R.K. Shyamasundar is a Professor at the Indian Institute of Technology Bombay , with a focus on Real-Time and Reactive Programming, Logic Programming, Pi-Calculus, and Parallel Programs. Research spans formal verification, concurrency, and distributed systems. Key contributions include RT-CDL semantics, Esterel language extensions, and hybrid system controller synthesis. Scientific awards include JC Bose National Fellow, Fellowships at Indian Academy of Sciences and Indian National Science Academy, and Senior Membership in IEEE. His work involves collaborations with institutions like TCS Group and researchers such as Basant Rajan, N. Raja, and Deepak Kapur.
Dr. Daniel Berio is a researcher at Goldsmiths, University of London, specializing in computational models for human-like movement in digital art and robotics. His work bridges computer graphics, cognitive psychology, and robotic manipulation, focusing on stylized stroke generation, graffiti analysis, and kinematic modeling. He collaborates with Frederic Fol Leymarie and Rejean Plamondon, utilizing the Sigma Lognormal model to simulate human handwriting dynamics. Education : Doctoral thesis on AutoGraff (2021), exploring computational understanding of graffiti and calligraphy. Research Themes : Human-like motion in digital art, kinematic reconstruction from static traces, robotic graffiti generation, and perceptual fluency in aesthetic evaluation. Publications : 15+ works since 2015, spanning ACM Transactions on Graphics, British Journal of Psychology, and conferences like MOCO and IROS. Applications : Font stylization tools, synthetic graffiti generation, compliant robot control, and semantic typography systems.
Tino Weinkauf is a Professor of Visualization and Head of the Division of Computational Science and Technology at KTH Royal Institute of Technology in Stockholm. His work bridges computer science and applied mathematics, with a focus on visualization and topological data analysis. He leads research in visualizing complex data from fields like fluid dynamics, neurobiology, and human-computer interaction. Education: Ph.D. in Computer Science (not explicitly stated in provided texts, but inferred from career trajectory). Research interests include flow visualization, topological methods for data analysis, and interactive visualization techniques. He develops tools like the TopoInVis Toolkit (TTK) and contributes to infrastructure such as the Swedish Research Infrastructure for Visualization Support (InfraVis). His work emphasizes applications in turbulence modeling, biomedical imaging, and user-centered design. Teaching: Responsible for courses such as Advanced Topics in Visualization and Computer Graphics , Information Visualization , and Introduction to Visualization and Computer Graphics . Supervises degree projects in Computer Science and Engineering across specializations like Machine Learning and Interactive Media Technology. Publications focus on topological data analysis, flow segmentation, and algorithm optimization. Notable projects include binary segmentation of turbulent flows and interactive reward tuning systems for preference elicitation. Labs/Teams: Leads the Division of Computational Science and Technology at KTH, fostering interdisciplinary research in computational methods and visualization technologies.
Zoe Taylor is a Senior Lecturer in Illustration at the University of Northampton, School of Art & Design, where she has been teaching since 2013. She has also served as a visiting lecturer at the Royal College of Art. Her work bridges academic research and professional illustration, with international exhibitions and publications. Education: MA in Communication Art and Design, Royal College of Art (2007–2009) BA in Illustration, University of the Arts London (2004–2007) BA in Ancient History and Archaeology, University College London (1999–2002) Zoe’s research focuses on visual narrative, cinematic drawing, lo-fi aesthetics in graphic art, fashion illustration, and the migration of icons across avant-garde and pop cultures. Her work interrogates themes of wonder, myth, romanticism, and the enduring relevance of the printed book. She explores narrative fragmentation and emotional resonance in both personal and commercial contexts. Her recent creative and scholarly outputs span comics, editorial illustrations, exhibitions, and digital media. The articles reflect a consistent engagement with experimental storytelling, fashion illustration, and critical analysis of contemporary graphic artists. Her work often blends autobiography with cultural critique, particularly in the realms of comics and fashion. Scientific and Professional Recognition: Contributing Editor, Varoom! The Illustration Report (2014–2020) Exhibitions at Angoulême International Comics Festival, New York Art Book Fair, Somerset House, and World Design Capital Taipei Published by Breakdown Press and featured in The Guardian , New York Times , Paris Review Collaborations with Chanel, Marc by Marc Jacobs, Luella, and Gucci campaigns Zoe Taylor advises on visual culture and illustration trends through her editorial work and public lectures. She has received no explicitly mentioned grants, but her externally funded activities include international exhibitions and media features. Her professional network includes institutions like the Royal College of Art, University of the Arts London, and Centre Pompidou. She is actively involved in creative teams and collectives through anthology contributions (Landfill Editions, Otto Press, Lagon) and collaborative projects. Her future work continues to explore the boundaries of drawing as a narrative and critical medium.
Christina Sormani is a Professor in the Department of Mathematics at Lehman College, City University of New York (CUNY), and a doctoral faculty member at the CUNY Graduate Center. She has been a key figure in geometric analysis since joining Lehman College in Spring 2000. Her research spans Riemannian geometry, metric spaces, and geometric measure theory, with a focus on the intrinsic flat distance, a concept she co-developed with Stefan Wenger. She has held visiting positions at prestigious institutions including the Institute for Advanced Study (IAS), Simons Center for Geometry and Physics (SCGP), and MSRI. Her education includes a PhD from the Courant Institute (1996), followed by postdoctoral positions at Johns Hopkins and Harvard University. She is deeply committed to mentoring and outreach, especially for underrepresented groups in mathematics. Sormani’s research interests center on convergence of Riemannian manifolds, particularly in contexts involving scalar curvature, Ricci curvature, and general relativity. She investigates the stability of geometric theorems such as the Positive Mass Theorem and scalar rigidity results using intrinsic flat convergence. Her work often involves constructing explicit examples, analyzing limit spaces, and proving compactness theorems. She has organized major workshops like VWRS and long programs at SCGP and Fields Institute. Her publications reveal a consistent focus on intrinsic flat convergence, its applications in general relativity, and its interplay with other notions like Gromov-Hausdorff and measured Gromov-Hausdorff convergence. The articles show a trend toward geometric stability, limit spaces with singularities, and the behavior of scalar curvature under weak convergence. She has received significant recognition for her work and service: Fellow of the American Mathematical Society (2015) Fellow of the Association for Women in Mathematics (2024) Sormani has advised numerous doctoral students and postdocs, including Dan Lee, Sajjad Lakzian, Raquel Perales, and Brian Allen. She has secured research funding from the NSF and PSC-CUNY. Her outreach includes organizing the "Inspiring Talks in Mathematics" lecture series and maintaining online resources for underrepresented mathematicians. She is actively involved in editorial boards and professional committees, contributing to the broader mathematical community. She is affiliated with research groups and teams focused on geometric analysis, scalar curvature, and convergence, including collaborations with Misha Gromov, Stefan Wenger, and others. Her recent work explores spacetime intrinsic flat convergence and null distances in Lorentzian geometry.
Pr. Jean-François Lalande is a Professor at CentraleSupélec, affiliated with Inria's PIRAT and CIDRE teams. His research focuses on the security of IT infrastructures, Android applications, and C embedded software, including access control policies, intrusion detection tools, and software code analysis. He has led projects like PEPR DefMal (2022–2028) and ANR LYRICS (2011–2015) for privacy-preserving cryptographic protocols in NFC systems. Roles: Conference Chair (EICC 2025, EICC 2020), Workshop Organizer (IWSMR, 3SL, COLSEC, SHPS). Editorial: Guest Editor for journals like Information Technology and Future Generation Computer Systems . His work spans malware analysis, privacy in mobile systems, and security validation. He has served on technical program committees for international conferences (IEEE, ACM) and national events like SSTIC. His students include PhD graduates such as Romain Brisse and Tomas Miranda Concepcion.
David Hovemeyer is an Associate Teaching Professor at the Whiting School of Engineering, Johns Hopkins University . He holds a PhD (2005) and MS (2001) in Computer Science from the University of Maryland and a BA (1994) from Earlham College. Prior to joining JHU in 2019, he taught at Vassar College and York College of Pennsylvania. Education : PhD, MS, and BA in Computer Science Research : Focuses on static analysis , systems software , and computer science education Projects : FindBugs, CloudCoder, ProgSnap2, FunWithSound His recent work includes frameworks for declarative autograders , formats for programming process data , and tools for educational software development . He has been recognized with Excellence in Teaching Awards and contributes to open-source educational platforms like GitHub. Scientific Awards : 2024 Whiting School Teaching, Advising, and Mentoring Award Excellence in Teaching Award (multiple years) David maintains an active role in the academic community through peer instruction , programming contests, and recommendation letter advising . He also develops tools like FreePoll and Declarative Autograder Framework to enhance teaching efficiency.
Jennifer Nelson is a Senior Lecturer in the Department of Earth, Atmospheric, and Planetary Sciences at Purdue University, located in West Lafayette, Indiana. Her office is situated in HAMP 4284. She is affiliated with the College of Science and maintains active research in human-virtual interaction systems. Her research focuses on understanding how humans interact with virtual environments, particularly in crowded scenarios. Key themes include analyzing avoidance behaviors in response to virtual characters, studying the effects of rendering styles on human movement, and developing frameworks to model human-crowd interactions in immersive virtual reality settings. Recent work emphasizes the impact of virtual character dynamics (speed, density, direction) on human navigation patterns, as well as perceptual factors like gesture recognition and proximity effects. Her studies often involve creating experimental frameworks to quantify behavioral responses under varying virtual conditions. No scientific awards or grants are explicitly listed in the provided materials. While no advising information is available, her publications suggest involvement in collaborative research teams focused on virtual reality applications. She contributes to Purdue's initiatives in computational behavioral studies and immersive technology development.
Howard C. Shane, PhD, CCC-SLP, is a Professor in the Department of Communication Sciences and Disorders at the MGH Institute of Health Professions since 1996. He concurrently serves as Director of the Center for Communication Enhancement (CCE) and Autism Language Program at Boston Children's Hospital, with an appointment in the Department of Otology and Otolaryngology at Harvard Medical School. His educational background includes: BA in Sociology, University of Massachusetts, Amherst MA in Speech Pathology/Audiology, University of Massachusetts, Amherst PhD in Speech Pathology, Syracuse University Dr. Shane's 30+ year career centers on augmentative and alternative communication (AAC) for complex communication disorders. His research emphasizes visual supports and technology-based interventions for autism spectrum disorder (ASD), motor speech disorders, and severe speech impairments. Key methodologies include graphic symbol systems, animation techniques, and mobile application development for communication enhancement. Analysis of his publications reveals a consistent focus on bridging clinical practice with technological innovation. His work examines symbol efficacy, visual language systems, and practical implementation challenges in AAC, with strong emphasis on real-world applicability for individuals with ASD and communication disabilities. Professional recognition includes: Honors of the Association from American Speech and Hearing Association Fellow of American Speech and Hearing Association Goldenson Award for Innovations in Technology (United Cerebral Palsy) As an educator, Dr. Shane teaches Autism, Motor Speech Disorders, and AAC courses in the Master of Science Speech-Language Pathology program. His dual clinical-academic role exemplifies the Institute's training philosophy. He has developed numerous computer innovations used globally by individuals with communication disorders and has lectured internationally on AAC applications. His laboratory leadership at the Center for Communication Enhancement focuses on developing evidence-based communication technologies and intervention strategies for children and adults with complex communication needs through interdisciplinary collaboration.
Feras Saad is an Assistant Professor in the Computer Science Department at Carnegie Mellon University, affiliated with the Principles of Programming and Artificial Intelligence groups. He received his Ph.D. in Computer Science from the Massachusetts Institute of Technology (MIT) in 2022, where his dissertations on probabilistic programming systems earned him the George M. Sprowls PhD Thesis Award and Charles & Jennifer Johnson MEng Thesis Award. His research focuses on developing scalable computing systems for probabilistic modeling and inference, integrating ideas from programming languages and probabilistic AI. Key research themes include probabilistic programming languages, automated probabilistic model discovery, statistical estimation and testing, random sampling algorithms, and applications in science and engineering. His lab explores new techniques to improve reasoning systems through automation, accuracy, and scale. Dr. Saad has published extensively in top venues including PLDI, POPL, ICML, and Nature Communications. His work spans foundational computational questions to practical software systems for probabilistic inference. Research trends show consistent focus on bridging theoretical computer science with practical applications in probabilistic modeling, with recent advances in random sampling algorithms and probabilistic programming systems. Awards and honors include: George M. Sprowls PhD Thesis Award in Artificial Intelligence and Decision Making (2023) Charles & Jennifer Johnson MEng Thesis Award in Computer Science (2017) Editor's Highlight for Nature Communications paper (2024) He currently advises graduate students Gaurav Arya and Thomas Draper in the Probabilistic Computing Systems Lab. His research is supported by software libraries including GenSQL, BayesNF, and SPPL that enable practical applications across scientific domains.
Dr. Yao Lu is an Assistant Professor in the Department of Architecture at Thomas Jefferson University's College of Architecture & the Built Environment. His academic background includes a PhD in Architecture from the University of Pennsylvania (2024), an MS in Matter Design Computation from Cornell University (2020), and both MArch and BEng degrees from Tongji University (2017, 2014). Dr. Lu's research integrates computational technologies with structural design to develop geometries optimizing performance, aesthetics, and constructability. Primary focus areas include: 3D graphics statics (3DGS) methodologies Generative design tools for architectural structures Reducing embodied carbon emissions in construction Material efficiency and fabrication cost reduction His work has received significant recognition including: Hangai Prize medal (IASS Symposium 2022) YoungCAADRIA Award (2020) R&D Award (2022) DigitalFUTURES Project Award (2022) Dr. Lu previously conducted doctoral research at the Polyhedral Structures Laboratory (University of Pennsylvania) and develops widely adopted computational tools with thousands of global downloads.
Dr. Damien Masson is an Assistant Professor in Human-Computer Interaction at the Université de Montréal, affiliated with Mila (Quebec AI Institute) and IVADO. He leads the Montréal HCI group and focuses on intelligent systems, document augmentation, and interactive visualization tools. His work bridges HCI, AI, and data science to improve how humans interact with complex information. Education: PhD in Computer Science (University of Waterloo, 2023), MSc from Université de Lille (2018). His research includes systems like Chameleon (interactive documents), ChartDetective (data extraction), and Textoshop (AI-based text editing). He has published at top venues like CHI and UIST, winning multiple awards including the 2023 Bill Buxton Dissertation Award. He actively mentors students across PhD/master's/undergraduate levels and develops open-source tools like Statslator.js and DirectGPT. His lab explores future directions in adaptive interfaces, multimodal interaction, and AI-driven document systems.
Sammie Katt serves as a Postdoctoral Researcher in the Department of Computer Science at Aalto University's School of Science, specializing in Bayesian Reinforcement Learning for robotics and decision-making under uncertainty. Their work addresses critical challenges in partially observable environments through algorithmic innovation and practical implementations. Dr. Katt's research centers on Bayesian approaches to reinforcement learning, with deep expertise in Partially Observable Markov Decision Processes (POMDPs). They develop scalable algorithms for uncertainty quantification, robot navigation, and real-time decision-making, bridging theoretical advances with robotic applications. Key contributions include BADDr for adaptive POMDP solutions and gym-gridverse for simulation benchmarking. Analysis of Katt's 14 publications (2012-2023) reveals three dominant trends: (1) Bayesian methods for efficient POMDP solving using Monte Carlo tree search and deep learning, (2) Robotics applications in motion prediction, target search, and scene reconstruction, and (3) Framework development for reproducible RL research. Their work consistently emphasizes computational efficiency and real-world applicability in uncertain environments.
Markus Enzweiler serves as Professor of Computer Science and Autonomous Systems at Esslingen University of Applied Sciences within the Department of Computer Science and Engineering. He concurrently holds the leadership position of Director at the Institute for Intelligent Systems, where he oversees research initiatives focused on intelligent systems development for real-world autonomous applications. His research program centers on computer vision for autonomous systems , with specialized expertise in visual-inertial SLAM, collective perception, and neural rendering techniques. Key investigation areas include environmental robustness across agricultural and urban settings, real-time processing constraints for embedded systems, sensor fusion methodologies (particularly camera-radar integration), and the application of generative models for perception enhancement. His work consistently addresses practical implementation challenges such as computational efficiency and sensor calibration in unstructured environments. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) Advancement of lightweight perception systems through stixel-based representations and neural rendering; (2) Development of infrastructure-supported collective perception frameworks with datasets like CoopScenes and OPNV; and (3) Rigorous benchmarking of SLAM components in domain-specific contexts including agricultural robotics and multi-season navigation. His recent systematic review on LLM-based vulnerability detection also demonstrates expanding interest in software security for autonomous systems. As Director of the Institute for Intelligent Systems, Prof. Enzweiler leads a research ecosystem focused on translating theoretical advances into practical autonomous vehicle technologies. His team develops specialized datasets (Rover, OPNV) and software stacks for smart city environments, emphasizing the integration of novel perception approaches with vehicle dynamics modeling and real-time operational constraints.
Prof. Dr. Katja Dörschner Boyaci is a Professor at Justus-Liebig-Universität Gießen , Faculty of Psychology and Sports Science, leading the Perception & Active Exploration Group . Her research focuses on understanding how the human brain constructs rich perceptual experiences from sensory input, particularly in the perception of material properties like softness, glossiness, and roughness. Research Interests: Computational and neural mechanisms of material perception Integration of visual and haptic information Expectation-driven modulation of perception Neuroimaging (fMRI, EEG) and psychophysical approaches Virtual reality and computational modeling Her work combines psychophysics , neuroimaging , and computational modeling to explore how humans judge material properties from static and dynamic images, and how prior experiences shape these perceptions. Scientific Contributions: Published extensively on material perception, with recent papers in Nature Human Behaviour , Journal of Neuroscience , and Vision Research . Leads the collaborative B8 project on integrating experience and sensory information in material perception. Collaborations & Funding: Co-leads the B8 project with Prof. Hüseyin Boyaci, funded to investigate neural mechanisms of expectation-based perception. Employs interdisciplinary methods including EEG, fMRI, VR, and behavioral experiments. Laboratory & Team: The Perception & Active Exploration Group at Giessen University studies how humans perceive intrinsic object qualities through active exploration and sensory integration, with implications for product design, computer graphics, and robotics.
