Cyber-Physical Systems Laboratory

The Cyber-Physical Systems Laboratory (CPSL) at Washington University performs cutting-edge research on AI and machine learning for healthcare, mobile health, real-time systems, Internet of Things, and cyber-physical systems that cross-cut computing and other disciplines.

• [News] Lu Wins Award for Most Influential Paper in Real-Time Systems
• [Paper] RT-TEE: Real-Time System Availability for Cyber-Physical Systems Using ARM TrustZone [SP'22]
• [Paper] Cross-trial Prediction of Depression Remission Using Problem-solving Therapy: A Machine Learning Approach [Journal of Affective Disorders]

• [News] Model Predicts Deterioration of Hospitalized Patients with Cancer (Healio)
• [News] That new Fitbit does more than count steps. It may save your life one day. (Diagnostic and Interventional Cardiology)
• [News] Research using Fitbit and machine learning to predict surgical outcomes (featured in the Next Byte podcast)
• [Paper] Personalized Surgical Transfusion Risk Prediction Using Machine Learning to Guide Preoperative Type and Screen Orders [Anesthesiology]
• [Paper] Predicting Physician Burnout Using Clinical Activity Logs: Model Performance and Lessons Learned [Journal of Biomedical Informatics]
• [Paper] Continuous Real-time Prediction of Surgical Case Duration Using a Modular Artificial Neural Network [British Journal of Anaesthesia]
• [News] Washington People: Chenyang Lu (WU Press)
• [News] Trackers Help Physicians Track Patient Health (WU Press)
• [News] Early Warning System Model Predicts Deterioration of Hospitalized Cancer Patients Based on Clinical Data (WU Press)
• [Editorial] Toward a Scientific and Engineering Discipline of Cyber-Physical Systems [TCPS]
• [Paper] Integrating Static and Time-Series Data in Deep Recurrent Models for Oncology Early Warning Systems [CIKM'21]
• [News] Dr. Chenyang Lu named Editor-in-Chief of ACM Transactions on Cyber-Physical Systems (03/2021)
• [News] Dr. Chenyang Lu named ACM Fellow (WU Press) (1/2021)
• [Talk] Digital Phenotyping with Wearables: Learning from Wearable Data to Predict Clinical Outcomes [Washington University School of Medicine]
• [Talk] Interdisciplinary Research: Advice and Opportunities [Guest lecture at UIUC]
• [Paper] Exploring Edge Computing for Multi-Tier Industrial Control [EMSOFT'20]
• [Paper] REACT: an Agile Control Plane for Industrial Wireless Sensor-Actuator Networks [IoTDI'20]
• [Paper] Adaptive Data Replication in Real-Time Reliable Edge Computing for Internet of Things [IoTDI'20]
• [News] PhD Student Openings in AI for Healthcare
• [Talk] Internet of Medical Things: Predicting Clinical Outcomes and Digital Phenotyping with Wearables and Machine Learning [Washington University School of Medicine]
• [Talk] Predicting Clinical Outcomes with Wearables: Machine Learning from Small Data [mHealth Research Core]
• [Talk] Machine Learning for Healthcare: From Wearables to Electronic Health Record [AI in Health, Washington University]
• [Paper] DeepAlerts: Deep Learning Based Multi-horizon Alerts for Clinical Deterioration on Oncology Hospital Wards [AAAI'20]

• News Archive