Full-Time Experience

[2021-2022] I worked as a Senior Research Scientist at GE Healthcare on deep learning in medical imaging applications.

[2021] I went to the industry and joined a startup company Matic and developed SLAM algorithms for housekeeping robots.

[2019-2020] I worked as a full-time research assistant at Columbia University Medical Center in a medical imaging lab.



News

[03/2025] Our paper on clinical time-series prediction for organ transplantation was accepted to Scientific Reports. [PDF]

[01/2025] Geometry-Aware Generative Autoencoder (GAGA) was accepted to AISTATS 2025. [PDF]

[12/2024] 3/3 papers (2 first-authored, both Oral) were accepted to ICASSP 2025. [ImageFlowNet] [DiffKillR]

[11/2024] I was recognized as a Top Reviewer at NeurIPS 2024.

[07/2024] I wrote a tool to generate your Google Scholar Citation World Map. [PDF] [Code]

[06/2024] My first project during my Ph.D. was accepted to MICCAI 2024. [Paper] [PDF] [MICCAI] [Poster] [Code]

[08/2022] I started my Ph.D. journey at Krishnaswamy Lab, Yale University.

[06/2022] I was recognized as an Outstanding Reviewer at ICML 2022.





Selected Recent Publications (* equal contribution)

Manifold learning Spatial-temporal dynamics

⏳ ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images

I designed a position-parameterized neural ODE that flows the multiscale latent representations, so that we can predict a future image given an earlier image and the change in time. For example: ``Predict how this patient's eye will look like if we leave the disease untreated for 2 years.''

Chen Liu*, Ke Xu*, Liangbo L. Shen, Guillaume Huguet, Zilong Wang, Alexander Tong, Danilo Bzdok, Jay Stewart, Jay C. Wang, Lucian V. Del Priore, Smita Krishnaswamy

ICASSP 2025 Oral Presentation 🔊

[Paper] [PDF] [IEEE PDF] [ICASSP] [Slides] [Code]

Manifold learning Multimodal fusion

ImmunoStruct: a multimodal neural network framework for immunogenicity prediction from peptide-MHC sequence, structure, and biochemical properties

ImmunoStruct predicts immunogenicity of protein MHC complexes by fusing information from multiple biological modalities: sequence, structure and biochemical properties. I designed a novel cancer-wildtype contrastive learning objective to establish a new state of the art in the field, by encouraging immunogenicity-aware pairwise similarity and suppressing feature space collapse.

Kevin Bijan Givechian, Joao Felipe Rocha*, Edward Yang*, Chen Liu*, Kerrie Greene, Rex Ying, Etienne Caron, Akiko Iwasaki, Smita Krishnaswamy

bioRxiv 2024, under review at Nature Machine Intelligence

[Paper] [PDF]

Manifold learning Weak supervision

✂️ CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation

Chen Liu*, Matthew Amodio*, Liangbo L. Shen, Feng Gao, Arman Avesta, Sanjay Aneja, Jay C. Wang, Lucian V. Del Priore, Smita Krishnaswamy

I introduced CUTS, a novel multiscale unsupervised segmentation framework. It first uses intra-image contrastive learning and local patch reconstruction to organize a meaningful pixel-level embedding space, and then produces multiscale assignments with diffusion condensation. On datasets with few training samples, CUTS performs on par or better than Segment Anything methods.

MICCAI 2024

[Paper] [PDF] [Code] [MICCAI] [Poster]



Conference Papers (* equal contribution)

Manifold learning Spatial-temporal dynamics

⏳ ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images

Chen Liu*, Ke Xu*, Liangbo L. Shen, Guillaume Huguet, Zilong Wang, Alexander Tong, Danilo Bzdok, Jay Stewart, Jay C. Wang, Lucian V. Del Priore, Smita Krishnaswamy

ICASSP 2025 Oral Presentation 🔊

[Paper] [PDF] [IEEE PDF] [ICASSP] [Slides] [Code]

Manifold learning Weak supervision

⚔️ DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy Images

Chen Liu*, Danqi Liao*, Alejandro Parada-Mayorga*, Alejandro Ribeiro, Marcello DiStasio, Smita Krishnaswamy

ICASSP 2025 Oral Presentation 🔊

[Paper] [PDF] [IEEE PDF] [ICASSP] [Slides] [Code]

Manifold learning

🌐 Geometry-Aware Generative Autoencoders for Warped Riemannian Metric Learning and Generative Modeling on Data Manifolds

Xingzhi Sun*, Danqi Liao*, Kincaid MacDonald*, Yanlei Zhang, Chen Liu, Guillaume Huguet, Guy Wolf, Ian Adelstein, Tim GJ Rudner, Smita Krishnaswamy

ICML 2024 GRaM Workshop & AISTATS 2025

[Paper] [PDF]

Weak supervision

Hyperedge Representations with Hypergraph Wavelets: Applications to Spatial Transcriptomics

Xingzhi Sun*, Charles Xu*, João F Rocha, Chen Liu, Benjamin Hollander-Bodie, Laney Goldman, Marcello DiStasio, Michael Perlmutter, Smita Krishnaswamy

ICASSP 2025

[Paper] [PDF] [IEEE PDF] [ICASSP]

Manifold learning Weak supervision

✂️ CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image Segmentation

Chen Liu*, Matthew Amodio*, Liangbo L. Shen, Feng Gao, Arman Avesta, Sanjay Aneja, Jay C. Wang, Lucian V. Del Priore, Smita Krishnaswamy

MICCAI 2024

[Paper] [PDF] [MICCAI] [Poster] [Code]

Manifold learning

🎲 Assessing Neural Network Representations During Training Using Noise-Resilient Diffusion Spectral Entropy

Danqi Liao*, Chen Liu*, Benjamin W. Christensen, Alexander Tong, Guillaume Huguet, Guy Wolf, Maximilian Nickel, Ian Adelstein, Smita Krishnaswamy

ICML 2023 TAG-ML Workshop & IEEE CISS 2024

[Paper] [PDF] [Slides] [Code]

Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape Features

Nanyan Zhu*, Chen Liu*, Zakary S. Singer, Tal Danino, Andrew F. Laine, Jia Guo

IEEE EMBC 2022

[Paper] [PDF] [Code]

Multimodal fusion

Deep Learning Identifies Neuroimaging Signatures of Alzheimer's Disease Using Structural and Synthesized Functional MRI Data

Nanyan Zhu*, Chen Liu*, Xinyang Feng, Dipika Sikka, Sabrina Gjerswold-Selleck, Scott A. Small, Jia Guo

IEEE ISBI 2021

[Paper] [PDF] [IEEE]

Substituting Gadolinium in Brain MRI Using DeepContrast

Haoran Sun, Xueqing Liu, Xinyang Feng, Chen Liu, Nanyan Zhu, Sabrina J Gjerswold-Selleck, Hong-Jian Wei, Pavan S Upadhyayula, Angeliki Mela, Cheng-Chia Wu, Peter D Canoll, Andrew F Laine, J Thomas Vaughan, Scott A Small, Jia Guo

IEEE ISBI 2020

[Paper] [PDF] [IEEE]



Journal Publications (* equal contribution)

Multimodal fusion

Deep Learning Unlocks the True Potential of Organ Donation after Circulatory Death with Accurate Prediction of Time-to-Death

Xingzhi Sun*, Edward De Brouwer*, Chen Liu, Smita Krishnaswamy, Ramesh Batra

Scientific Reports 2025, Impact Factor: 3.8 (2025)

[Paper] [PDF] [Nature] [Nature PDF]

Multimodal fusion

Deep Learning of MRI Contrast Enhancement for Mapping Cerebral Blood Volume from Single-Modal Non-Contrast Scans of Aging and Alzheimer's Disease Brains

Chen Liu*, Nanyan Zhu*, Haoran Sun, Junhao Zhang, Xinyang Feng, Sabrina Gjerswold-Selleck, Dipika Sikka, Xuemin Zhu, Xueqing Liu, Tal Nuriel, Hong-Jian Wei, Cheng-Chia Wu, J Thomas Vaughan, Andrew F Laine, Frank A Provenzano, Scott A Small, Jia Guo

Frontiers in Aging Neuroscience 2022, Impact Factor: 5.7 (2022)

[Paper] [PDF] [NIH PubMed]

In Vivo γ-Aminobutyric Acid Increase as a Biomarker of the Epileptogenic Zone: An Unbiased Metabolomics Approach

Sophie Hamelin, Vasile Stupar, Lucile Mazière, Jia Guo, Wafae Labriji, Chen Liu, Ludiwine Bretagnolle, Sandrine Parrot, Emmanuel L Barbier, Antoine Depaulis, Florence Fauvelle

Epilepsia 2021, Impact Factor: 6.7 (2021)

[Paper] [PDF] [NIH PubMed]

Reduced Hippocampal GABA is associated with Poorer Episodic Memory in Healthy Older Women: A Pilot Study

Joan Jiménez-Balado, Alexandra Ycaza Herrera, Kay Igwe, Lynda Klem, Korhan Buyukturkoglu, Andrei Irimia, Chen Liu, Jia Guo, Adam M Brickman, Teal S Eich

Frontiers in Behavioral Neuroscience 2021, Impact Factor: 3.6 (2021)

[Paper] [PDF] [NIH PubMed]



Preprints (* equal contribution)

Manifold learning Multimodal fusion

ImmunoStruct: a multimodal neural network framework for immunogenicity prediction from peptide-MHC sequence, structure, and biochemical properties

Kevin Bijan Givechian, Joao Felipe Rocha*, Edward Yang*, Chen Liu*, Kerrie Greene, Rex Ying, Etienne Caron, Akiko Iwasaki, Smita Krishnaswamy

bioRxiv 2024

[Paper] [PDF]

Adversarial Focal Loss: Asking Your Discriminator for Hard Examples

Chen Liu, Xiaomeng Dong, Michael Potter, Hsi-Ming Chang, Ravi Soni

arXiv 2022

[Paper] [PDF]



Patents (* equal contribution)

System and Method for Obtaining Accurate Measurements and Quantification of X-Ray Image from Estimation of Key Anatomical Locations

Gireesha Chinthamani Rao, Ravi Soni, Gopal B Avinash, Poonam Dalal, Chen Liu, Molin Zhang, Zita Herczeg

U.S. Patent App.

[Patent] [PDF]

X-Ray Lead Marker Detection System for X-Ray Imaging System

Gireesha Chinthamani Rao, Ravi Soni, Poonam Dalal, Chen Liu, PATI Dibyajyoti, Katelyn Nye

U.S. Patent App.

[Patent] [PDF]



Conference Abstracts (Excluding those published elsewhere) (* equal contribution)

DL-BET-A Deep Learning Based Tool for Automatic Brain Extraction from Structural Magnetic Resonance Images in Mice

Sabrina Gjerswold-Selleck, Nanyan Zhu, Haoran Sun, Dipika Sikka, Jie Shi, Chen Liu, Tal Nuriel, Scott A Small, Jia Guo

ISMRM 2021

[PDF]

JET-A Matlab Toolkit for Automated J-Difference-Edited MR Spectra Processing of In Vivo Mouse MEGA-PRESS Study at 9.4 T

Chen Liu, David Jing Ma, Nanyan Zhu, Kay Igwe, Jochen Weber, Roshell Li, Emily Turner Wood, Wafae Labriji, Vasile Stupar, Yanping Sun, Neil Harris, Antoine Depaulis, Florence Fauvelle, Scott A Small, Douglas L Rothman, Jia Guo

ISMRM 2021 Oral Presentation 🔊

[PDF]

Predicting Gadolinium Contrast Enhancement for Structural Lesion Analysis using DeepContrast

Dipika Sikka, Nanyan Zhu, Chen Liu, Scott Small, Jia Guo

ISMRM 2021 Oral Presentation 🔊

[PDF]

Blogs and Side Projects (* equal contribution)

🌍 CitationMap: A Python Tool to Identify and Visualize Your Google Scholar Citations Around the World

Chen Liu

TechRxiv, Authorea Preprints

[Paper] [PDF] [Code]

A Novel Entropy and Mutual Information Measure for High Dimensional Data and Deep Neural Networks

Chen Liu

Blog

[PDF]

A Technical Deep Dive into Drag Your GAN (DragGAN)

Chen Liu

Blog

[PDF]

Towards a Large-Scale Unbiased Machine Learning Benchmark for Cell Instance Segmentation: Final Report for CPSC 537 Intro to Database Systems

Chen Liu

Course Project

[PDF]


Others

Service  I'm a regular reviewer for conferences NeurIPS, ICML, ICLR, MICCAI, ICASSP and journals TNNLS.


Fun fact 1  I am the father of two cats.

Fun fact 2  My spirit animal is a fox.