Faculty Profiles

Dr. Kecheng Yang

Ph.D., Computer Science, University of North Carolina at Chapel Hill, 2018.

Yang, Kecheng (Principal). CAREER: Predictable Real-Time Computing in the Presence of Unpredictabilities, National Science Foundation (NSF), Federal, $587080. (Submitted: July 2024, Funded: July 2025 - June 2030). Grant.
Yang, Kecheng (Principal), Ngu, Hee Hiong (Co-Principal), Chen, Xiao (Supporting), Islam, Tanzima Z (Supporting), Metsis, Vangelis (Supporting), Hou, Tao (Supporting), Rathore, Heena (Supporting), Wang, Lu (Supporting), Queiroz de Farias, Mylene Christine (Supporting), Qasem, Apan Muhammad (Supporting). REU Site: Research Experiences for Undergraduates in Edge Computing, National Science Foundation (NSF), Federal, $389995. (Submitted: August 2021, Funded: March 1, 2022 - February 28, 2026). Grant.
Yang, Kecheng (Principal). Real-Time Scheduling Algorithms and Analysis for ROS2 Systems, Texas State University, Texas State University, $8000. (Submitted: October 2021, Funded: January 2022 - May 2023). Grant.
Yang, Kecheng (Principal). CRII: CNS: Supporting Mixed-Criticality Real-Time Systems on Heterogeneous Platforms, National Science Foundation (NSF), Federal, $175000. (Submitted: October 2020, Funded: July 1, 2021 - June 30, 2025). Grant.
Yang, Kecheng (Principal). Mixed-Criticality Scheduling in Compositional Real-Time Systems, Texas State University, Texas State University, $8000. (Submitted: October 2018, Funded: January 2019 - December 2020). Grant.

Ratul, I. J., Zhou, Y., & Yang, K. (2025). Accelerating Deep Learning Inference: A Comparative Analysis of Modern Acceleration Frameworks. Electronics, 14(15), 2977:1-2977:20. https://doi.org/10.3390/electronics14152977
Ratul, I. J., Guo, Z., & Yang, K. (2025). Cascading IDK Classifiers to Accelerate Object Recognition While Preserving Accuracy. In Proceedings of the 49th IEEE Annual Computers, Software, and Applications Conference (COMPSAC) (pp. 1522–1525). IEEE. https://doi.org/10.1109/COMPSAC65507.2025.00194
Agrawal, K., Baruah, S., Guo, Z., Li, J., Reghenzani, F., Yang, K., & Zhao, J. (2025). Faster Classification of Time-Series Input Streams. In Proceedings of the 37th Euromicro Conference on Real-Time Systems (ECRTS) (p. 13:1-13:22). Schloss Dagstuhl. https://doi.org/10.4230/LIPIcs.ECRTS.2025.13
Agrawal, K., Baruah, S., Guo, Z., Li, J., Reghenzani, F., Yang, K., & Zhao, J. (2025). Faster Classification of Time-Series Input Streams (Artifact). Dagstuhl Artifacts Series (DARTS), 4:1-4:3. https://doi.org/10.4230/DARTS.11.1.4
Reghenzani, F., Agrawal, K., Baruah, S., Guo, Z., Li, J., Yang, K., & Zhao, J. (2025, May). Scripts for the article “Faster Classification of Time-Series Input Streams.” Zenodo. Zenodo. https://doi.org/10.5281/zenodo.15429421

Award / Honor Recipient: CAREER Award, National Science Foundation (NSF). 2025
Award / Honor Recipient: CRII Award, National Science Foundation (NSF). 2021
Award / Honor Recipient: Outstanding Paper Award, 40th IEEE Real-Time Systems Symposium. 2019
Award / Honor Recipient: Best Student Paper Award, 40th IEEE Real-Time Systems Symposium. 2019
Award / Honor Recipient: Schloss Dagstuhl - NSF Support Grant for Junior Researchers, Dagstuhl Seminar 19101, Schloss Dagstuhl and NSF. 2019