Welcome to Machine Learning and Deep Learning (MLDL) Lab!

Machine Learning and Deep Learning (MLDL) Lab was founded in October 2017 to foster “undergraduate research” in exploring modeling, simulation, and analysis of complex information network such as the web and the internet and studying human network users or artificial agents' (e.g., bots) behaviors by using an efficient and effective algorithm for machine learning, which is an extension of multi-task automation paradigm.  MLDL Lab is composed of dedicated people (Dr. Ka-wing Wong, Dr. Shuangteng Zhang, Dr. Mengkun Yang, Dr. Dae Wook Kim, and Mr. Alex Dixon) and undergraduate students (mostly, junior or senior students) in Artificial Intelligence (AI) and its closely related areas from digital forensics, cybersecurity, computational social science, and data science.

The MLDL Lab student members were funded by EKU College of Science (Faculty Startup Fund, Junior Faculty Summer Research Award, Battelle-EKU Science Scholars Program), EKU Sponsored programs (Faculty Mini-Grants), NVIDIA GPU Grant program and NSF Fund (NSF REU Cybersecurity Research Program Award).  These independent grants and awards supported the MLDL Lab students’ research and scholarly projects, resulting in their achieving multiple poster presentation opportunities at the domestic conferences and events (e.g., NSF REU Cybersecurity Research Program, ACM Southeast Conference, NCHC Annual Conference, Poster-at-the-Capitol event, EKU University Presentation Showcase of Scholars, etc.).

The mission of the MLDL Lab is to provide undergraduate students with strong hands-on capabilities for independent research work and learning experiences in the areas of AI. 

For EKU graduate students: if you are interested in working with us, please contact us via daewook.kim@eku.edu (or ka-wing.wong@eku.edu).