معرفی
Christopher K. May is an Assistant Teaching Professor in the Department of Computer Science at Purdue University, joining in Fall 2024. He holds a B.S., M.S., and Ph.D. in Computer Science from Purdue University, all completed between 2013 and 2024. His research focuses on computer vision, generative adversarial networks (GANs), and 3D rendering techniques, particularly in omnidirectional image synthesis and satellite imagery analysis.
His educational background includes a decade of study at Purdue University, culminating in his doctorate in 2024. His work spans applications such as video frame interpolation, facade synthesis from satellite data, and interactive 3D rendering optimization. His research often intersects machine learning and computer graphics, addressing challenges in synthetic image generation and geospatial data processing.
Dr. May's publications reflect a strong emphasis on generative models, with recent work exploring explicit camera control in omnidirectional synthesis (EpipolarGAN, 2024) and cube-based GAN architectures (CubeGAN, 2023). Earlier contributions include video folding techniques for framerate enhancement (2021) and satellite-based 3D building regularization (2020).
No scientific awards or grants are explicitly listed in the provided information. His current position emphasizes teaching responsibilities alongside research.
