Yichun He

I'm a Ph.D. candidate at Harvard University School of Enginnering and Applied Sciences and the Broad Institute of MIT and Harvard. I'm fortunate to be advised by Prof. Jia Liu and Prof. Xiao Wang. I also interned in Prof. Aviv Regev's lab at Genentech with Hanchen Wang and Paula Coelho during the summer of 2024.
My research explores the complex biological systems across multi-scales, from molecular features and cell identities to tissue structures, functions and behaviors. I develop artificial intelligence (AI), machine learning (ML), and multi-agent systems solutions with applications in spatial multi-omics and brain machine interfaces to advance the understanding of biology and health.

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Research

I am passionate about accelerating discovery in biology through advanced AI/ML approaches. My work spans multiple directions, including:

(1) Mapping Spatially Resolved Cell Types and Molecular Profiles at Scale
(2) Linking Cellular Characteristics to Spatial Contexts Across Technologies and Conditions
(3) Uncovering Long-Term Biological Processes and Behaviors
(4) Integrating Diverse Biological Data to Understand Cell States and Dynamics
(5) Enabling Autonomous Experimentation, Analysis, and Scientific Discovery

Representative papers are highlighted. # Co-first authors; * Corresponding authors.

(1) Characterize whole-brain spatially resolved cell types at molecular resolution with scalable AI and spatial transcriptomics
	Spatial Atlas of the Mouse Central Nervous System at Molecular Resolution Hailing Shi#, Yichun He#, Yiming Zhou#, Jiahao Huang, Kamal Maher, Brandon Wang, Zefang Tang, Shuchen Luo, Peng Tan, Morgan Wu, Zuwan Lin, Jingyi Ren, Yaman Thapa, Xin Tang, Ken Y. Chan, Benjamin E. Deverman, Hao Shen, Albert Liu, Jia Liu* & Xiao Wang* Nature, 2023 Github Cover and Perspective highlight in Nature as part of collection for whole mouse brain spatial atlas, "BRAIN Initiative Cell Census Network 2.0 – Whole Mouse Brain". Google Map of the Mouse Brain at Molecular Resolution.
	ClusterMap for multi-scale clustering analysis of spatial gene expression Yichun He#, Xin Tang#, Jiahao Huang, Jingyi Ren, Haowen Zhou, Kevin Chen, Albert Liu, Hailing Shi, Zuwan Lin, Qiang Li, Abhishek Aditham, Johain Ounadjela, Emanuelle I. Grody, Jian Shu, Jia Liu* & Xiao Wang* Nature Communications, 2021 ClusterMap package Research develops new way to map RNAs in the cell.
	Controlling organoid symmetry breaking uncovers an excitable system underlying human axial elongation Giridhar M. Anand, Heitor C. Megale, Sean H. Murphy, Theresa Weis, Zuwan Lin, Yichun He, Xiao Wang, Jia Liu, Sharad Ramanathan* Cell, 2023
(2) Bridge cellular features with spatial contexts across various technologies with contextual AI
	Towards a universal spatial molecular atlas of the mouse brain Yichun He, Hao Sheng, Hailing Shi, Wendy Xueyi Wang, Zefang Tang, Jia Liu, and Xiao Wang bioRxiv, 2024 Data portal of the molecular common coordinate framework (molCCF) FuseMap package
	Spatiotemporally resolved transcriptomics reveals the subcellular RNA kinetic landscape Jingyi Ren#, Haowen Zhou#, Hu Zeng#, Connie Kangni Wang, Jiahao Huang, Xiaojie Qiu, Xin Sui, Qiang Li, Xunwei Wu, Zuwan Lin, Jennifer A. Lo, Kamal Maher, Yichun He, Xin Tang, Judson Lam, Hongyu Chen, Brian Li, David E. Fisher, Jia Liu & Xiao Wang* Nature Methods, 2023
	Scalable spatial single-cell transcriptomics and translatomics in 3D thick tissue blocks Xin Sui#, Jennifer A. Lo#, Shuchen Luo, Yichun He, Zefang Tang, Zuwan Lin,Yiming Zhou, Wendy Xueyi Wang, Jia Liu, Xiao Wang* bioRxiv, 2024
(3) Decode dynamic biological processes in long term with real-time AI and brain computer interfaces
	End-to-end multimodal deep learning for real-time decoding of months-long neural activity from the same cells Yichun He#, Arnau Marin-Llobet#, Hao Sheng, Ren Liu, Jia Liu* bioRxiv, 2024 AutoSort package
	Soft bioelectronics for cardiac interfaces Xin Tang#, Yichun He# Jia Liu, Biophysics Reviews*, 2022
	Brain implantation of tissue-level-soft bioelectronics via embryonic development Hao Sheng#, Ren Liu#, Qiang Li#, Zuwan Lin#, Yichun He, Thomas Blum, Hao Zhao, Xin Tang, Wenbo Wang, Lishuai Jin, Zheliang Wang, Emma Hsiao, Paul Le Floch, Hao Shen, Ariel J. Lee, Rachael Alice Jonas-Closs, James Briggs, Siyi Liu, Daniel Solomon, Xiao Wang, Nanshu Lu, and Jia Liu* bioRxiv, 2024
(4) Integrate diverse biological data with multi-modal AI and single-cell multi-omics
	Multi-task learning for single-cell multi-modality biology Xin Tang#, Jiawei Zhang#, Yichun He#, Xinhe Zhang, Zuwan Lin, Sebastian Partarrieu, Emma Bou Hanna, Zhaolin Ren, Hao Shen, Yuhong Yang, Xiao Wang, Na Li, Jie Ding* & Jia Liu* Nature Communications, 2023 UnitedNet package Editor highlights in Biotechnology and Methods and Computational Science.
	Multimodal charting of molecular and functional cell states via in situ electro-seq Qiang Li#, Zuwan Lin#, Ren Liu#, Xin Tang#, Jiahao Huang, Yichun He, Xin Sui, Weiwen Tian, Hao Shen, Haowen Zhou, Hao Sheng, Hailing Shi, Ling Xiao, Xiao Wang, Jia Liu Cell, 2023 Cover highlight in Cell Perspective highlight in Nature Methods
(5) Autonomous experimental planning, data analysis, and scientific discovery in spatial biology with Agentic AI
	An autonomous agent for scientific discovery in spatial biology Hanchen Wang#, Yichun He#, Paula Coelho#..., Aviv Regev In preparation, 2024
	Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design Chenyu Wang#, Masatoshi Uehara#, Yichun He, Amy Wang, Tommaso Biancalani, Avantika Lal, Tommi Jaakkola, Sergey Levine, Hanchen Wang, Aviv Regev arxiv, 2024

This website is borrowed from Jon Barron. Thanks!

Research

(1) Characterize whole-brain spatially resolved cell types at molecular resolution with scalable AI and spatial transcriptomics

(2) Bridge cellular features with spatial contexts across various technologies with contextual AI

(3) Decode dynamic biological processes in long term with real-time AI and brain computer interfaces

(4) Integrate diverse biological data with multi-modal AI and single-cell multi-omics

(5) Autonomous experimental planning, data analysis, and scientific discovery in spatial biology with Agentic AI