Xiaodong Qu

I am currently a visiting assistant professor of Computer Science at Swarthmore College.

I received my Ph.D. in Computer Science from Brandeis University.

My Ph.D. advisor is Professor Timothy J Hickey.

My research interests are Machine Learning and Brain-Computer Interfaces.

Here is the pronunciation of my first name and last name.

xqu1@swarthmore.edu

Zoom Link for Office Hours and Research Meetings

More on our CS Faculty Page

CPSC 21 - Introduction to Computer Science (Fall 2021, Spring 2023)

CPSC 66 - Machine Learning (Fall 2022)

CPSC 91.3 - Machine Learning and Brain-Computer Interfaces (Spring 2022)

CPSC 93 - Machine Learning Research Project (Fall 2022)

I am actively recruiting motivated students interested in Machine Learning or Neuroscience.

Please see this Research Talk Fall 2022 for an overview of my recent research.

Our research lab currently has fifteen students (and fifteen Brain-Computer Interfaces headsets).

My publications are here: Google Scholar and Research Gate.

More details are on our Research Team Website.

Three Full-Time Research Students, Summer 2022:

Abdelrahman Abdelmonsef, Brian Xiang, and Tianyi (Jonathan) Wang.

Funded by Swarthmore Summer Research Opportunities

Congratulations!

Abdelrahman Abdelmonsef and Brian Xiang got a paper accepted at KDD 2022 Undergraduate Consortium, SIGKDD, the top conference in Data Mining and Analysis.

Too Fine or Too Coarse? The Goldilocks Composition of Data Complexity for Robust Left-Right Eye-Tracking Classifiers

More Student Papers

(Selected from HCI International, one of the top twenty conferences in Human Computer Interaction)

S014: Advances in Augmented Cognition - I

It’s Easy as ABC Framework for User Feedback, Sydney Levy, Alexandra Fischmann

High-Powered Ocular Artifact Detection with C-LSTM-E, Ian McDiarmid-Sterling, Luca Cerbin

Single-Subject vs. Cross-Subject Motor Imagery Models, Joseph Geraghty, George Schoettle

ML vs DL: Accuracy and Testing Runtime Trade-offs in BCI, Anarsaikhan Tuvshinjargal, Elliot Kim

S045: Advances in Augmented Cognition - IΙ

Vector-Based Data Improves Left-Right Eye-Tracking Classifier Performance After a Covariate Distributional Shift, Brian Xiang, Abdelrahman Abdelmonsef

CNN with Self-Attention in EEG Classification, Xuduo Wang, Ziji Wang

Optimizing ML Algorithms under CSP and Riemannian Covariance in MI-BCIs, Yang Windhorse, Nader Almadbooh

S089: AI for Human Cognition, Emotions, and Physiology

Using Machine Learning to Determine Optimal Sleeping Schedules of Individual College Students, Orlando Azuara Hernandez, Zachary Gillette

Hierarchical Binary Classifiers for Sleep Stage Classification, Kenneth Barkdoll, Erebus Oh

(Selected, more details are on my Google Scholar page and Research Gate page)

Yi, Long, and Xiaodong Qu. "Attention-Based CNN Capturing EEG Recording’s Average Voltage and Local Change." In International Conference on Human-Computer Interaction, pp. 448-459. Springer, Cham, 2022. Paper, Slides

Wang, Ruyang, and Xiaodong Qu. "EEG Daydreaming, A Machine Learning Approach to Detect Daydreaming Activities." In International Conference on Human-Computer Interaction, pp. 202-212. Springer, Cham, 2022. Paper, Slides

Dou, Guangyao, Zheng Zhou, and Xiaodong Qu. "Time Majority Voting, a PC-based EEG Classifier for Non-expert Users." In International Conference on Human-Computer Interaction, 2022, Late Breaking Work. PDF File, Slides

Zhou, Zheng, Guangyao Dou, and Xiaodong Qu. "BrainActivity1: A Framework of EEG Data Collection and Machine Learning Analysis for College Students." In International Conference on Human-Computer Interaction, 2022, Late Breaking Work. Paper, Poster

Qu, Xiaodong, and Timothy J. Hickey. "EEG4Home: A Human-In-The-Loop Machine Learning Model for EEG-Based BCI." In International Conference on Human-Computer Interaction, pp. 162-172. Springer, Cham, 2022. PDF File, Slides

Qu, Xiaodong, Peiyan Liu, Zhaonan Li, and Timothy Hickey. "Multi-class Time Continuity Voting for EEG Classification." In International Conference on Brain Function Assessment in Learning, pp. 24-33. Springer, Cham, 2020. Best Paper Award, PDF File

Qu, Xiaodong, Qingtian Mei, Peiyan Liu, and Timothy Hickey. "Using EEG to distinguish between writing and typing for the same cognitive task." In International Conference on Brain Function Assessment in Learning, pp. 66-74. Springer, Cham, 2020. PDF File

Qu, Xiaodong, Saran Liukasemsarn, Jingxuan Tu, Amy Higgins, Timothy J. Hickey, and Mei-Hua Hall. "Identifying clinically and functionally distinct groups among healthy controls and first episode psychosis patients by clustering on EEG patterns." Frontiers in psychiatry (2020): 938. PDF File

Qu, Xiaodong, Yixin Sun, Robert Sekuler, and Timothy Hickey. "EEG markers of STEM learning." In 2018 IEEE Frontiers in Education Conference (FIE), pp. 1-9. IEEE, 2018. PDF File

Qu, Xiaodong, Mercedes Hall, Yile Sun, Robert Sekuler, and Timothy J. Hickey. "A Personalized Reading Coach using Wearable EEG Sensors." Presentation In Analytics in Education Environments (A2E2018). PDF File

Chair the following sessions in HCI International 2022:

Department Representative (Computer Science, 2022-23) of Sigma Xi