Alexander Schwing

Alexander Schwing is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC), with affiliations to the Coordinated Science Laboratory and the Computer Science Department. His research focuses on machine learning, computer vision, and structured prediction, emphasizing algorithms for deep networks, multivariate distributions, and 3D scene understanding. He has held postdoctoral positions at the University of Toronto and completed his PhD at ETH Zurich.

• Educations:
• PhD in Computer Science (ETH Zurich, 2014)
• Diploma in Electrical Engineering & IT (Technical University of Munich, 2010)

Research interests include generative modeling, embodied agents, video segmentation, and reinforcement learning. He has developed influential frameworks like XMem for video object segmentation and MaskRNN for instance-level tracking. His work emphasizes reproducibility and open-source releases.

Key awards include the NSF CAREER Award, Amazon Research Award, and NVIDIA GPU donations. He has advised over 25 students, many of whom have pursued roles at top tech firms and academia.

Current research explores structured prediction, multi-agent systems, and 3D reconstruction. His labs collaborate with industries like Samsung and Adobe, and he teaches courses on machine learning and pattern recognition.