
Bio
Dr. Letu Qingge, Ph.D, is an Assistant Professor in the Department of Computer Science at North Carolina A&T State University (NCAT), NC. His research interests include algorithms and combinatorial optimization, machine learning and deep learning, bioinformatics and computational biology, image processing and computer vision, transportation and neural network control. His papers received ISBRA 2024 Best Paper Award at the 20th International Symposium on Bioinformatics Research and Application (ISBRA 2024), BICOB 2024 Best Paper Award Finalist at the 16th International Conference on Bioinformatics and Computational Biology (BICOB 2024) and IEEE UEMCON 2023 Best Paper Award at the IEEE 14th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON 2023). His research has been funded by NSF and NIH. Dr. Qingge is a director of Bioinformatics and Artificial Intelligence Lab (BioAI Lab) at NCAT.
External URL
https://letuqingge.github.io/research-group-app/
Recent Publications
- Richard Annan, Letu Qingge (2025). (Federated Learning for COVID-19 Detection: Optimized Ensemble Weighting and Knowledge Distillation). 2024 IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM).
- Jordan Sturtz, Kushal Kalyan Devalampeta Surendranath, Maxwell Sam, Xingang Fu, Chanakya Dinesh Hingu, Rajab Challoo, Letu Qingge (2024). (Accelerating the neural network controller embedded implementation on fpga with novel dropout techniques for a solar inverter). Pervasive and Mobile Computing, Elsevier.
- Guodong Li, Letu Qingge, Qingyi Pan, Pei Yang (2024). (Edge-Guided Mural Image Inpainting by Integrating Local and Global Information and Multiple Color Spaces). 2024 IEEE International Conference on Multimedia and Expo (ICME).
- Richard Annan, Hong Qin, Xiaohong Yuan, Kaushik Roy, Robert Newman, Letu Qingge (2024). (Efficient Federated Learning with Multi-Teacher Knowledge Distillation for COVID-19 Detection). ACM BCB '24: Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM BCB 2024)).
- Letu Qingge, Kushal Badal, Richard Annan, Jordan Sturtz, Xiaowen Liu, Binhai Zhu (2024). (Generative AI Models for the Protein Scaffold Filling Problem). Journal of Computational Biology.
- Kushal Badal, Letu Qingge, Xiaowen Liu, Binhai Zhu (2024). (Probabilistic and Machine Learning Models for the Protein Scaffold Gap Filling Problem). The 20th International Symposium on Bioinformatics Research and Application (ISBRA 2024), Springer Nature Singapore.
- Zexin Wang, Letu Qingge, Qingyi Pan, Pei Yang (2024). (Retinex decomposition based low‐light image enhancement by integrating Swin transformer and U‐Net‐like architecture). IET Image Processing.
- Ning Guo, Letu Qingge, YuanChen Huang, Kaushik Roy, YangGui Li, Pei Yang (2023). (Blind Image Quality Assessment via Multiperspective Consistency). International Journal of Intelligent Systems.
- Abdulrahman Alrajhi, Kaushik Roy, Letu Qingge, James Kribs (2023). (Detection of Road Condition Defects Using Multiple Sensors and IoT Technology: A Review). (IEEE Open Journal of Intelligent Transportation Systems) IEEE.
- Xingang Fu, Jordan Sturtz, Eduardo Alonso, Rajab Challoo, Letu Qingge (2023). (Parallel Trajectory Training of Recurrent Neural Network Controllers With Levenberg–Marquardt and Forward Accumulation Through Time in Closed-Loop Control Systems). IEEE Transactions on Sustainable Computing.