David Whitney is a Professor of Psychology at the University of California, Berkeley , with affiliations in Cognitive Science and Neuroscience . His research focuses on visual perception, particularly how humans process information in cluttered environments through mechanisms like ensemble perception , serial dependence , and perceptual crowding . He employs techniques such as psychophysics, fMRI, and TMS to study these phenomena. Whitney's recent work examines serial dependence in schizophrenia, emotion perception in crowds , and medical image analysis for dermatology and radiology. His studies reveal how the brain uses dynamic predictive templates and motion cues to stabilize perception despite neural processing delays. Publications span Current Biology , Nature Reviews Psychology , and PLoS ONE , with a strong emphasis on interdisciplinary applications of perceptual science. Scientific contributions include foundational studies on visuomotor control , blind spot filling-in , and holistic face processing . His lab investigates perceptual stability across eye movements, spatial localization, and cross-modal interactions. Whitney has received grants such as NIH EY018216 to support his research on motion-dependent visual coding. Detailed information about his work is available on the Whitney Lab website .
Christine Clark, MD, MSc is an attending laryngologist at Weill Cornell Medicine’s Sean Parker Institute for the Voice and Assistant Professor in the Department of Otolaryngology-Head and Neck Surgery at Weill Cornell Medical College. She earned her B.A. from the University of Pittsburgh (2011) and her M.D. from Pennsylvania State University College of Medicine (2017), followed by residency at Georgetown University Medical Center and a fellowship in Laryngology at Weill Cornell, where she also obtained a master’s degree in Clinical and Translational Science. B.A. - University of Pittsburgh (2011) M.D. - Pennsylvania State University College of Medicine (2017) Residency - Georgetown University Medical Center Fellowship - Sean Parker Institute for the Voice (Laryngology) Master’s - Clinical and Translational Science at Weill Cornell Dr. Clark specializes in evaluating and treating swallowing, voice, and airway disorders. Her research focuses on chronic cough, laryngeal hypersensitivity, and benign phonotraumatic vocal fold lesions. She has developed clinical tools like the 3D-printed injection laryngoplasty simulator and quality improvement initiatives for surgical airway management. Her clinical work and research span topics such as vocal fold hemorrhage management, pharyngeal residue quantification in dysphagia, and granuloma as markers of malignancy. Recent publications emphasize global otolaryngology capacity building and performer-specific voice injury care. Scientific awards include: Teaching awards for excellence in medical student education during residency Dr. Clark is affiliated with the Sean Parker Institute for the Voice at Weill Cornell Medicine and serves as an Assistant Professor of Otolaryngology.
Peter Schroeder is the Shaler Arthur Hanisch Professor of Computer Science and Applied and Computational Mathematics at the California Institute of Technology (Caltech). He holds a B.S. from the Technical University of Berlin (1987), M.S. from MIT (1990), M.A. and Ph.D. from Princeton University (1992–1994). His academic roles at Caltech include Assistant Professor (1995–1998), Associate Professor (1998–2001), Professor (2001–2013), and Hanisch Professor since 2013. He served as Division Deputy Chair (2012–2015) and Acting Director of the Center for Advanced Computing Research (2013–2014). Schroeder’s research focuses on numerical algorithms for computer graphics, geometric modeling, and physical simulation. His work emphasizes Discrete Differential Geometry, rebuilding classical differential geometry for computational applications. Key areas include cloth deformation, fluid dynamics, and vortex simulations. Notable contributions include 'Schrödinger’s smoke' and fluid visualization techniques using Clebsch maps. His publications span ACM Transactions on Graphics and address topics like constrained Willmore surfaces, filament-based plasma models, and shape reconstruction from metrics. He has received the ACM Fellowship and Best Paper in Geometry Processing Award. His research often bridges computational mathematics with artistic and engineering challenges, such as simulating ink chandeliers and solar flares. Schroeder’s academic leadership includes co-founding the ACM SIGGRAPH Academy and mentoring students like James R. McLaughlin and Yanke Song, both recipients of the Henry Ford II Scholar Award.
Dr. Cristina Rosell is a Professor and Head of the Department of Food and Human Nutritional Sciences at the Faculty of Agricultural and Food Sciences, University of Manitoba. Her research focuses on grain-based food innovation, starch properties, and sustainable bakery processes. Education: PhD and BSc in Pharmacy from Universidad Complutense de Madrid, Spain Dr. Rosell specializes in cereal science, enzymatic food modification, and gluten-free product development. Her current projects include optimizing bakery processes with computational tools, tracing rice supply chains via blockchain, and integrating bioactives into gluten-free foods. Her work bridges food chemistry, nutritional science, and industrial bakery technology. Her recent research trends emphasize gluten-free bread using legume and root starches, starch-plant compound interactions , and sustainable food processing via microwave-assisted extraction, high-pressure treatments, and fermentation. Key subfields include dough rheology, polyphenol bioactivity, and techno-functional ingredient development. Dr. Rosell’s teaching includes graduate seminars in food science (HNSC 7130). She supervises graduate students in breadmaking, starch hydrolysis, and functional food design. Her lab explores grain quality, enzymatic treatments, and bakery product optimization through interdisciplinary approaches combining chemistry, nutrition, and process engineering.
Kostas Daniilidis is the Ruth Yalom Stone Professor at the University of Pennsylvania in the School of Engineering and Applied Science , specifically the Department of Computer and Information Science . He is also affiliated with the GRASP Laboratory and Archimedes, Athena Research Center, Greece . Education : PhD in Computer Science (1992) from the University of Karlsruhe with Hans-Hellmut Nagel Diploma in Electrical Engineering (1986) from the National Technical University of Athens Research Interests : Kostas Daniilidis is a leading researcher in Computer Vision and Robotics , with significant contributions to event-based vision , equivariant learning , 3D human pose estimation , and hand-eye calibration . His work spans neural rendering , dynamic scene modeling , and low-latency sensing systems . Article Trends : Daniilidis’s recent publications focus on event cameras for low-light and high-speed applications, Gaussian splatting for real-time 3D reconstruction, and equivariant neural architectures for robust motion estimation. His work bridges deep learning with geometric vision , emphasizing human mesh recovery and multi-agent coordination . Scientific Awards : Best Conference Paper Award at ICRA 2017 IEEE Fellow (2012) Teaching : He has taught courses such as CIS580: Machine Perception and CIS121: Data Structures , alongside advanced topics in robotics and computer vision. Lab & Collaborations : As director of the GRASP Laboratory (2008–2013), he fostered interdisciplinary research in robotics, and currently collaborates with institutions like the Athena Research Center in Greece.
Zhao Guoying is an Academy Professor at the Academy of Finland and holds a tenured Full Professorship at the University of Oulu, Finland. His research focuses on human behavior understanding, emotion AI, and computer vision. He has held visiting positions at institutions including Stanford University and Aalto University. He earned his PhD (2005) in Computer Science from the Chinese Academy of Sciences. His work has led to pioneering contributions in facial expression analysis, micro-expression recognition, and remote physiological signal measurement. Zhao has secured over €19.8 million in research grants as PI, including the prestigious Academy Professor Grant (2021-2026) and Profi-7 Hybrid Intelligence funding. He has supervised 22+ PhD students and 16+ postdocs, many of whom hold academic and industry leadership roles. His awards include IEEE Fellow (2022), IAPR Fellow (2020), and Finland’s Most Publishing AI Researcher (2017). His research interests span machine learning, affective computing, and feature representation. Notable contributions include the first systems for spontaneous micro-expression analysis, novel methods for face anti-spoofing, and remote health monitoring via video. He actively organizes conferences (e.g., Arctic AI Days) and chairs committees such as the Finnish AI Society board.
Fernando De la Torre is a Courtesy Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, with an affiliation to the Robotics Institute where he has been a research faculty member since 2005. He holds a Ph.D. in Electronic Engineering from Ramon Llull University (2002). His research focuses on machine learning and computer vision, with applications in human health, augmented/virtual reality, generative models, and data-centric methodologies. He directs the Human Sensing Laboratory, which explores technologies for human behavior analysis and health monitoring. Notable contributions include founding FacioMetrics LLC (acquired by Meta), advancing facial recognition and 3D human digitization, and developing frameworks for robust visual models. His work bridges theory and practice, with over 225 peer-reviewed publications and editorial roles, including Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence. Recent research trends emphasize generative AI applications in satellite imagery analysis, VR/AR rendering optimizations (e.g., Gaussian splatting), and clinical motion recognition for healthcare. His projects often intersect with industry, addressing challenges in wearable health monitoring and immersive technologies. His lab collaborations span academia and industry, focusing on scalable solutions for 3D human modeling, adversarial robustness, and multimodal data fusion. Key achievements include pioneering work on 3D face animation from speech and garment reconstruction from single images.
Dr. He Wang is an Associate Professor in the Department of Computer Science at University College London (UCL), affiliated with the Virtual Environment and Computer Graphics (VECG) group and the UCL Centre for Artificial Intelligence. He holds a Visiting Professorship at the University of Leeds and previously served as an Associate Professor and Lecturer there, as well as a Senior Research Associate at Disney Research Los Angeles. His research focuses on computer graphics, vision, and machine learning, with notable contributions to crowd simulation, generative models, and physics-informed neural networks. Dr. Wang earned his BEng from Zhejiang University and his PhD from the University of Edinburgh, followed by postdoctoral work at the University of Edinburgh's School of Informatics. He has been recognized as a Turing Fellow and serves as an Academic Advisor to the Commonwealth Scholarship Council and an Associate Editor of Computer Graphics Forum . His research spans cutting-edge topics including 3D reconstruction, adversarial attacks on motion recognition, and AI-driven groundwater modeling. He has supervised six PhD students to completion and actively engages in collaborative projects, consultancy, and grant evaluations. His lab welcomes students through dedicated recruitment channels.
Buyung Kosasih is a Professor in the School of Mechanical, Materials, Mechatronic and Biomedical Engineering at the University of Wollongong. He has held this position since 2000 and focuses on teaching and research in mechanical engineering, including Machine Dynamics, Finite Element Methods, and Renewable Energy Technology. His research spans fluid dynamics in industrial processes, renewable energy systems, and aqueous lubrication. Key projects include 3D-printed surfboard fin optimization and steel coating dynamics. Research interests emphasize experimental and computational fluid dynamics, particularly in renewable energy turbines and tribological systems. Notable awards include the 2013 Outstanding Contribution to Teaching and Learning Award. He has supervised numerous students and led over 20 funded projects, including ARC grants for steel innovation and renewable energy. Collaborative work includes the Steel Research Hub and HVAC/cool roof efficiency studies.
Karen Panetta is a Professor at Tufts University School of Engineering with appointments in Electrical and Computer Engineering, Computer Science, Mechanical Engineering, and Academic Services. She currently serves as Dean of Graduate Education for the School of Engineering and holds the title of Distinguished Professor. Ph.D. in Electrical Engineering, Northeastern University M.S. in Electrical Engineering, Northeastern University B.S. in Computer Engineering, Boston University Dr. Panetta's research focuses on developing efficient algorithms for simulation, modeling, and signal and image processing for security and biomedical applications. Her work brings together artificial intelligence, machine learning, and visual sensing systems to create solutions for robot vision and biomedical imaging. She develops algorithms inspired by the human visual system to enable machines to 'see' like humans, with applications in homeland security, biomedicine, facial recognition, and search and rescue operations. Her research has significant humanitarian applications, addressing global challenges facing women and children. Dr. Panetta has received numerous prestigious awards including induction into the National Academy of Engineering (2023), the Presidential Award for Science and Engineering Education and Mentoring (2011), and the IEEE Award for Distinguished Ethical Practices (2013). She is a fellow of multiple prestigious academies including the National Academy of Inventors, European Academy of Sciences and the Arts, and IEEE. Member, National Academy of Engineering (2023) Presidential Award for Science and Engineering Education and Mentoring (2011) IEEE Award for Distinguished Ethical Practices (2013) Fellow, National Academy of Inventors Fellow, European Academy of Sciences and the Arts Fellow, Asia-Pacific Artificial Intelligence Association As an educator and mentor, Dr. Panetta founded the nationally acclaimed Nerd Girls program to promote engineering to young students, particularly women. She previously served as worldwide director for IEEE Women in Engineering and editor-in-chief of the IEEE Women in Engineering magazine. Her approach to graduate education emphasizes the importance of building strong collaborative relationships between faculty and students, with a focus on proactive communication and documentation of research progress. Dr. Panetta's humanitarian research applies engineering solutions to global challenges, including developing technology to help doctors find cancerous tumors, security screeners find concealed weapons, and law enforcement agencies find criminals and missing children. Her work demonstrates a commitment to 'Doing The Right Thing' by addressing issues affecting populations with limited resources or 'voice' in society.
Adriana I. Kovashka is an Associate Professor in the Department of Computer Science at the University of Pittsburgh's School of Computing and Information. She serves as Chair of the Department of Computer Science. Her research focuses on computer vision, machine learning, and their intersections with human-machine communication and visual rhetoric analysis. Kovashka earned her BA in Computer Science and Media Studies from Pomona College (2008) and her PhD in Computer Science from the University of Texas at Austin (2014). She joined Pitt in 2015. Her work emphasizes improving image retrieval systems through semantic attributes, human-in-the-loop feedback, and crowd-sourced data. Notable projects include analyzing advertisements' persuasive strategies, developing object detection models resilient to domain shifts, and exploring multimodal learning with linguistic and visual inputs. She has secured significant grants, including NSF awards for geographic diversity in object detection (2023), CAREER funding for weak supervision methods (2021), and multiple Google Faculty Research Awards. Kovashka advises PhD students on topics ranging from multimodal intent modeling to domain generalization. She has organized workshops on advertising understanding and subjective attributes in vision conferences. Her lab's datasets, such as the 64,832-image ad repository and video ad collections, are widely used in vision research. Recent efforts include quantifying perceptual diversity in multilingual systems and mitigating bias in CNNs through shape regularization. Awards and recognitions include the NSF CAREER Award, Pitt's CRDF grants, and leadership roles in CVPR and WACV conferences. Her research bridges technical innovation with societal impact, addressing challenges in visual communication, ethical AI, and educational robotics.
Syed S.H. Rizvi is a Professor of Food Process Engineering at Cornell University's Department of Food Science, affiliated with the College of Agriculture and Life Sciences. He holds the title of International Professor and advises over 65 graduate and 70 undergraduate students. His expertise spans food engineering, processing, and international development. Education: Ph.D., The Ohio State University (1976) MEng, Chemical Engineering, University of Toronto (1988) B.Tech., Panjab University (1968) Research Focus: Physical, chemical, and engineering aspects of food and biomaterials Supercritical fluid technology, liposome synthesis, and sustainable processing International value-chain developments and food security Articles Trends: Recent works emphasize supercritical fluid extrusion, liposome encapsulation, and novel food processing innovations. Key themes include material characterization, functional food development, and sustainable technologies. Awards: Distinguished Professor (2017), Chinese Academy of Agricultural Science Excellence in Teaching Award (2014) Stanley Watson Award (2012) Advising & Grants: Mentor to numerous students globally. Collaborates internationally under sponsorships like FAO, UNIDO, and World Bank. Teaches courses on food engineering, international agriculture, and bioprocessing systems. Labs/Teams: Leads the Rizvi Lab, focusing on novel food processes and engineering. Active in developing sustainable technologies for bioactive delivery and food security.
Associate Professor Mohammad Saadatfar is affiliated with the School of Civil Engineering at The University of Sydney. His research focuses on meso-scale materials, combining experiments with simulations to address challenges in environmental science, biomedical engineering, and advanced materials design. Key areas include the study of cellular solids, granular materials, and meta-materials. His work integrates physics, engineering, and biology, with applications to CO₂ geo-sequestration, bone implants, and mechanical meta-materials. He uses X-ray tomography, FE simulations, and topological analysis to explore material behavior. Recent publications span topics like additive manufactured foams, CO₂ flow dynamics in sandstone, and biomimetic wood structures. His contributions highlight interdisciplinary approaches to material science and engineering challenges. No scientific awards or student advisement details are explicitly mentioned in the provided text.
Jun-Yan Zhu is an Assistant Professor at Carnegie Mellon University's School of Computer Science, affiliated with the Robotics Institute and Computer Science Department. His research focuses on generative models, computer vision, and graphics. He holds a B.E. from Tsinghua University and a Ph.D. from UC Berkeley, with postdoctoral work at MIT CSAIL. Zhu leads the Generative Intelligence Lab, exploring human-creator collaboration with generative models. Affiliations: Robotics Institute, CMU Graphics Lab, CMU Computer Vision Group Education: B.E. (Tsinghua), Ph.D. (UC Berkeley) Research Interests: Generative AI, image/video synthesis, neural rendering, tactile sensing integration Notable contributions include CycleGAN, pix2pix, and GAN compression techniques. His work has been commercialized in Adobe's Firefly and NVIDIA's Canvas tools. Awards: ACM SIGGRAPH Dissertation Award, David J. Sakrison Prize, CVPR Best Paper Finalist Lab Members: 10+ PhD students and researchers Current projects include LEGO design synthesis, tactile-driven 3D generation, and generative model personalization.
Dr. Joseph Dumpler is a Lecturer at the Department of Health Sciences and Technology at ETH Zürich, specializing in Sustainable Food Processing. He holds a PhD in Dairy Science and Technology from the Technical University of Munich, Weihenstephan, with a focus on UHT treatment of concentrated milk. His work emphasizes advancing food processing technologies, particularly in protein refinement, non-thermal methods, and membrane filtration. Educations: PhD in Dairy Science and Technology, Technical University of Munich, Weihenstephan (2017) MSc Food Engineering, Technical University of Munich, Weihenstephan His research interests include Natural Deep Eutectic Solvents (NADES) for plant protein extraction, microwave vacuum drying of dairy products, and membrane filtration optimization for microalgae and dairy systems. He has pioneered methods to refine rapeseed and pea proteins while minimizing antinutrients, and his work on microfiltration of milk products addresses emerging microbial risks. Key contributions span kinetic modeling of heat-induced protein aggregation, sustainable food processing , and non-thermal concentration techniques . His articles reflect a focus on bridging lab-scale innovations with industrial applications. Awards: J.T.M. Wouters Young Scientist Award Julius Maggi Research Award (2018) Best PhD Thesis Award from the Association of Dairy, Food and Biotechnologists (Weihenstephan) Dr. Dumpler collaborates with industry partners to translate research into scalable processes, such as NADES-based protein extraction and microwave drying systems. His current role at ETH Zürich’s Sustainable Food Processing Lab (Prof. Mathys) focuses on plant-based meat analogs and novel protein refining concepts .
