Junru Chen <br> (陈俊儒)

Junru Chen
(陈俊儒)

Zhejiang University (ZJU)

I am the 4-th-year Ph.D. student in the college of Computer Science and Technology at Zhejiang University, fortunately advised by Prof. Yang Yang. I graduated from the Chu Kochen Honors College, Zhejiang University (浙江大学竺可桢学院) with dual bachelor’s degrees in Statistics and Computer Science and Technology. My research interests include machine learning for healthcare, large-scale time series analysis, human-centered AI and any interesting topics and cutting-edge technology. I have published several papers at the top international AI conferences such as KDD, NeurIPS, AAAI. Here is my CV. If you are seeking any form of academic cooperation, please feel free to touch me.

🔥 News

  • 2024.05:  🎉🎉 Brant-X is accepted by KDD’24 in the Research Track (~20% acceptance rate).
  • 2023.09:  🎉🎉 Brant and PPi are accepted by NeurIPS’23 in the Main Track (26.1% acceptance rate).
  • 2023.05:  🎉🎉 MBrain is accepted by KDD’23 in the Research Track (~22% acceptance rate).

📝 Publications

Exploring foundation model for brain signals

Since 2020, I have served as the team leader for the BrainNet group, working alongside Prof. Yang to initiate and develop the group’s research direction and roadmap from scratch. In my role as team leader, I have been deeply involved in shaping the ideas for each paper among the group members. Simultaneously, I have provided assistance and guidance to the best of my ability in coding and writing. Below is the roadmap of our group’s research.

We aim to establish a universal model for brain signals, enhancing performance in various downstream tasks within the healthcare domain while empowering a quantitative understanding of brain activity in neuroscience.

Starting from a real medical scenario—seizure detection, our goal is to automatically identify epileptic waves in intracranial brain signals for medication-resistant patients, expediting the localization of lesions within the brain. Inspired by neuroscience research, we initially attempt to model the diffusion patterns of epileptic waves for individual patients (BrainNet, KDD’22). Subsequently, we employ self-supervised learning to capture universal spatiotemporal correlations between signals from different brain regions, facilitating transferability across different patients (MBrain, KDD’23, PPi, NeurIPS’23).

To construct a foundational model, we first attempt to pretrain a foundational model with 500M parameters based on a large volume of intracranial brain signals (Brant, NeurIPS’23). Subsequently, we integrate EEG into the pretraining corpus, building a foundational model with 1B parameters, thereby generalizing to a broader range of downstream tasks such as sleep staging and emotion recognition (Brant-2, arXiv). Leveraging the strong generalization of Brant-2, we propose a unified alignment framework (Brant-X, KDD’24) to rapidly adapt Brant-2 to downstream tasks involving rare physiological signals (e.g., EOG/ECG/EMG). In our pursuit to construct a universal foundational model, we recognize the necessity for a comprehensive dataset encompassing a wide array of domains. Given the scarcity of brain signal data, we explore a diffusion-based model for intracranial brain signals generation (NeuralDiff, under review). Furthermore, we innovate to directly synthesize infinite sequences, thereby circumventing the dependence on actual data (InfoBoost, arXiv).

In future work, we will continue to expand the generalization capability of the foundational model while exploring its interaction with humans.

arXiv preprint
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Brant-2: Foundation Model for Brain Signals
Zhizhang Yuan, Daoze Zhang, Junru Chen, Gefei Gu, Yang Yang
code
Brant-2 is the first large-scale, off-the-shelf model that can be applied to the application scenrios of both SEEG and EEG.

NeurIPS 2023
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Brant: Foundation Model for Intracranial Neural Signal
Daoze Zhang*, Zhizhang Yuan*, Yang Yang, Junru Chen, Jingjing Wang, Yafeng Li (*: equal contribution)
Homepage | code
Brant is a foundation model in the field of intracranial recordings, which learns powerful representations of intracranial neural signals.

NeurIPS 2023
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PPi: Pretraining Brain Signal Model for Patient-independent Seizure Detection
Zhizhang Yuan*, Daoze Zhang*, Yang Yang, Junru Chen, Yafeng Li (*: equal contribution)
code
PPi is a pretraining-based model to conduct patient-independent seizure detection on SEEG in the clinical scenario.

KDD 2023
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MBrain: A Multi-channel Self-Supervised Learning Framework for Brain Signals
Donghong Cai*, Junru Chen*, Yang Yang, Teng Liu, Yafeng Li (*: equal contribution)
MBrain is a generalized self-supervised learning framework, which can be applied to pre-train both EEG and SEEG signals.

KDD 2022
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BrainNet: Epileptic Wave Detection from SEEG with Hierarchical Graph Diffusion Learning
Junru Chen*, Yang Yang*, Tao Yu, Yingying Fan, Xiaoling Mo, Carl Yang (*: equal contribution)
BrainNet is a model that jointly learns the dynamic diffusion graphs and models the brain wave diffusion patterns thereon to achieve accurate epileptic wave detection.

Explore the robustness of graphs

AAAI 2022
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Unsupervised Adversarially-Robust Representation Learning on Graphs
Jiarong Xu, Yang Yang, Junru Chen, Chunping Wang, Xin Jiang, Jiangang Lu, Yizhou Sun
code
We propose a robust graph pre-trained model, such that the adversarial attacks on the input graph can be successfully identifed and blocked before being propogated to different downstream tasks.

AI Open Robustness of Deep Learning Models on Graphs: A Survey
Jiarong Xu, Junru Chen, Siqi You, Zhiqing Xiao, Yang Yang, Jiangang Lu

🎖 Honors and Awards

  • 2021,2023 Outstanding Graduate Student of the Year
  • 2020 Outstanding Undergraduate of Zhejiang University
  • 2019 First Prize Scholarship
  • 2019 Excellent Student Cadre

📖 Educations

💬 Invited Talks

💻 Academic Service

  • 2021–2023, Program committee member of KDD
  • 2023, Program committee member of TNNLS
  • 2022–2023, Program committee member of TBD

👽 Personal

Born in the chilly embrace of January, I’m an Aquarius. My MBTI says I’m an INFJ, but honestly, I’m just an ambivert with a sprinkle of everything. I’m all about philosophy, psychology, and sociology, and I run a WeChat public account called 第N面墙. Join me there for some mind-bending discussions. My dream is to wander the cosmos. And my current favorite quote: Anxiety is the dizziness of freedom. - Soren Kierkegaard.

When it comes to sports, I jive with basketball, badminton, and hiking; as for the arts, musicals, dramas, and impressionist art make my heart sing. My all-time favorite movies? Mr. Nobody and The Before Trilogy. I’m a fan of puzzle games such as the Rusty Lake series, and lately, I’ve been playing Valorant.