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Jean FanView profile

Assistant Professor

• Single-cell omics
• Spatial omics
• Computational biology
• +3 more

Jean Fan, PhD is an Assistant Professor of Biomedical Engineering at Johns Hopkins University, affiliated with the Center for Computational Biology and Institute for Computational Medicine. Her research focuses on developing machine learning methods to analyze spatially resolved and single-cell omics data. Her team, the JEFworks Lab, creates open-source tools for analyzing high-dimensional biological data to understand cellular identity, tissue organization, and disease progression. Dr. Fan's work bridges computational biology with clinical applications, particularly in leukemia and pediatric brain cancers. Education: BS in Biomedical Engineering & Applied Math from Johns Hopkins (2013); PhD in Bioinformatics from Harvard Medical School (2018); Postdoc in Chemical Biology/Physics at Harvard (2018–2020) under Xiaowei Zhuang, focusing on spatial transcriptomics. Research emphasizes spatial genomics and computational tool development, with key contributions to spatial alignment algorithms (STalign), normalization techniques, and cell-type deconvolution methods. Her lab's work has advanced understanding of kidney ischemic injury, glioblastoma spatial dynamics, and CLL pathogenesis. Awards include Forbes 30 Under 30, NSF CAREER Award, and 2025 PECASE. She founded CuSTEMized, a nonprofit providing STEM storybooks for girls. Recent collaborative projects include HuBMAP 3D reference atlas construction and Discovery Award-funded interdisciplinary initiatives. Labs/Teams: JEFworks Lab (primary); active collaborations with Dana-Farber Cancer Institute and Harvard Medical School. Current efforts focus on spatially resolved multi-omic integration and clinical translation of computational tools.

Gerd GrauView profile

Associate Professor

• Semiconductor devices
• Microfabrication
• Printed electronics
• +4 more

Gerd Grau is an Associate Professor of Electrical Engineering at York University, affiliated with the Lassonde School of Engineering and the Department of Electrical Engineering & Computer Science. He holds a BA and MEng from the University of Cambridge and a PhD from UC Berkeley (2016). His research focuses on semiconductor devices, microfabrication, printed electronics, and additive manufacturing, funded by NSERC, CIHR, Mitacs, and industry partners. He leads the Electronics Additive Manufacturing (E-AM) Lab, which integrates 3D printing and printed electronics for applications in biomedical devices, aerospace, and smart materials. Education: BA and MEng (University of Cambridge), PhD (UC Berkeley, 2016). Research interests include printed transistor devices, carbon fiber composites with integrated sensors, and machine learning optimization for printing processes. His lab houses advanced equipment like 3D printers, micro-inkjet systems, and characterization tools. Grau supervises a dynamic group of graduate and undergraduate students, with former advisees now leading roles in industry and academia. Teaching includes courses on semiconductor physics, nanoelectronics, and printed electronics. The E-AM Lab collaborates with Prof. Garrett Melenka on carbon fiber structural health monitoring and explores novel applications of laser-induced graphene for energy storage and environmental sensors.

Masato KikuchiView profile

Associate Professor

• Instructional Technology
• Intelligent Computer-Assisted Language Instruction (CALI)
• Japanese Language
• +4 more

Dr. Masato Kikuchi is an Associate Professor of Japanese in the School of Modern Languages at Georgia Tech. He holds a PhD from the University of Pittsburgh (1995), an M.S. in Intercultural Communication (1982), and a B.A. from International Christian University (1979). His research focuses on instructional technologies for language acquisition, particularly leveraging virtual worlds like Second Life for immersive Japanese learning. He has developed platforms such as the 'Sky Platform at EduNation III,' exploring 3D visualization for grammar concepts and comparative studies on 3D vs. 2D language learning tools. Dr. Kikuchi teaches advanced and intermediate Japanese courses, specializing in CALL (Computer-Assisted Language Learning), technical translation, and intercultural communication. His work emphasizes integrating technology into language education, including courseware design for online and hybrid learning environments. Recent projects include software for virtual world-based communicative practice and research on NMT (Neural Machine Translation) as a pedagogical tool. His publications span conference proceedings, courseware development, and software tools like the 'Understanding Written Japanese' CD-ROM series. He actively presents on topics such as virtual world design, information gap exercises, and Japanese course design. His research aligns with Georgia Tech’s focus on STEM-integrated language education and international collaborations.

Jonas BeskowView profile

Professor

• Multimodal Interaction
• Speech Synthesis
• Robotics
• +3 more

Jonas Beskow is a Professor and Head of Division at the Division of Speech, Music and Hearing at KTH Royal Institute of Technology. His research focuses on multimodal interaction, speech synthesis, robotics, and human-robot interaction. He leads the Learning style variation in nonverbal behaviour for social robots and agents project as part of Digital Futures, a cross-disciplinary research center. His work involves developing social robots like the Furhat head and advancing technologies for gesture synthesis, audio-driven motion, and adaptive intelligent systems. He holds roles as Co-PI for the Advanced Adaptive Intelligent Systems (AAIS) and Adaptive Intelligent Homes (AIH) projects. His research spans robotics, computer graphics, and clinical applications such as dementia detection through multimodal patient behavior analysis. Beskow also contributes to educational initiatives, supervising courses in computer science and engineering, including degree projects in machine learning and systems engineering. Publications highlight innovations in gesture generation, speech-driven animation, and socially-aware robotics. Collaborations with institutions like Stockholm University and RISE Research Institutes drive interdisciplinary solutions. His work bridges artificial intelligence, human-computer interaction, and assistive technologies, emphasizing ethical and societal impacts of emerging digital systems.

• Earthquake Geology
• Tectonic Geomorphology
• Structural Geology
• +3 more

Ramon Arrowsmith is a Professor at Arizona State University's School of Earth and Space Exploration (SESE). His research focuses on earthquake geology, tectonic geomorphology, and active faulting, with a particular emphasis on leveraging high-resolution topography through initiatives like OpenTopography. He has over 35 years of experience in paleoseismology, geomorphic mapping, and fault zone analysis. Arrowsmith has held administrative roles such as Deputy Director of SESE and associate directorships in graduate studies and geological sciences departments. His work integrates remote sensing, lidar technology, and robotics to address geological hazards and landscape evolution. Key projects include the QUAKES mission for topographic data collection and the development of low-cost seismic tools like ShakeBot. His research spans global regions, including the San Andreas Fault, Pamir-Tien Shan collision zone, and volcanic fields in Arizona and Mexico. Arrowsmith's recent publications highlight advancements in fault slip modeling, seismic hazard assessment, and open-access geospatial data platforms. His contributions to education include courses on field geology and computational methods in earth sciences. Collaborations with international teams and interdisciplinary projects underscore his commitment to advancing geoscience through innovation and accessibility.

• Computer Graphics
• Computer Vision
• Virtual Reality
• +7 more

Prof. Dr. Aljosa Smolic is a Professor and Co-Head of the Immersive Realities Research Lab at Lucerne School of Computer Science and Information Technology, Lucerne University of Applied Sciences and Arts. He joined HSLU in 2022 and became Co-Head in 2023. Previously, he served as SFI Research Professor at Trinity College Dublin (2016-2021) where he led the V-SENSE group in visual computing, combining computer vision, graphics, and media technology. His career includes positions as Senior Research Scientist at Disney Research Zurich (2009-2016) and Scientific Project Manager at Fraunhofer HHI (2001-2009). He holds a PhD from RWTH Aachen University. Research focuses on immersive technologies including AR/VR, volumetric video, light-fields, and deep learning applications in visual computing. His work has resulted in over 50 Disney R&D projects, publications, patents, and technology transfers. Publications emphasize VR evaluation, volumetric video applications, 3D reconstruction, and XR in education, frequently employing deep learning and computer vision techniques. Awards and Recognition: IEEE ICME Star Innovator Award 2020 TCD Campus Company Founders Award 2020 Multiple best paper awards Co-founded Volograms (volumetric video startup) and holds editorial roles including Associate Editor for IEEE Transactions on Image Processing.

Uwe GrünefeldView profile

Visiting Professor

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +5 more

Dr. Uwe Grünefeld is a Visiting Professor at the Faculty of Computer Science , Institute for Computer Science and Business Information Systems (ICB) of the University of Duisburg-Essen. He has been actively contributing to Human-Computer Interaction research through multiple publications in 2025-2022 focusing on Virtual Reality , Augmented Reality , and Robotics . Research Interests span across immersive technology applications for health behavior change (situated artifacts, weight visualization mirrors), haptic feedback systems (EMS for weight perception, vibrotactile directional cues), and behavioral biometrics (hand tracking identification, gaze-based user recognition). His work addresses cross-reality system design , collaborative robotics , and human-in-the-loop simulation methodologies . Key Publications demonstrate significant contributions to VR/AR user engagement, with particular focus on Physical activity promotion through situated artifacts Advanced haptic feedback techniques for immersive environments Behavioral biometric identification systems Robot motion intent communication Cross-reality transition visualization His research often employs mixed-method approaches combining technical implementations with user studies involving quantitative and qualitative data collection.

Oliver DeussenView profile

Professor

• Visualization
• Computer Graphics
• Digitalization Processes
• +4 more

Oliver Deussen is a Professor of Visual Computing at the University of Konstanz, recognized by the German Informatics Society (GSI) as a Fellow for his contributions to computer science. His research focuses on visualization, robotics, and environmental modeling, particularly in plant and landscape representation. He has pioneered methods in image manipulation and robotic painting, emphasizing digitalization's societal impacts. His work spans computational biology (e.g., schooling fish behavior) and AI-driven creative technologies. Research Interests: Visualization techniques, swarm behavior analysis, robotic creativity, and interdisciplinary applications of computer science. He explores how computational methods can model natural systems and enhance human-machine interaction. Awards: Fellow of the German Informatics Society (GSI) His research often bridges theory and practice, with contributions to SLAM frameworks, style transfer algorithms, and uncertainty visualization tools. Collaborations in robotics and biology reflect his commitment to applied computational research.

Guanghan MengView profile

Assistant Professor

• Physical Electronics
• Biosystems & Computational Biology
• Artificial Intelligence
• +3 more

Guanghan Meng is an Assistant Professor at the University of California, Berkeley , with dual appointments in the Herbert Wertheim School of Optometry and Vision Science and the Department of Electrical Engineering and Computer Science (EECS) . He leads the Visionary Optical Imaging Lab (VOILA) , focusing on interdisciplinary research combining optical physics and computational science to develop advanced microscopy technologies for eye and brain imaging. Education : PhD (2021, UC Berkeley), BE (2015, Shanghai Jiao Tong University) PhD Programs Affiliated With : Vision Science, Applied Science & Technology (AS&T), EECS His research integrates optical physics , computational biology , and artificial intelligence to create cutting-edge imaging tools. Recent work includes differentiable wave-optics libraries (Chromatix), super-resolution microscopy techniques, and high-speed neural imaging systems. Publications highlight applications in neuroscience (cerebral circulation, synaptic activity) and biomedical imaging (OCT, two-photon microscopy). VOILA is a highly interdisciplinary team spanning physics , engineering , and biology . In 2025, the lab will welcome 2 PhD students and 1 postdoc, though funding is currently at capacity for new members. Meng is affiliated with the Berkeley Artificial Intelligence Research Lab (BAIR) and Berkeley Center for Computational Imaging (BCCI) .

• Robotics
• Computer Vision
• Machine Learning
• +4 more

Nicolas RAGOT is an Associate Professor at CESI, affiliated with the Engineering and Numerical Tools department. He teaches Digital and embedded electronics, Microcontroller programming, System control, and Sensors at the Bachelor and Master levels. His research focuses on Environment perception for robotics and Computer vision, particularly in unconventional applications. He leads or collaborates on major research programs including ROJUNACO (2023–2025), FUSION (2023–2027), OASIS (2022–2024), and COLIBRY (2021–2024), all addressing robotics, digital twins, and industrial automation. He co-supervises PhD students Y. Feddoul, S. Ouarab, and S. Choudhary. His work spans smart mobility, assistive technologies, and energy-efficient systems. He is a member of the Secure Electronic Transactions (TES) competitiveness cluster's expert committee. Education: PhD in Computer Vision (University of Rouen, 2009), Master in Electrical Engineering (University of Paris XI, 2003), Engineering diploma (ESIGELEC, 1999). Research interests emphasize robot perception, human-robot collaboration, and extended reality integration. His publications span object detection, SLAM algorithms, and smart wheelchair systems. Current projects emphasize industrial robotics, digital twins, and real-time 3D reconstruction. Advising and grants include leadership roles in multiple research programs and co-supervision of three PhDs. His lab work focuses on Engineering and Numerical Tools, with contributions to CESI LINEACT's collaborative robotics initiatives.

Ruihui LiView profile

Professor

• Deep Geometry Learning
• Generative modeling
• 3D Vision
• +3 more

Ruihui Li - Academic Summary Professional Overview Prof. Ruihui Li is a faculty member at the College of Computer Science and Electronic Engineering, Hunan University , specializing in Deep Geometry Learning , Generative Modeling , and 3D Vision . His work focuses on advancing 3D reconstruction and generation with high controllability, particularly in applications like point cloud upsampling and neural rendering. Education & Career Dr. Li earned his Ph.D. in 2021 (oral defense passed in June 2021). His career includes significant contributions to research in geometric deep learning and 3D computer graphics. He actively collaborates with institutions like the Chinese University of Hong Kong and Tel Aviv University on projects such as PU-GAN and SP-GAN . Research Interests His research spans cutting-edge topics in: Neural Wavelet-Domain Diffusion for 3D Shape Generation Topology-Aware 3D Mesh Reconstruction Camera-Based 3D Scene Completion Point Cloud Analysis and Upsampling Professional Activities Dr. Li has delivered invited talks at prestigious events such as the Asia Graphics Webinar and Peking University . He serves as a reviewer for top conferences (CVPR, ICCV, ECCV) and journals (TPAMI, TVCG). His research is supported by grants from the National Natural Science Foundation of China and the Chinese Academy of Sciences. Technical Contributions Key projects include: PU-GAN : A point cloud upsampling adversarial network (ICCV 2019). SP-GAN : Sphere-guided 3D shape generation (SIGGRAPH 2021). Neural Wavelet-domain Diffusion : 3D shape generation and manipulation (TOG 2024). Labs & Teams He leads a research group at Hunan University, mentoring Ph.D./MPhil students, RAs, and postdocs. His team focuses on interdisciplinary projects combining AI, computer graphics, and geometric deep learning.

Hanan SametView profile

Professor

• Spatial Databases
• Data Structures
• Geographic Information Systems (GIS)
• +5 more

Hanan Samet is a Distinguished University Professor at the University of Maryland's Computer Science Department, affiliated with the Institute for Advanced Computer Studies (UMIACS) and the Center for Automation Research. He holds a Ph.D. from Stanford University (1975) and specializes in spatial databases, data structures, and geographic information systems. His research bridges computer science and geospatial analytics, with applications in image databases, computer vision, and spatio-temporal data management. Education: Ph.D., Computer Science, Stanford University, 1975 Research Interests: Focuses on spatial data structures, GIS, spatio-textual systems like NewsStand and CoronaViz, trajectory analysis, and metric indexing. His work emphasizes scalable algorithms for spatial networks and multimedia databases. Notable Projects: CoronaViz : Tracks disease spread via spatio-temporal data visualization NewsStand : Maps news articles geospatially SAND: Spatial browser for digital government Awards: ACM Paris Kanellakis Award (2014), IEEE McDowell Award (2015), UCGIS Research Award, and Fellowships in ACM/IEEE/AAAS. Recognized for advancing spatial database theory and practice. Grants/Advising: Leads NSF-funded projects on spatio-textual extraction and similarity search. Advises graduate students (e.g., Nicole Schneider, Montana Hoover) and undergraduate researchers. Labs/Teams: Active in UMIACS and the Center for Automation Research, collaborating on projects like VASCO (spatial visualization tools) and MARCO (image database systems).

Wei-Chen HungView profile

Professor

• Problem Solving
• Human-Computer Interaction
• Performance Support Systems
• +7 more

Wei-Chen Hung is a Professor and Department Chair in the Department of Educational Technology, Research and Assessment at Northern Illinois University’s College of Education. He holds a Ph.D. in Instructional Systems Technology from Indiana University-Bloomington and is actively engaged in teaching, research, and leadership in educational technology. Ph.D., Instructional Systems Technology, Indiana University-Bloomington (with Minor in Information Science) His research focuses on problem solving, human-computer interaction (HCI), and performance support systems in educational contexts. He explores how technology can scaffold learning, enhance problem-solving skills, and support teachers in instructional design and classroom management. His work spans K–12, higher education, and professional training environments. The recent publications highlight a strong trend in developing and evaluating technology-enhanced learning environments, including intelligent tutoring systems, 3D virtual worlds, educational simulations, and performance support tools. These works span disciplines such as STEM education, nursing, and social sciences, reflecting an interdisciplinary approach to solving instructional challenges through technology. Wei-Chen Hung has secured significant research funding from agencies including the National Science Foundation, NASA, and the Illinois Department of Education. He has served as Principal Investigator and Co-Principal Investigator on multiple grants focused on educational simulations, research methods training, and assistive technologies. National Science Foundation: Web-based Interactive Landform Simulation Model (WILSIM), $236,041, 2013–2016 (Senior Faculty Expert) Elgin Community College: Information security awareness, $10,000, 2011–2012 (Principal Investigator) National Science Foundation: Intelligent tutoring system for research methods, $150,000, 2008–2012 (Co-Principal Investigator) NASA: MARS Valley Networks Project, $20,000, 2005–2007 (Faculty Expert) Illinois Department of Education: Assistive technology for blind and visually impaired children, $75,000, 2005–2007 (Faculty Expert) He has contributed to the development of software tools and systems such as the Cause and Consequence behavior management system and performance support systems for educators. His lab and research initiatives emphasize applied design, usability testing, and evaluation of educational technologies in real-world settings.

Voicu S. PopescuView profile

Associate Professor

• Computer Graphics
• Visualization
• Computer Vision
• +3 more

Voicu S. Popescu is an Associate Professor of Computer Science at Purdue University, affiliated with the College of Science. He joined the department in 2001 and specializes in computer graphics, visualization, and computer vision. His research includes novel camera models for rendering complex visual effects, large-scale 3D environment modeling, and integrating distance education into on-campus systems. He holds a BS from the University of Cluj-Napoca (1995), and MS/PhD from the University of North Carolina (1999/2001). Research Interests: Developing photorealistic visualization techniques for large-scale simulations Camera models addressing occlusion and multiperspective rendering General-purpose visualization tools for scientific data Key Trends in Publications: Focus on camera geometry, large-scale data visualization, and interdisciplinary applications of computer graphics in education and simulation. Lab Affiliation: Purdue CS XR Lab

Jean F. Honorio CarrilloView profile

Adjunct Professor

• Machine Learning
• Artificial Intelligence
• Optimization Theory
• +5 more

Jean F. Honorio Carrillo is an Adjunct Professor at Purdue University's Department of Computer Science and a Senior Lecturer at the University of Melbourne's School of Computing and Information Systems. He specializes in machine learning theory, optimization, and their applications to combinatorial and non-convex problems. His research focuses on developing algorithms with theoretical guarantees for structured prediction, robustness, fairness, and federated learning. He has advised numerous students across multiple institutions and holds adjunct roles at Purdue's Statistics Department and MIT CSAIL. Roles: Senior Lecturer (Melbourne), Adjunct Professor (Purdue), Adjunct at MIT CSAIL Research Areas: ML Theory, Non-Convex Optimization, Fairness, Federated Learning Key contributions include breakthroughs in exact inference for structured prediction, optimization frameworks for NP-hard problems, and theoretical foundations for modern ML challenges. His work has been published in top venues like NeurIPS, ICML, and JMLR. He has secured grants from NSF and industry partners, including a 2021 NSF DMS grant for deep learning research. His students have gone on to postdoctoral roles at NUS and UChicago/CMU.