معرفی
Fang Jin is an Associate Professor in the Department of Statistics at George Washington University (2020–present), previously serving as Assistant Professor in the Department of Computer Science at Texas Tech University (2017–2020). He holds expertise in Deep Learning Interpretation, Explainable AI, Machine Learning, and Social Network Analysis. His work bridges artificial intelligence with healthcare applications, neurotechnology, and disaster response systems.
Research interests include interpretable segmentation algorithms for Alzheimer's diagnosis, wearable neurostimulation devices, and adversarial detection in machine learning systems. He actively develops frameworks for TMS coil placement optimization and opioid relapse prevention through social media analysis. His platforms include an interactive COVID-19 tracking system and a data-driven approach for post-disaster recovery analysis.
Publications span medical AI, reinforcement learning, and social media epidemiology, with notable contributions to explainable AI in healthcare and disaster management. His work integrates statistical methodology with cutting-edge neural network architectures, emphasizing real-world clinical and societal applications.
