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Edward AndòView profile

Researcher

• 3D Image Analysis
• Digital Volume Correlation
• X-ray Tomography
• +5 more

Edward Andò is a Principal Scientist and Lecturer at École Polytechnique Fédérale de Lausanne (EPFL) , with affiliations to the IMAGING group and the College of Engineering (ENAC) . His work bridges software development, experimental geomechanics, and educational initiatives in image analysis. Principal Scientist, IMAGING-GE (EPFL) Lecturer, Sciences et Génie Civil (SGC-ENS) Lecturer, Enseignement à la Défense (EDEE-ENS) Research Interests Andò specializes in 3D image analysis , with a focus on X-ray tomography , digital volume correlation (DVC) , and micromechanical modeling of granular materials. His work addresses geomechanical failure mechanisms, soil dynamics, and open-source software tools like SPAM for practical material analysis. Publication Trends His recent articles (2025–2023) emphasize X-ray tomography for studying granular deformation , rock failure , medical imaging , and soft particle compaction . Topics span geomechanics, computational modeling, and software development for experimental validation. Labs and Teams Andò contributes to the IMAGING group at EPFL, where he co-develops the SPAM (Software for Practical Analysis of Materials) . His teaching includes courses like Fundamentals of Image Analysis and Quantitative Imaging for Engineers , which integrate hands-on training with theoretical frameworks.

• Russian History
• Soviet History
• Cultural History
• +4 more

Denis Kozlov is an Associate Professor in the Department of History at Dalhousie University, specializing in modern Russian and Soviet history. His academic journey includes a BA from Herzen Russian State Pedagogical University, an MA from the University of Massachusetts Amherst, and a PhD from the University of Toronto. He holds appointments within Dalhousie's Faculty of Arts and Social Sciences and maintains an active research profile focused on cultural and intellectual transformations in the Soviet Union. His educational background reflects deep engagement with Russian studies: BA: Herzen Russian State Pedagogical University MA: University of Massachusetts Amherst PhD: University of Toronto Kozlov's research centers on Soviet cultural and intellectual history during the post-Stalin era (1953-1991), with particular emphasis on memory practices, reading audiences, and migration. His work examines how Soviet citizens processed historical trauma through literature and media, especially during the Thaw period, and explores transnational migrations from the USSR in the 1970s-1980s. He investigates intersections between literature, society, and historical consciousness, revealing how cultural production shaped Soviet identity and social change. Analysis of his 15 most recent publications shows consistent focus on Soviet cultural history, with dominant themes including reading practices during de-Stalinization, migration as political expression, and memory politics. His methodology combines archival research with cultural analysis, increasingly incorporating transnational perspectives in recent works on Soviet Jewish migration and Eastern European identity. His scholarly recognition includes significant awards: SSHRC Insight Grant (2019-2024) Andrew W. Mellon Fellowship at Institute for Advanced Study, Princeton (2010-2011) Harvard University Postdoctoral Fellowships (2008-09) Faculty of Arts and Social Sciences Teaching Award (2014-2015) Kozlov actively supervises graduate research in Soviet history while securing major grants including SSHRC and NEH funding. His teaching spans introductory surveys to advanced seminars on Soviet Russia and comparative cultural history, with recent courses including HIST 2021F (Soviet Russia) and HIST 3088F (History & Memory Russia and West) for 2024-2025. While no dedicated research labs are mentioned, his collaborative projects like the NEH-funded conference "The Thaw: Soviet Society and Culture during the 1950s and 1960s" demonstrate his role in building scholarly networks. Current work focuses on Soviet migration patterns and their ideological implications.

• Autonomous Driving
• Sensor Fusion
• Intelligent Transportation Systems
• +5 more

Prof. Dr.-Ing. Christoph Stiller is a full professor at the Karlsruher Institut für Technologie (KIT) and serves as the director of the Institute of Measurement and Control Technology (Institut für Mess- und Regelungstechnik, MRT). His work focuses on autonomous driving, sensor fusion, probabilistic estimation, HD mapping, motion planning, and intelligent transportation systems. Education: Details on his academic degrees are not provided in the text, but he holds the title of Dr.-Ing. indicating a doctoral degree in engineering. Research Interests: Prof. Stiller's research spans a wide array of topics critical to the development of autonomous vehicles. His work includes: Sensor Fusion: Integrating data from LiDAR, cameras, and radar to create robust perception systems. HD Mapping & Localization: Developing high-definition maps and precise localization techniques for urban and highway environments. Motion Planning & Decision Making: Creating algorithms for safe and efficient trajectory planning under uncertainty. Machine Learning & AI: Applying deep learning and reinforcement learning to perception, prediction, and control tasks. Publication Trends: His recent publications (2023–2025) emphasize robust traffic light detection, image stitching for panoramic views, motion prediction using redundancy reduction, and safety-enhanced model predictive control. The work increasingly integrates learning-based methods with classical control and estimation theory. Scientific Awards: No specific awards are listed in the provided text. Teaching & Supervision: Prof. Stiller teaches foundational and advanced courses in measurement and control systems, probabilistic estimation, and autonomous driving. He holds regular office hours during both summer and winter semesters and is actively involved in advising students and researchers. Labs & Teams: He leads the Institute of Measurement and Control Technology (MRT) at KIT, which is engaged in cutting-edge research in autonomous systems. The institute collaborates with industry and academia on large-scale projects such as UNICARagil and various European initiatives.

Lifeng ZhouView profile

Assistant Professor

• Robotics
• Algorithms
• Combinatorial Optimization
• +4 more

Lifeng Zhou is an Assistant Professor in the Department of Electrical and Computer Engineering at Drexel University, where he leads the Zhou Lab focused on advancing robustness and reliability in multi-robot systems through integration of foundation models. His research addresses real-world challenges in environmental monitoring, disaster response, and urban mobility. Education PhD, Electrical and Computer Engineering, Virginia Tech, 2020 MS, Control Science and Engineering, Shanghai Jiao Tong University, 2016 BS, Automation, Huazhong University of Science and Technology, 2013 Research Focus Dr. Zhou's work integrates robotics, algorithms, game theory and machine learning to develop secure and scalable autonomous systems. Primary research thrusts include: Resilient multi-robot coordination in adversarial environments Large language model integration for robotic decision-making Game-theoretic resource allocation strategies Risk-aware planning for autonomous vehicles Publication Trends Recent work (2024-2025) demonstrates strong focus on large language model applications in multi-robot systems, with 12/15 articles exploring LLM integration for flocking, scene segmentation, and decision-making. Additional emphasis includes adversarial robustness in target tracking (5 articles) and autonomous driving applications (4 articles). Awards and Recognition Best Paper Award, WACV 2025 LLVM-AD Workshop Professional Service Associate Editor, ICRA Conference Editorial Board Laboratory Focus The Zhou Lab develops foundational algorithms for secure and scalable multi-robot systems, with current projects spanning environmental monitoring drones, disaster response coordination, and autonomous vehicle perception systems.

• Big Data
• Business Analytics
• Healthcare Analytics
• +4 more

Haipeng Shen is a Professor of Innovation and Information Management at HKU Business School, The University of Hong Kong, serving as Associate Dean (EMBA and IMBA) and holding the Patrick S C Poon Professorship in Analytics and Innovation. He chairs the Business Analytics and Innovation program and joined HKU in 2015 after previously holding a professorship at the University of North Carolina at Chapel Hill. His academic credentials include: PhD in Statistics, The Wharton School of Business, University of Pennsylvania, 2003 MA in Statistics, The Wharton School of Business, University of Pennsylvania, 2000 BS in Mathematics, School of Mathematical Sciences, Peking University, 1998 Professor Shen's research focuses on data-driven decision making under uncertainty, with expertise spanning big data analytics, business analytics, healthcare analytics, and service engineering. He develops advanced statistical and machine learning methodologies to solve complex operational problems in call centers, optimize stroke care protocols, and enhance financial risk modeling, emphasizing real-time applications in high-stakes environments. Analysis of his recent publications reveals a consistent interdisciplinary approach bridging operations research, statistics, and domain-specific knowledge. His work demonstrates strong methodological innovation in time-series forecasting for service systems, risk assessment frameworks for medical complications, and covariance structure analysis for financial markets, with direct translational impact on business operations and clinical outcomes. His scientific contributions have been recognized with prestigious awards including: Most Influential Publication Award from China Stroke Association (2018) Fellow of the American Statistical Association (2015) Best Advisor of the Year Award from Academy of Asian Business (2018) Elected Member of International Statistical Institute (2015) Cluster Chair for Big Data Analytics at INFORMS International (2015) As an academic leader, Professor Shen has secured significant research funding from organizations including The Xerox Foundation and National Institute on Drug Abuse. He serves as Associate Editor for Management Science, Journal of the American Statistical Association, and Technometrics, while mentoring graduate students in statistical methodology and applied analytics. His current initiatives position HKU Business School at the forefront of healthcare innovation through big data analytics, driving collaborations with medical institutions to transform stroke care and hospital operations in Asia.

Siwei LyuView profile

Professor

• Digital Media Forensics
• Computer Vision
• Machine Learning
• +4 more

Dr. Siwei Lyu is a SUNY Distinguished Professor and SUNY Empire Innovation Professor in the Department of Computer Science and Engineering at the University at Buffalo. He serves as Co-Director of the Center for Information Integrity (CII) and Director of the UB Media Forensic Lab (UB MDFL). His research focuses on digital media forensics, computer vision, and machine learning, with significant contributions to counter-deepfake technologies. Education includes a PhD in Computer Science from Dartmouth College (2005), MS from Peking University (2000), and BS in Information Science from Peking University (1997). He has held academic positions at the University at Albany and New York University. His work spans media forensics, adversarial machine learning, and AI security. Notable achievements include developing the Celeb-DF dataset, leading NSF-funded projects, and testifying before U.S. and NYS legislative bodies on disinformation threats. Over $11.3M in grants have supported his research on AI-generated media detection, including a $5M NSF Convergence Accelerator grant. Key awards include IEEE and IAPR Fellowships, Google Faculty Award, and SUNY Chancellor's Research Award. He has authored 230+ papers, 4 patents, and serves on editorial boards of top journals and conferences (e.g., CVPR, ICCV).

Anna Marie MunsterView profile

Professor

• software studies
• technologies and embodiment
• multichannel and interactive installation work
• +19 more

Professor Anna Marie Munster is a distinguished academic and artist at UNSW Art and Design (College of Fine Arts), where she has held a full-time tenured position since 2001. Her work bridges theoretical scholarship with creative practice, establishing her as a leading figure in digital media art and critical theory. University: University of New South Wales School: College of Fine Arts (UNSW Art and Design) Position: Professor Qualifications: PhD from UNSW (2002), BA (Class 1 Hons with University Medal) from University of Sydney (1984) Professor Munster's research explores the intersections of art, technology, and philosophy, with particular focus on statistical visuality, radical empiricism, the politics and aesthetics of machine learning, and more-than-human perception. Her work integrates process philosophy with contemporary media practices, examining how time, movement, and sonicity shape our experience of digital environments. She approaches these topics through both theoretical scholarship and creative practice, often collaborating with artist Michele Barker on multi-channel audiovisual installations. Her publications reveal a consistent trajectory exploring the relationship between embodiment and digital media, with recent work focusing on AI and machine learning in cultural contexts. Munster's creative output demonstrates sophisticated integration of technical innovation with philosophical inquiry, particularly in how her installations challenge conventional perceptions of time and space. ARC, UNSW Student Council Award for Excellence in Postgraduate Supervision (2017) Dean's Award for Excellence in Postgraduate Supervision (2015) Highly commended for Materializing New Media at Prix Ars Electronica (2008) Winner of National Digital Art Awards 'The Harries' (2006) University Press of New England Publishing Award (2005) Professor Munster has completed over 20 PhD and Masters supervisions at UNSW and been involved in another 10 secondary supervisions. She currently supervises five PhD candidates working on diverse topics including coding materialities, critical bio-textiles, schizophrenia and XR technologies, sound and resonance, and affective drawing. Her ARC-funded research projects demonstrate sustained commitment to interdisciplinary work, particularly at the intersection of art, science, and technology. Her creative practice with Michele Barker has resulted in numerous commissioned installations exploring perception, embodiment, and the relationship between humans and technology.

Frank E. GarceaView profile

Academic

• Cognitive Neuroscience
• Neuroimaging
• Neurology
• +4 more

Frank E. Garcea, Ph.D., is a Research Assistant Professor in the Department of Neurosurgery and Neuroscience at the University of Rochester School of Medicine and Dentistry. His research focuses on the cognitive and neural mechanisms underlying tool use, apraxia, and stroke recovery. He employs neuropsychological testing, fMRI, and lesion-symptom mapping to study brain injury effects on functional connectivity and action knowledge. Education: Bachelor of Science in Psychology, St. John Fisher College (2006–2010) PhD in Brain and Cognitive Sciences, University of Rochester (2012–2017) Research Interests: Dr. Garcea investigates how brain regions like the parietal cortex and dorsal/ventral streams mediate object manipulation and tool use. His work explores stroke-related disconnection syndromes, motor speech coordination networks, and translational brain mapping to preserve neural function during surgery. He collaborates on projects involving epilepsy patients undergoing electrocorticography to study action-related neural pathways. Labs & Affiliations: Principal Investigator of the Garcea Lab at URMC, focusing on tool use deficits in brain tumor/stroke survivors. Affiliated with the Del Monte Institute for Neuroscience and the Neurobiology & Anatomy Program. His lab integrates neuroimaging, lesion analysis, and clinical care to advance personalized brain mapping strategies.

John DiffleyView profile

Professor

• DNA Replication
• Cell Cycle Control
• Chromosome Biology
• +5 more

John Diffley is a Principal Group Leader and Associate Research Director at The Francis Crick Institute in London, UK, where he leads research on DNA replication mechanisms. His work focuses on understanding how cells precisely duplicate their DNA during cell division and how errors in this process contribute to cancer development. Diffley obtained his PhD from New York University in 1985 and completed postdoctoral training with Bruce Stillman at Cold Spring Harbor Laboratory until 1990. He established his research group at the Clare Hall Laboratories (originally Imperial Cancer Research Fund, then Cancer Research UK) before moving to The Francis Crick Institute in 2015. His research spans DNA replication initiation, cell cycle control, replication fork checkpoints, and epigenetic inheritance. Diffley's lab has pioneered methods to reconstitute chromatin replication using purified proteins, providing unprecedented insights into chromosome biology. His team combines genetics, cell biology, and biochemistry to study the molecular 'machines' that copy DNA in yeast and human cells. Analysis of Diffley's recent publications reveals a strong focus on structural mechanisms of DNA replication, particularly using cryo-EM to visualize replication machinery. His work examines helicase loading and activation, replication fork stability under stress, and the connection between replication errors and cancer development. The research spans model organisms to human cells, with increasing emphasis on structural approaches in recent years. FRS (Fellow of the Royal Society) FMedSci (Fellow of the Academy of Medical Sciences) Diffley actively mentors a diverse team of postdoctoral researchers and PhD students, investigating various aspects of DNA replication. His lab has received substantial funding to support their work on replication mechanisms, with projects spanning basic biochemical reconstitution to studies of replication errors in cancer contexts. The lab maintains multiple technical platforms including structural biology, biochemistry, and cell biology approaches. His research group operates within The Francis Crick Institute's collaborative environment, utilizing shared facilities for structural biology, microscopy, and genomics to advance understanding of DNA replication mechanisms and their implications for genome stability and disease.

• European history
• Microhistory
• Italian history
• +3 more

Edward Muir is the Clarence L. Ver Steeg Professor in the Arts and Sciences and Charles Deering McCormick Professor of Teaching Excellence at Northwestern University, with joint appointments in the Department of History and Italian Studies at Weinberg College of Arts and Sciences. His academic journey includes a B.A. from the University of Utah (1969), an M.A. (1970), and Ph.D. (1975) in Modern European History from Rutgers University, including a Semester in Italy Program at Syracuse University (1967). Muir's research explores the intersection of ritual, violence, and power in Renaissance Europe, with emphases on Italian history, microhistory, and cultural anthropology. His work examines civic ceremonies, gender exclusion, and the sociopolitical underpinnings of early opera. Key themes include the anthropology of Venice, religious processions, and community formation in pre-modern societies. His scholarly publications reveal a consistent focus on Renaissance cultural practices, Venetian society, and methodological innovations in microhistory. Recent works analyze opera's emergence in 17th-century Venice, anti-war movements, and gendered public spaces, blending archival rigor with interdisciplinary theory. Awards and Honors: Herbert Baxter Adams Prize (1982) Two-time Howard R. Marraro Prize winner (1982, 1993) Andrew W. Mellon Foundation Distinguished Achievement Award (2010, $1.5 million) Fellow, American Academy of Arts and Sciences (2014) Charles Deering McCormick Professorship for Teaching Excellence (2006) Muir has held major administrative roles including Department Chair at Northwestern and LSU, co-directed the Graduate Program in Italian Studies, and served on editorial boards for journals like the American Historical Review . He mentors through graduate programs but no specific student advisees are listed.

• Computer Graphics
• Machine Learning
• Deep Learning
• +5 more

Dr. Frederick Li is an Associate Professor in the Department of Computer Science at Durham University, UK. He holds editorial roles as Associate Editor of Frontiers in Education (Digital Education) and Editorial Board Member of Virtual Reality & Intelligent Hardware. His research focuses on Computer Graphics, Machine Learning, Geometric Modelling, Collaborative Virtual Environments, Visual Aesthetics, and Educational Technologies. He earned his B.A. (Hons) and M.Phil. from The Hong Kong Polytechnic University and his Ph.D. in Computer Graphics from City University of Hong Kong. Prior roles include Assistant Professor at HK PolyU and project manager of a Hong Kong Government ITF-funded project. **Education**: B.A. (Computing Studies) and M.Phil. from HK PolyU; Ph.D. in Computer Graphics (CityU Hong Kong). **Research Interests**: His work spans mesh saliency detection, human-object interaction recognition, cloud modeling, face beautification, and educational technology. Recent achievements include awards for papers (e.g., Best Paper at ITiCSE 2014) and recognition such as EPSRC Peer Review College membership. He leads Durham's Undergraduate Board of Examiners and has been an external examiner at Northumbria University. **Awards**: Best Paper (ACM ITiCSE 2014), Outstanding Paper (ICALT 2013), EPSRC Peer Review College (2024), Outstanding BMVC 2024 Reviewer. **Grants & Labs**: His research is supported by grants from EPSRC and others. He collaborates with the Centre for Vision and Visual Cognition, VIViD, and AIHS group at Durham.

Niko TrojeView profile

Professor

• Vision Science
• Biological Motion Perception
• Cognitive Psychology
• +5 more

Niko Troje is a Professor at York University, affiliated with the Departments of Psychology, Biology, and Electrical Engineering & Computer Science. He holds cross-appointments and leadership roles, including Director of the BioMotion Lab. His research focuses on perceptual representations, biological motion, and vision science. Education: Ph.D. in Biology (1994) - Albert-Ludwigs Universität B.Sc. in Biology (1990), Physics & Mathematics (1987) - Albert-Ludwigs Universität Research Interests: Troje investigates how the brain processes biological motion, perception of human and animal movement, and applications in virtual reality. His work bridges neuroscience, psychology, and computer science. Key Contributions: Pioneered point-light displays for motion perception, explored gait analysis in mental health, and developed tools for motion capture and analysis (e.g., bmlTUX). Awards: Humboldt Research Prize (2014) NSERC Steacie Fellowship (2008-2009) Canada Research Chair (2003-2013) Grants & Labs: Led funded projects on movement perception, collaborated with institutions like the Max Planck Institute, and directs the BioMotion Lab at York University.

David WettergreenView profile

Research Professor

• Space Robotics
• Robotic Exploration
• Autonomous Navigation
• +7 more

David Wettergreen is a Research Professor at the Robotics Institute within Carnegie Mellon University's School of Computer Science , where he has been a faculty member since 2000. He directs the PhD Program in Robotics and holds a courtesy appointment in Mechanical Engineering. His research focuses on robotic exploration systems for extreme environments, spanning planetary surfaces, underwater caves, and terrestrial deserts. Key areas include autonomous navigation , science autonomy , multi-modal perception , and resource-cognizant planning . Field validation drives his work, with deployments in the Atacama Desert, Antarctic volcanoes, and lunar analog sites. Co-founder of Mesh Robotics LLC for off-road autonomy Former Research Fellow at Australian National University Former National Research Council Research Associate at NASA Ames Research Center His 15 most recent publications (2023-2025) demonstrate expertise in autonomous path planning , machine learning applications , terrain modeling , and science-driven exploration . Collaborations span planetary science, environmental monitoring, and space systems engineering. He has advised 17 PhD and 33 MS students , many of whom now work in space exploration or field robotics, and teaches courses in Robotics Systems Engineering . Current projects include the MoonRanger lunar micro-rover and technologies for autonomous resource mapping .

Mahmoud El-SakkaView profile

Associate Professor

• Image Compression
• Medical Imaging
• Image Segmentation
• +5 more

Mahmoud El-Sakka is an Associate Professor at the Department of Computer Science, University of Western Ontario since 1999. Previously, he was a faculty member at the University of Waterloo (1997–1999). He holds a B.Sc. and M.Sc. from Alexandria University (Egypt) and a Ph.D. in Systems Design Engineering from the University of Waterloo. His research focuses on medical imaging, image processing, and computer-aided diagnostics. He has served as Chair of the graduate program (2002–2007) and undergraduate program (2017–present) in Computer Science at Western Ontario. El-Sakka is a Senior Member of the IEEE and a licensed Professional Engineer in Ontario. His work spans grants from NSERC, internal university funding, and industry collaborations. Major research areas include image compression, segmentation, and medical applications like vascular analysis and echocardiography. He has led over 20 funded projects since 1999, emphasizing interdisciplinary approaches in healthcare technology. Academic contributions include advisory roles in summer programs, thesis evaluations, and conference participation. His service includes roles as Pro-Chancellor at convocations and involvement in equipment purchasing committees. Collaborations include consulting with NCR Canada and VRP Web Technology.

John NassourView profile

Researcher

• Computational Cognitive Systems
• Robotics
• Wearable Robotics
• +5 more

John Nassour is a Researcher at the Technical University of Munich's School of Computation, Information and Technology, affiliated with the Chair of Cognitive Systems. He holds engineering degrees from Tishreen University (electronics), a Master's in intelligent systems from University of Cergy-Pontoise/École Nationale Supérieure de l'Électronique, and a joint PhD from University of Versailles/TUM. His interdisciplinary research focuses on computational cognitive systems applied to robotics, including wearable devices, humanoid robots, soft robotics, and robot learning for locomotion/manipulation. Before joining TUM in 2020, he was a lecturer/researcher at Chemnitz University of Technology. He teaches courses in cognitive systems, neuro-inspired engineering, and soft robotics.