Feng Liu

Dr. Feng Liu is an Assistant Professor at the Department of Systems and Enterprises within the Charles V. Schaefer, Jr. School of Engineering and Science at Stevens Institute of Technology. He holds a PhD in Industrial Engineering from the University of Texas at Arlington (2018), and postdoctoral training at MGH/Harvard Medical School and MIT's Picower Institute. His research focuses on AI-driven healthcare solutions, brain imaging, optimization, and dynamical systems. Notable contributions include developing the first fine-tuned LLM for epilepsy analysis and pioneering work in EEG/MEG source localization using graph-based deep learning.

• Education:
  • PhD, Industrial Engineering, University of Texas at Arlington (2018)
  • MS, Electrical Engineering/Control Science, Huazhong University (2013)
  • BS, Electrical Engineering/Control Systems, Qingdao University (2010)

Research interests span AI for healthcare, brain networks, epilepsy, optimization, and chaos theory. He has led NIH-funded projects on deep learning for sleep apnea and epileptic network modeling. Awards include Best Paper Awards at Brain Informatics (2018) and INFORMS (2019), and 3rd place in the Defense Data Grand Prix (2023).

His lab develops cutting-edge tools for medical imaging and predictive analytics, with applications in oncology, chronic disease, and renewable energy systems. Active roles include editorial positions in journals like Machine Learning with Applications and NIH panel reviewing.