Difference between revisions of "Cyber-Physical Systems Laboratory"
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The Cyber-Physical Systems Laboratory (CPSL) at [http://www.wustl.edu/ 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. | The Cyber-Physical Systems Laboratory (CPSL) at [http://www.wustl.edu/ 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. | ||
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== Updates == | == Updates == | ||
Revision as of 02:56, 13 October 2022
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.
Updates
- [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]
