Penghao Qian

Education and Internship

Education

• PhD student | Artificial Intelligence, College of Computer Science and Artificial Intelligence

• Master's in Computer Science | Average score: 87.87/100 | Rank: top 5% (7/151)

• Bachelor of Engineering in Computer Science | GPA: 3.6/4.0 | Rank: top 15%

Internship

• Using multimodal fMRI and biomarker data for LLM-based Alzheimer's diagnosis in PET-CT.

• Studied brain-computer interfaces (BCI) and electroencephalography (EEG), and contributed to experiment design and execution.
• Managed, processed, and analyzed EEG and electrodermal activity (EDA) data, and built the preprocessing pipeline for physiological signals such as EEG recorded in natural settings.

Projects

Unimportant, there's a million things I haven't done, just you wait, just you wait …

— Alexander·Hamilton

My study of neuroscience has been a gradual deepening process. I started by implementing brain-computer interfaces to understand neural mechanisms, and then moved to inter-individual analysis of physiological signals (e.g. EEG, sEMG, PPG). At the master's level, I began to study structural and functional brain networks at the single-cell level and developed novel morphology-based classification tools. I also explored more abstract models at the whole-brain scale.

At my current PhD stage, I continue to study brain structure–function relationships and have expanded my work to multiple scales, ranging from nanoscale electron microscopy imaging to single-cell networks and mesoscale brain regions. My work also extends from the mouse to the human brain. In addition, I am actively exploring AI-based methods to tackle challenges in neuroscience.

Analysis of structural and functional brain networks

This project has two parts. In the first part, we studied how the details of neuronal morphology — in particular bouton distribution — affect network structure. In the second part, we studied the relationship between single-cell connectivity and function through simulations.

From single neuron to structure

Paper | Project Page

From single neuron to function

Paper

We simulated the resting state of the whole mouse brain using an extensive dataset of 1,876 fully reconstructed neurons, revealing stronger and more varied connections than earlier tracer-injection-based measurements had indicated. After optimizing global coupling and background noise parameters, we tested how well the simulation agreed with experimental data, and found that simulations built on single-cell connectivity had greater predictive power than those based on tracer-based connectomes. Our findings underscore the importance of incorporating detailed single-cell information to model brain dynamics accurately, offering insights into the functional architecture of the mouse brain.

Tools for neuron classification based on manifold patterns

Paper | Morphological feature space toolkit | Preprint | Neuron type classification toolkit

Because morphological feature spaces are often too complex for neuron classification, we introduce a method that detects the optimal subspace of features in which neurons cluster well. We applied this method to one of the largest curated databases of morphological reconstructions, containing more than 9,400 mouse neurons across 19 cell types. Our method detects the distinctive feature subspace of each cell type. It also outperforms prevailing cell-typing approaches in identifying key morphological indicators for each neuron type and in separating super-classes of these types. Neuronal subclasses can inform brain connectivity and modeling, and also support other analyses such as feature-space studies.

Study of EEG signal correlation between students

Paper | Code

This study examined the relationship between EEG signal correlation and students' academic performance in the classroom; my contribution focused on data analysis and processing.
A portable two-electrode headband was used to record real classroom data over up to four months, which produced a large dataset with a substantial number of artifacts. To address this, I developed a pipeline that slices the data into 30-second epochs and evaluates data quality. Slow drifts were then removed using NoiseTool in MATLAB, and ocular artifacts were attenuated with the MSDL (multi-scale dictionary learning) toolbox. Finally, total interdependence was computed.

Game based on BCI and VR

Project Page

This project explores the combination of BCI and VR. Both EEG-BCI and VR require a headset, so it is natural to hope that the two can be combined.
As for BCI interaction, we felt that active BCI — which requires external stimuli to induce interaction — is not natural enough, while passive BCI has lacked interaction scenarios that cannot be replaced by other modalities, such as the measurement of personal state and emotion. We therefore designed a game that combines several BCI interaction paradigms, using personal state as a means of control.

Publications

Only the written can stably exist outside the mind.

— Elowen·Crawford

I study brain structure and function from a network perspective across different scales (inter-individual, brain region, single cell, and synapse), while also developing new neuroscience tools, such as methods for classifying neuronal morphologies.

Journal Papers:

Main works

1. Non-homogeneous axonal bouton distributions constrain whole-brain single-cell network topology
   Penghao Qian, Linus Manubens-Gil, Shengdian Jiang, Hanchuan Peng
   Journal of Computational Neuroscience | 2026
2. Non-homogenous axonal bouton distribution in whole-brain single cell neuronal networks
   Penghao Qian, Linus Manubens-Gil*, Shengdian Jiang, Hanchuan Peng*
   Cell Reports | 2024 | Paper | Code
3. Cell Typing and Sub-typing Based on Detecting Characteristic Subspaces of Morphological Features Derived from Neuron Images
   Sujun Zhao, Penghao Qian, Lijuan Liu*
   Preprint | 2023 | under review | Preprint | Code
4. Inter-brain Coupling Reflects Disciplinary Differences in Real-world Classroom Learning
   Jingjing Chen, Penghao Qian, Xinqiao Gao, Baosong Li, Yu Zhang*, Dan Zhang*
   npj Science of Learning | 2023 | Paper | Code
5. Manifold-Classification of Neuron Types from Microscopic Images
   Lijuan Liu*, Penghao Qian
   Bioinformatics | 2022 | Paper | Code

Co-authored works

1. Neuronal diversity and stereotypy at multiple scales through whole brain morphometry
   Yufeng Liu, Shengdian Jiang, Yingxin Li, ... , Penghao Qian, ... , Hanchuan Peng*
   Nature Communications | 2024 | Paper | Project

Conference:

1. 2025 Autumn Conference of the New Cornerstone Science Foundation
   Poster | Guilin, Guangxi Province 2025
   
2. 2025 Symposium on Neural Computation and Beyond
   Poster | Shanghai Jiao Tong University 2025
   
3. Cognitive Computational Neuroscience (CCN) 2024 | Abstract
   Poster | 2024
   
4. BioImage Informatics Conference | Bioimaging and microscopy applications | Poster
   Poster Section | Institut Pasteur Online 2021
   Title: Single neuron morphological details imply a shift from a Small-World to a Scale-Free topology in the mouse brain network
   Penghao Qian*, Linus Manubens-Gil
5. 3rd Annual Conference on Engineering Psychology of C.P.S. | News
   Assisted with Oral Presentation | East China Normal University 2019
   Our analysis of EEG data collected by portable devices was presented by A.P. Dan Zhang
   

Summer School:

1. First Archaeological Theory Summer Institute
   Trainee | Shandong University 2026
   
2. The Computational and Cognitive Neuroscience (CCN) summer school| News
   Trainee | Cold Spring Harbor Asia 2024
   
3. BioBit Program Summer School for Computational Biology | Poster
   Best Poster and Best Student Award | Zhejiang Lab 2023
   
4. IEEE 4th International Summer School for Neural Engineering | News
   Trainee (40 selected from 400+ applicants) | Tsinghua University 2018

Competition:

1. Modeling of deep brain electrical stimulation (DBS) therapy for Parkinson's disease | Project
   National Second Prize | China Postgraduate Mathematical Contest in Modeling | 2021
   
   • Built a basic neuron firing model based on the H-H model and the structure of the basal ganglia network.
   • Compared the firing of basal ganglia circuits in Parkinson's disease with normal conditions.
   • Applied DBS to two different targets (STN and GPi) and selected the optimal stimulation target.
   • Varied the intensity, frequency, and stimulation mode of DBS to find the optimal parameter combination.
   • Also identified other potential stimulation targets.
2. Design of Dynamic Scheduling Strategy of Smart Rail Guided Vehicle (RGV)
   National Second Prize | Contemporary Undergraduate Mathematical Contest in Modeling | 2018
   
   • Simulated the RGV operation process with different algorithms (Sequential, Elevator Scheduling, Greedy).
   • Pruned the feature search space to find the optimal solution.
   • Discussed all initialization cases and their influence on subsequent processes.
   • Estimated process arrangement and failure risk to demonstrate the robustness of the system.

Honors

Honorable Titles

• 2024, Best Outstanding Young Student at Southeast University | 10 students per year among all undergraduate and graduate students university-wide
• 2024, Honored Graduate at Southeast University | 11 students among all graduates of the college (about 160+ students)
• 2023, Honor Student at Southeast University | Only 15 students per year at the college (about 500+ students)

Awards

• 2024, Brains for Brains Young Researcher Award | Awarded by the Bernstein Network Computational Neuroscience (one student every two years)
• 2021, National Second Prize, the 18th China Post-Graduate Mathematical Modeling Contest | Project Code
• 2018, National Second Prize, Contemporary Undergraduate Mathematical Contest in Modeling (CUMCM)
• 2018, Third Prize in the Physics Competition in parts of China
• 2017, Third Prize in the Chinese Mathematics Competitions (Beijing Division)
• 2017, Third Prize in the Provincial Blue Bridge Cup Programming Competition
• 2017, Second Prize in the Preliminary Competition of the FLTRP Cup English Debate

Scholarships

• 2023, National Scholarship | The highest scholarship in China | 11 students per year college-wide (about 500+ students)
• 2022, First Prize Graduate Scholarship (second year of Master's)
• 2021, First Prize Graduate Scholarship (first year of Master's)
• 2019, Third Prize Scholarship for Academic Excellence
• 2018, Third Prize Scholarship for Academic Excellence
• 2017, Scholarship for Outstanding Students
• 2017, Second Prize Scholarship for Academic Excellence

Beyond Research

Archaeology

Study Notes

Beyond my formal research, I maintain a long-term personal study of Chinese archaeology and cultural heritage, including Neolithic cultures in China, bronze artifacts of the Xia, Shang, and Zhou dynasties, Buddhist sculpture in northern China, ancient Chinese timber architecture, mural paintings, and Han-dynasty tombs. I have compiled extensive study notes on these subjects.
Drawing on visits to the National Museum of China, the National Archaeological Museum of China, the Shanghai Museum, the Nanjing Museum, the Shanxi Museum, the Shanxi Bronze Museum, the Zhejiang Provincial Museum, the Anhui Museum, and other institutions, I have also written introductions to artifacts and museum-visit notes. As of July 2026, these notes total approximately 150,000 Chinese characters.