Lu Niu

I am currently pursuing a Ph.D. in Computer Science at the University of Notre Dame, working under the advisement of Dr. Patrick Flynn. My research spans computer vision, machine learning, signal processing, and biometrics. My primary focus is on applying advanced deep learning methods to extensive video datasets for predicting remote photoplethysmography (rPPG) signals. This research supports projects in pulse rate estimation, blood pressure estimation, and spoof detection through windshield to distinguish real from printed faces inside the moving vehicles. Beyond my core research, I am also exploring AI-generated content (AIGC), developing an integrated AI system that leverages various Large Language Models (LLMs) and Vision-Language Models (VLMs) to advance content creation.

In my free time, I enjoy swimming, and exploring trails. I love music and enjoy playing the piano and accordion.

Publications

Full-Body Cardiovascular Sensing with Remote Photoplethysmography
Lu Niu, Jeremy Speth, Nathan Vance, Benjamin Sporrer, Adam Czajka, Patrick Flynn
in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshop (CVPRW) on Computer Vision for Physiological Monitoring (CVPM), 2023 (best paper award)

Hallucinated Heartbeats: Anomaly-Aware Remote Pulse Estimation
Jeremy Speth, Nathan Vance, Benjamin Sporrer, Lu Niu, Patrick Flynn, Adam Czajka
The 16th International Joint Conference onBiomedical Engineering Systems and Technologies: BIOSIGNALS, ISBN 978-989-758-631-6, pp. 106-117, 2023 (shortlisted for best student paper award)

Mspm: A multi-site physiological monitoring dataset for remote pulse, respiration, and blood pressure estimation
Jeremy Speth, Nathan Vance, Benjamin Sporrer, Lu Niu, Adam Czajka, Patrick Flynn
IEEE Transactions on Instrumentation and Measurement, 2024