Klaus Mueller

Director, Visual Analytics and Imaging (VAI) Lab
Liaison, SUNY Korea CS Program
(Interim) Chair, Department of Tech and Society

Center for Visual Computing
Computer Science Department
Stony Brook University - State University of New York

Contact: mueller@cs.stonybrook.edu

Quick Bio

I received a PhD in computer science from The Ohio State University in 1998. I am currently a professor in the Computer Science Department at Stony Brook University and I am also a senior scientist at the Computational Science Initiative at Brookhaven National Lab. I currently serve as the interim chair of the Department of Tech and Society. From 2012-2015, I served as the founding chair of the Computer Science Department at SUNY Korea and I was also VP for Academic Affairs and Finance at SUNY Korea for two years. My current main research interests are visual analytics, explainable machine learning and AI, algorithmic fairness and transparency, data science and computational and medical imaging. I won the US National Science Foundation Early Career award in 2001, the SUNY Chancellor Award for Excellence in Scholarship and Creative Activity in 2011, and the Meritorious Service Certificate and the Golden Core Award of the IEEE Computer Society in 2016. In 2018 I was inducted into the US National Academy of Inventors. To date, I have authored more than 300 peer-reviewed journal and conference papers, which have been cited more than 13,000 times. I am a frequent speaker at international conferences, have organized or participated in 18 tutorials on various topics, chaired the IEEE Visualization Conference in 2009, was the elected chair of the IEEE Technical Committee on Visualization and Computer Graphics (VGTC) from 2012-2015, and served as the Editor-in-Chief of IEEE Transactions on Visualization and Computer Graphics from 2019-2022. I am a Fellow of the IEEE. (Please see here for a bio in the third person and here is a real pic of me).

Research Interests
research word art Visual analytics -- Visualization, visual data science, visual storytelling, explainable AI, infovis, HCI
Computational fairness: Human in the loop bias detection, exploration, and mitigation
Computational imaging -- Computed tomography, low-dose, GAN-synthesis, GPU-acceleration
Volume visualization -- Medical and scientific visualization, multivalued data w/geo-reference
Virtual reality -- Virtual, augmented, mixed reality, display walls, immersive visualization
Cognitive computer graphics -- Color, texture, details, points, perception, cognition, semiotics
Filters and grids -- Sampling, hexagonal amd body-centerered lattices, extensions to N-D
Eyetracking -- Visualization for eye tracking data, acquisition, applications
Natural phenomena -- Simulation, urban security applications,GPU-acceleration
Face recognition (this is no longer an active research topic)
All my publications via Google Scholar

Recent Developments


Stars of CSE 564 Spring 2023: Check out this playlist for videos of the best projects of this year's grad visualization course
Recent papers on visual analytics and explainable AI published or accepted:
  Won Best Paper at the Visual Analytics in Healthcare Workshop at AMIA 2022 for our COVID-19 Risk Explorer
  Don't trust your causal models? Audit them with ChatGPT, described in our NLVIZ 2023 Workshop paper
  Presented three TVCG papers at IEEE VIS 2023 in Melbourne, Australia:
  - Temporal causal reasoning with DOMINO (final chapter of Jun Wang's PhD thesis)
  - Multivariate volume rendering with RadVolViz (final chapter of Ayush Kumar's PhD thesis)
  - Interactive subspace analysis with Semantic Subspace Clustering (final chapter of Salman Mahmood's PhD thesis)
  Debiasing data can be tricky: See our new ACM CIKM paper on Cascaded Debiasing
Recent papers on machine learning in medical imaging and computed tomography:
  Our Nature MI article on the Metaverse for Intelligent Healthcare is published as a Perspectives article
  Guest Editorial in IEEE Trans. on Medical Imaging: Image Reconstruction Is a New Frontier of Machine Learning with G. Wang, J. Fessler, and J. C. Ye
  Synthesizing CT images of artificial humans: see how we do it in our new Fully 3D Reconstruction paper with A. Krishna, S. Yenneti, and G. Wang

Teaching Portfolio


CSE 332 Introduction to Visualization (undergraduate level) CSE 591 GPU Programming (Special Topics course)
CSE 377 Introduction to Medical Imaging (undergraduate level) CSE 577 Medical Imaging (graduate level)
CSE 323 Human Computer Interaction (co-taught at graduate level) CSE 523 Master's Projects (continued as CSE 524)
CSE 564 Visualization and Visual Analytics (graduate level) CSE 648 Visual Analytics Seminar (every semester)
CSE 590 Data Science Fundamentals (graduate level) More... Complete set of courses

Also known as Klaus Müller (German spelling)