οΈ healthcare settings, so as to improve medical treatment, diagnosis and understanding of the disease. My research extends to, but is not limited to:

πŸ‘¨β€βš–οΈ trustworthy machine learning (fairness and robustness);
πŸ“ geometric deep learning and shape modeling;
πŸ‘οΈ multimodal learning and vision language models;
πŸ”­ physics-informed machine learning.



Publications & Preprints


Refining Skewed Perceptions in Vision-Language Models through Visual Representations.
  • Haocheng Dai, Sarang Joshi.
  • Preprint, 2024
  • πŸ‘¨β€βš–οΈπŸ‘οΈ / Paper / Code /Citation

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High-Fidelity CT on Rails-Based Characterization of Delivered Dose Variation in Conformal Head and Neck Treatments.
  • Haocheng Dai, Vikren Sarkar, Christian Dial, Markus Foote, Ying Hitchcock, Sarang Joshi, Bill Salter.
  • Applied Radiation Oncology (ARO), 2023
  • πŸ‘¨β€βš–οΈπŸ§‘β€βš•οΈ / Paper / Code / Slides / Citation

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Detect AI-generated Images Uploaded for Risk Evidence Collection in CSSW.
  • Haocheng Dai, Siwei Chen, Bei Xiao, Yangho Chen.
  • Amazon Machine Learning Conference (AMLC), 2023
  • πŸ‘¨β€βš–οΈπŸ‘οΈ / Paper / Citation

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Neural Operator Learning for Ultrasound Tomography Inversion.
  • Haocheng Dai*, Michael Penwarden*, Mike Kirby, Sarang Joshi. (*equal contribution)
  • International Conference on Medical Imaging with Deep Learning (MIDL), 2023
  • πŸ§‘β€βš•οΈπŸ”­ / Paper / Code / Slides / Poster / Citation

midl



Modeling the Shape of the Brain Connectome via Deep Neural Networks.
  • Haocheng Dai, Martin Bauer, Tom Fletcher, Sarang Joshi.
  • International Conference on Information Processing in Medical Imaging (IPMI), 2023
  • Oral Presentation
  • πŸ§‘β€βš•οΈπŸ“πŸ”­ / Paper / Code / Slides / YouTube / Citation / Media Coverage

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Understanding Visual Documents from Customer Self-Service Workflow using Multimodal Transformer.
  • Haocheng Dai, Jia-Kai Chou, Siwei Chen, Bei Xiao, Yangho Chen.
  • Amazon Machine Learning Conference (AMLC), 2022
  • πŸ‘οΈ / Paper / Citation

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Integrated Construction of Multimodal Atlases with Structural Connectomes in the Space of Riemannian Metrics.
  • Kris Campbell, Haocheng Dai, Zhe Su, Martin Bauer, Tom Fletcher, Sarang Joshi.
  • Machine Learning for Biomedical Imaging (MELBA), 2022
  • πŸ§‘β€βš•οΈπŸ“ / Paper / Code / Citation

melba



Structural Connectome Atlas Construction in the Space of Riemannian Metrics.

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Services


I have served as a reviewer for several journals and conferences, including ACM MM, AISTATS, ACM TIST, CVPR, ARO, ICLR, MedIA, MELBA, MICCAI, MIDL, NeurIPS, Scientific Reports, AI for Differential Equations in Science@ICLR, and WiCV@ECCV.



Miscellaneous


I made a handful of notes for better understanding in machine learning, mathematics of imaging, metric estimation, image registration, and solving large systems of linear equations.

My ErdΕ‘s Number = 4:
Haocheng Dai -> Sarang Joshi -> Ulf Grenander -> Oved Shisha -> Paul ErdΕ‘s;
Haocheng Dai -> Mike Kirby -> Frank Stenger -> Ambikeshwar Sharma -> Paul ErdΕ‘s.

I'm an amateur photographer, vlogger and also a loyal reader of πŸ“° newspapers, you can find the highlight front pages of the New York Times I collect by the years of 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, and 2023; the highlight front pages of the Washington Post I collect before 2015, 2016 - 2020, and 2021 - 2024.



Footprints


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