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GeezerVison is showing ppwangyc.github.io — Yanchen Wang

[Yanchen :)]
Wilson (Yanchen) Wang
Ph.D. Student, Computer Science, Stanford University
Email: ppwang (at) stanford.edu
Office: Somewhere on Earth
Scholar / GitHub / Twitter
Biography
[more]
I'm a first-year Ph.D. student in Computer Science at Stanford University. Previously, I did research at Columbia's Center for Theoretical Neuroscience and Stanford, and received my B.S. in Computer Science from the University of Rochester. My research interests lie in computational neuroscience and computational cognitive science as I am passionate about understanding the inner workings of the brain. My ultimate dream is to create a FullDive machine like a science fiction: Sword Art Online (SAO) .
SAO

"Sword Art Online" is a light novel series written by Reki Kawahara. "Full Dive" is a central concept in "Sword Art Online," representing a fully immersive virtual reality experience. In this advanced VR system, players connect through nerve gear technology ( Brain Computer Interface) that stimulates the brain, allowing for sensory experiences and interactions that feel as real as the physical world.

Research
(* indicates equal contribution, † indicates equal mentorship.)
BEAST3D: Animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting
Yanchen Wang, Lenny Aharon, Wangshu Zhu, Kyle Daruwalla, Linghua Zhang, Jiaru Zou, Selmaan N. Chettih, Xun Helen Hou, Liam Paninski, and Matthew R. Whiteway
NeurIPS 2026 / Homepage / Paper / Code / bibtex
Oral (Top 0.4%)
      @article{wang2026beast3d,
  title={BEAST3D: Animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting},
  author={Wang, Yanchen and Aharon, Lenny and Zhu, Wangshu and Daruwalla, Kyle and Zhang, Linghua and Zou, Jiaru and Chettih, Selmaan and Hou, Helen and Paninski, Liam and Whiteway, Matthew R},
  journal={arXiv preprint arXiv:2606.02937},
  year={2026}
}
[Lightning Pose 3D]
Lightning Pose 3D: an uncertainty-aware framework for data-efficient multi-view animal pose estimation
Lenny Aharon*, Matthew R. Whiteway*, Karan Sikka, Keemin Lee, Yanchen Wang, Selmaan Chettih, Benjamin Midler, Ilana B. Witten, Dmitriy Aronov, International Brain Laboratory, and Liam Paninski
Nature Methods (Revision) / Paper / Code / bibtex
      @article{aharon2026lightning,
  title={Lightning Pose 3D: an uncertainty-aware framework for data-efficient multi-view animal pose estimation},
  author={Aharon, Lenny and Whiteway, Matthew R and Sikka, Karan and Lee, Keemin and Wang, Yanchen and Chettih, Selmaan and Midler, Benjamin and Witten, Ilana B and Aronov, Dmitriy and International Brain Laboratory and others},
  journal={bioRxiv},
  pages={2026--04},
  year={2026},
  publisher={Cold Spring Harbor Laboratory}
}
[MMA++]
MMA++: Effective Multi-Modal Adaptation for Vision-Language Models
Lingxiao Yang, Ru-Yuan Zhang, Yanchen Wang, and Xiaohua Xie
IEEE TPAMI / Paper / Code / bibtex
      @article{YangMMA++_TPAMI2026,
  author={Yang, Lingxiao and Zhang, Ru-Yuan and Wang, Yanchen and Xie, Xiaohua},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  title={MMA++: Effective Multi-Modal Adaptation for Vision-Language Models},
  year={2026},
  doi={10.1109/TPAMI.2026.3691448}
}
[BEAST]
Animal behavioral analysis and neural encoding with transformer-based self-supervised pretraining
Yanchen Wang*, Han Yu*, Ari Blau, Yizi Zhang, International Brain Laboratory, Cole Hurwitz, Liam Paninski, and Matt Whiteway
ICLR 2026 / Paper / Code / bibtex
      @article{wang2025self,
          title={Animal behavioral analysis and neural encoding with transformer-based self-supervised pretraining},
          author={Wang, Yanchen and Yu, Han and Blau, Ari and Zhang, Yizi and Laboratory, The International Brain and Paninski, Liam and Hurwitz, Cole and Whiteway, Matt},
          journal={arXiv preprint arXiv:2507.09513},
          year={2025}
        }
[NEURONA]
Neuro-Symbolic Decoding of Neural Activity
Yanchen Wang*, Joy Hsu*, Ehsan Adeli†, and Jiajun Wu†,
ICLR 2026 / Homepage / Paper / Code / bibtex
      @article{wang2026neuro,
          title={Neuro-Symbolic Decoding of Neural Activity},
          author={Wang, Yanchen and Hsu, Joy and Adeli, Ehsan and Wu, Jiajun},
          journal={arXiv preprint arXiv:2603.03343},
          year={2026}
        }
[RRR]
Exploiting correlations across trials and behavioral sessions to improve neural decoding
Yizi Zhang, Hanrui Lyu, Cole Hurwitz, Shuqi Wang, Charles Lincoln Findling, Yanchen Wang, Felix Hubert, Alexandre Pouget, International Brain Laboratory, Erdem Varol, and Liam Paninski
Neuron / Paper / Code / bibtex
      @article{zhang2025exploiting,
        title={Exploiting correlations across trials and behavioral sessions to improve neural decoding},
        author={Zhang, Yizi and Lyu, Hanrui and Hurwitz, Cole and Wang, Shuqi and Findling, Charles Lincoln and Wang, Yanchen and Hubert, Felix and Pouget, Alexandre and Laboratory, International Brain and Varol, Erdem and Paninski, Liam},
        journal={Neuron},
        
        year={2025}
      }
[NEDS]
Neural Encoding and Decoding at Scale
Yizi Zhang*, Yanchen Wang*, Mehdi Azabou, Alexandre Andre, Zixuan Wang, Hanrui Lyu, International Brain Laboratory, Eva Dyer, Liam Paninski, and Cole Hurwitz
ICML 2025 / Homepage / Paper / Code / bibtex
Spotlight (Top 2.6%)
      @article{zhang2025neural,
        title={Neural Encoding and Decoding at Scale},
        author={Zhang, Yizi and Wang, Yanchen and Azabou, Mehdi and Andre, Alexandre and Wang, Zixuan and Lyu, Hanrui and Laboratory, The International Brain and Dyer, Eva and Paninski, Liam and Hurwitz, Cole},
        journal={arXiv preprint arXiv:2504.08201},
        year={2025}
      }
[WAVE]
Decoding Visual Experience and Mapping Semantics through Whole-Brain Analysis Using fMRI Foundation Models
Yanchen Wang, Adam Turnbull, Tiange Xiang, Yunlong Xu, Sa Zhou, Adnan Masoud, Shekoofeh Azizi, Feng Vankee Lin, and Ehsan Adeli
Medical Image Analysis (Revision) / Homepage / Paper / Code / bibtex
@article{wang2024decoding,
  title={Decoding Visual Experience and Mapping Semantics through Whole-Brain Analysis Using fMRI Foundation Models},
  author={Wang, Yanchen and Turnbull, Adam and Xiang, Tiange and Xu, Yunlong and Zhou, Sa and Masoud, Adnan and Azizi, Shekoofeh and Lin, Feng Vankee and Adeli, Ehsan},
  journal={arXiv preprint arXiv:2411.07121},
  year={2024}
}
[MTM]
Towards a "universal translator" for neural dynamics at single-cell, single-spike resolution
Yizi Zhang, Yanchen Wang, Donato Jimenez-Beneto, Zixuan Wang, Mehdi Azabou, Blake Richards, Olivier Winter, International Brain Laboratory, Eva Dyer, Liam Paninski, and Cole Hurwitz
NeurIPS 2024 / Homepage / Paper / Code / bibtex
@InProceedings{Zhang_2024_arXiv,
  author    = {Zhang, Yizi and Wang, Yanchen and Benetó, Donato Jiménez and Wang, Zixuan and Azabou, Mehdi and Richards, Blake and Winter, Olivier and The International Brain Laboratory and Dyer, Eva and Paninski, Liam and Hurwitz, Cole},
  title     = {Towards a “universal translator” for neural dynamics at single-cell, single-spike resolution},
  booktitle = {arXiv},
  month     = {July},
  year      = {2024},
  url       = {http://arxiv.org/abs/2407.14668}
}
[MMA]
MMA: Multi-Modal Adapter for Vision-Language Models
Lingxiao Yang, Ru-Yuan Zhang, Yanchen Wang, and Xiaohua Xie,
CVPR 2024 / Paper / Code / bibtex
@inproceedings{yang2024mma,
  title={MMA: Multi-Modal Adapter for Vision-Language Models},
  author={Yang, Lingxiao and Zhang, Ru-Yuan and Wang, Yanchen and Xie, Xiaohua},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={23826--23837},
  year={2024}
}
[FACE]
Vision-based estimation of fatigue and engagement in cognitive training sessions
Yanchen Wang*, Adam Turnbull*, Yunlong Xu, Kathi Heffner, Feng Vankee Lin, and Ehsan Adeli
Artificial Intelligence in Medicine (Elsevier) / Paper / Code / bibtex
@article{wang2024vision,
  title={Vision-based estimation of fatigue and engagement in cognitive training sessions},
  author={Wang, Yanchen and Turnbull, Adam and Xu, Yunlong and Heffner, Kathi and Lin, Feng Vankee and Adeli, Ehsan},
  journal={Artificial Intelligence in Medicine},
  volume={154},
  pages={102923},
  year={2024},
  publisher={Elsevier}
}
Education
Stanford University
Ph.D. in Computer Science
2026 - Present
Stanford, US
University of Rochester
B.S. in Computer Science
2019 - 2023
Rochester, US
Experience
Columbia University Center for Theoretical Neuroscience
Research Staff Assistant | Advisor: Prof. Liam Paninski
2024 - 2026
New York, US
Stanford University
Research Data Analyst | Advisors: Profs. Ehsan Adeli, Jiajun Wu, and Feng Vankee Lin
2023 - 2024
Stanford, US
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