Xiaoming Liu is the Anil K. and Nandita Jain Endowed Professor of Engineering and MSU Foundation Professor in the Department of Computer Science and Engineering at Michigan State University . Holding a Ph.D. from Carnegie Mellon University (2004), he leads cutting-edge research in computer vision and machine learning. Research Interests : Computer Vision Pattern Recognition Image and Video Processing Machine Learning Medical Image Analysis Multimedia Retrieval Recent Research Trends : Focus on 3D object detection and depth estimation Development of robust biometric recognition systems Integration of radar-camera fusion for autonomous systems Advancements in self-supervised and multimodal learning Exploration of adversarial AI security Creation of interpretable forgery detection frameworks Teaching : Spring 2013: CSE891-006 Computer Vision Seminar Fall 2012-2015: CSE803 Computer Vision Spring 2014-2017: CSE 471 Media Processing and Multimedia Contact Information : Email: liuxm@cse.msu.edu Office: EB 3137, Michigan State University Phone: +1 (517) 355-2359
Thomas Hacker is a Professor in the Department of Computer and Information Technology at Purdue Polytechnic Institute, Purdue University. His research focuses on cloud computing, high-performance computing, operating systems, computer networking, and cyber infrastructure . He holds a Ph.D. and M.S. in Computer Science & Engineering from the University of Michigan, along with dual B.S. degrees in Computer Science and Physics from Oakland University. Education: PhD (Computer Science & Engineering), University of Michigan (2004) MS (Computer Science & Engineering), University of Michigan (1993) BS (Computer Science, Mathematics Minor), Oakland University (1989) BS (Physics), Oakland University (1989) Dr. Hacker's research spans cloud and grid computing, operating systems, and distributed systems , with applications in earthquake engineering data systems and AI-driven infrastructure analysis. His recent work explores extended layer 2 networking for bare-metal provisioning ( 2023 IEEE Cloud Summit ) and machine-supported bridge inspection using artificial intelligence ( Transportation Research Record, 2023 ). Notable scientific contributions include 15+ publications on topics like cyberinfrastructure for earthquake engineering, container-based virtualization, and data-intensive systems. His work has been recognized with awards such as the NSF CAREER Award (2010) and multiple Purdue Seed for Success Awards . Key Scientific Awards: NSF CAREER Award (2010) Purdue Seed for Success Awards (2008-2013) ASEE Information Systems Division Best Paper Award (2012) College of Technology Outstanding Faculty in Discovery Award (2010) He has held leadership roles at Purdue, including Department Head (2018-2021) and Interim Department Head (2011-2016) . His career spans academic positions at Indiana University, University of Michigan, and industry roles at Storage Technology Corporation.
Dr. Joey Paquet is a Tenured Associate Professor and Department Chair in the Department of Computer Science and Software Engineering at Concordia University in Montreal, Canada. He holds a PhD and specializes in research areas including Design and Implementation of Programming Languages, Context-Driven Computing, and Demand-Driven Computing. His work focuses on advancing programming paradigms and their applications in cybersecurity, distributed systems, and autonomic computing. Dr. Paquet is actively involved in thesis supervision across Computer Science and Software Engineering programs at both master's and doctoral levels. Research interests are centered around programming language design, particularly in demand-driven and context-aware systems. His contributions include frameworks like GIPSY and OpenISS, enabling scalable data processing and forensic computing. Recent work explores autonomic intent-driven networking, real-time gesture recognition, and IoT forensics. These efforts highlight his expertise in both theoretical constructs and practical implementations. His advising role supports students in MCompSc, MASc, and PhD programs. While specific grants are not detailed, his projects often involve interdisciplinary collaboration. Dr. Paquet is affiliated with platforms like LinkedIn and ResearchGate, reflecting an active academic presence. Key technical contributions include pioneering work on forensic computing backends, intent expression languages, and multimodal interaction systems. His research addresses challenges in cybersecurity, distributed systems, and service composition, with a focus on resilience and scalability.
Professor Hong Hao is a John Curtin Distinguished Professor at Curtin University, affiliated with the School of Civil and Mechanical Engineering and the Curtin Research Centre for Infrastructural Monitoring & Protection. His expertise spans Structural Dynamics, Earthquake Engineering, Blast and Impact Engineering, and Structural Health Monitoring. He holds prestigious roles like Fellow of ATSE, ISEAM, and ASCE, and has led organizations such as the International Association of Protective Structures and the Australian Earthquake Engineering Society. Education: BE (Tianjin University, 1982), MSc (UC Berkeley, 1985), PhD (UC Berkeley, 1989). Awards include the Tan Chin Tuan Fellowship and multiple Ko Medals. He has authored over 200 journal articles, with recent work focusing on blast-resistant materials, seismic fragility, and AI-driven structural health monitoring. His research emphasizes resilient infrastructure, including metaconcrete structures, corrosion-resistant materials, and sensor-based damage detection. Ongoing projects involve smart tunnel safety under BLEVE explosions and modular building systems.
Professor Eugene O'Brien serves as Professor of Civil Engineering within the School of Civil Engineering at University College Dublin's College of Engineering and Architecture. His research focuses on critical structural assessment methodologies for long-span bridges, with particular expertise in traffic load modeling and bridge safety evaluation. His research interests center on structural engineering challenges related to bridge infrastructure, specifically traffic load assessment for long-span bridges , structural health monitoring systems , and sustainable infrastructure management . Professor O'Brien pioneered camera-based monitoring techniques to overcome limitations of traditional Weigh-in-Motion sensors during congested traffic conditions, enabling more accurate safety assessments of aging bridge infrastructure. His work addresses the critical gap in quantifying traffic loading on bridges with spans up to 2 kilometers, where conventional methods fail during stop-and-go traffic scenarios. Analysis of his 15 most recent publications reveals a consistent research trajectory focused on probabilistic modeling of traffic loads, with increasing sophistication in handling extreme events and long-term infrastructure performance. His work spans fundamental statistical methods for load effect prediction, practical applications in real-world bridge assessments, and environmental considerations regarding infrastructure carbon footprints. The research demonstrates strong methodological evolution from basic traffic modeling to comprehensive lifetime assessment frameworks incorporating sustainability metrics. As co-founder and director of Roughan O'Donovan's subsidiary Innovative Solutions (ROD-IS), Professor O'Brien has translated research into practice through significant projects including the Malahide Railway Viaduct assessment (2009), EU-funded bridge lifespan simulation tools (2011), vibration reduction systems for bridge cables, and structural assessments for major international projects including the Ting Kau Bridge in Hong Kong, the Forth Road Bridge in Scotland, and the Chacao Channel Bridge in Chile. His consultancy work demonstrates direct application of academic research to critical infrastructure challenges worldwide. Professor O'Brien's research group operates at the intersection of structural engineering and sustainable infrastructure management, with particular emphasis on extending bridge service life through accurate safety assessment. Their work on the Chacao Channel Bridge demonstrates practical implementation of traffic monitoring systems using toll data to manage truck loads, while their environmental impact analysis shows how accurate safety assessments reduce unnecessary bridge replacements, thereby lowering the carbon footprint of transportation infrastructure through extended service life of carbon-intensive materials like concrete and steel.
Michael J. Black is a Professor and Honorarprofessor at the University of Tübingen's Faculty of Science, Department of Computer Science, and a founding Director of the Max Planck Institute for Intelligent Systems, leading the Perceiving Systems department. He holds a B.Sc. from the University of British Columbia (1985), M.S. from Stanford (1989), and Ph.D. in Computer Science from Yale (1992). His research focuses on computer vision, 3D human modeling, motion capture, and AI-driven digital humans. Key contributions include the SMPL body model, optical flow algorithms, and datasets like Middlebury Flow and Sintel. He has received major awards such as the PAMI Distinguished Researcher Award, multiple Koenderink and Longuet-Higgins Prizes, and is a member of the German National Academy of Sciences Leopoldina and Royal Swedish Academy of Sciences. His commercial ventures include co-founding Body Labs (acquired by Amazon) and Meshcapade, advancing 3D human generation and interaction technologies. Recent work includes markerless motion capture systems (e.g., MAMMA, PICO), 3D hair and garment synthesis, and AI tools like ChatHuman for 3D human interaction analysis. His research bridges vision, graphics, and robotics, with applications in animation, healthcare, and robotics.
Francesco Pilati is an Associate Professor at the Department of Industrial Engineering, University of Trento, where he serves as local coordinator for the scientific field ING-IND/17 (Industrial Plants and Logistic Systems). He chairs the research group on Industrial Plants, Production Systems, and Logistics, and teaches courses in Industrial Plants and Design of Digital Production and Assembly Systems. As coordinator of the Master's program in Management and Industrial Systems Engineering and University Coordinator for the EIT double degree in Zero-Defect Manufacture, Pilati bridges academic leadership with advanced manufacturing research. He has also served as Invited Lecturer at universities in Vienna and Göttingen. His research focuses on integrating environmental sustainability with technical-economic criteria through multi-objective optimization and impact assessment. Key areas include: Distribution networks and warehousing systems Manufacturing and assembly line design Hybrid energy production systems Digitization of manual production processes using depth cameras Recent publications highlight applications of Industry 4.0 technologies to pandemic safety, logistics optimization, and smart manufacturing. Pilati has received significant recognition including the Philip Morris Italia Empowering Research Award (2016) and Autostrade per l'Italia academic recognition. His editorial contributions include guest editing special issues on Digital Twins and Smart Factories in Q1 journals.
Dr A. I. Shihab is a Senior Lecturer at Kingston University's Faculty of Engineering, Computing and the Environment, Department of Networks and Digital Media. He teaches programming languages (C++/Java), data structures, web development, and AI/machine learning. His research focuses on affective computing and machine learning applications including: Acoustic event detection in sports environments Audio signal analysis for tennis match modeling Multi-camera visual surveillance systems Medical imaging analysis using fuzzy clustering techniques Publications demonstrate expertise in combining audio/video modalities for sports analytics (tennis rallies, court-shots) and developing Markov models for sound event sequence analysis. Contact: a.shihab@kingston.ac.uk
Dr. Foong Shaohui is an Associate Professor and Associate Head at the Engineering Product Development (EPD) pillar of the Singapore University of Technology and Design (SUTD), with prior experience as a Visiting Assistant Professor at MIT's Mechanical Engineering department (2011). He leads the Aerial Innovation Research (AIR) Laboratory @ SUTD and actively collaborates with Singapore's Ministry of Defence (MINDEF) and medical institutions like National University Hospital (NUH) and Changi General Hospital (CGH). PhD, MS, and BS in Mechanical Engineering from Georgia Institute of Technology (2005-2010) Research Interests span multiple domains: Robotics & UAVs : Nature-inspired aerial craft design (Project MONOCO), hybrid flight dynamics, and transformable rotorcraft Medical Device Innovation : Magnetic localization systems for nasogastric tubes and ventriculostomy procedures Engineering Education : Design-Centric pedagogy and pre-university Aerial Craft Workshops Autonomous Systems : Deep tunnel sewer inspection drones (NRF/PUB funded) and soft robotics Scientific Contributions include patented magnetic localization technologies (licensed to Medergo Pte. Ltd.), over 20 peer-reviewed publications, and 5 granted patents. His work bridges aerospace engineering with biomedical applications through innovative mechatronic solutions. Best Application Paper Award at SCIS & ISIS (2014) Research Grants include projects funded by Singapore's National Research Foundation (NRF), Public Utilities Board (PUB), and National University Hospital partnerships. He mentors PhD/Master's students through interdisciplinary research in aerial robotics and medical device development.
Mani Golparvar Fard is a Professor at the University of Illinois at Urbana-Champaign, holding joint appointments in the Siebel School of Computing and Data Science and the Department of Civil and Environmental Engineering. He also contributes to the Technology Entrepreneur Center. His research focuses on integrating artificial intelligence, computer vision, and data analytics to advance construction management, infrastructure monitoring, and automation. Key areas include BIM integration, reality capture systems, and deep learning-based progress tracking. His work emphasizes automated construction progress monitoring through semantic segmentation, vision-language models, and UAV-based data collection. He has pioneered methods like Scan2BIM-NET for converting point clouds into BIM models and developed frameworks for worker safety analysis using machine learning. Awards: Walter L. Huber Civil Engineering Research Prize (2018) Daniel W. Halpin Award for Scholarship (2016) Advising & Grants: While no specific grant details are provided, his research is supported by collaborations with industry and government initiatives, such as the Japanese national bridge inspection project. He advises a team focused on AI-driven construction solutions and maintains active partnerships with engineering firms. Labs & Teams: Leads research groups in vision-based construction analytics, automated scheduling systems, and BIM integration. His work is disseminated through platforms like the VisualSiteDiary system and the InstaDam open-source platform for structural damage analysis.
Prof. Christian Heipke is a distinguished academic serving as Dean of the Faculty of Civil Engineering and Geodetic Science at Leibniz University Hannover, Germany. He also holds the position of Executive Director at the Institute of Photogrammetry and GeoInformation (IPI), one of the leading research institutions in geospatial sciences within the faculty. His leadership extends across multiple committees including the Curriculum and Teaching Committee, Admissions and Examination Boards for Geodetic Science and Geoinformatics, and Navigation and Environmental Robotics. As a Professor at IPI, he maintains active research while overseeing significant academic and administrative responsibilities at the university. Professor Heipke's research spans multiple domains within geospatial sciences, with particular emphasis on: Advanced photogrammetric techniques and algorithms Remote sensing applications for environmental monitoring Computer vision approaches for geospatial data analysis Urban development monitoring using satellite imagery Machine learning applications in geoinformatics Disaster prediction and management systems His recent scholarly output reveals a strong focus on integrating cutting-edge computer vision and deep learning techniques with traditional photogrammetric methods. Analysis of his 15 most recent publications shows a clear trajectory toward more sophisticated AI-driven approaches for processing geospatial data, with particular attention to time-series analysis, uncertainty quantification, and multi-view systems. His work bridges theoretical advancements with practical applications in flood forecasting, deforestation monitoring, urban planning, and construction materials analysis. The geographic scope of his research has expanded significantly, with recent projects focusing on international case studies in the Philippines and tropical regions. Professor Heipke leads the Institute of Photogrammetry and GeoInformation, a major research hub that has celebrated 75 years of contributions to the field. His leadership extends to the Graduiertenkolleg 2159: "Integrity and Collaboration in Dynamic Sensor Networks," where he serves as a professor overseeing doctoral research. The institute maintains state-of-the-art facilities for processing satellite imagery, aerial photography, and developing novel algorithms for geospatial data analysis. Under his direction, the institute has strengthened its international collaborations and interdisciplinary research approaches, particularly in addressing Sustainable Development Goals through geospatial technologies.
Antonio González is a full Professor at the Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Architecture. He leads the Microarchitecture and Compilers (ARCO) research group, focusing on robust and energy-efficient computing systems, including general-purpose processors, GPUs, and cognitive computing architectures. His research spans computer architecture, microarchitecture, compilers, GPU design, and deep learning acceleration, with a strong emphasis on energy efficiency and memory optimization. His work integrates hardware and compiler techniques to enhance performance in modern computing systems. The recent publications highlight a strong trend in energy-efficient DNN acceleration, GPU microarchitecture, memory systems, and near-data processing. His team explores novel quantization methods, adaptive caching, and architectural extensions for vision and AI workloads, published in top-tier venues such as MICRO, ISCA, and IEEE/ACM journals. ACM Fellow (2020) ICREA Academia Award (2014, 2019, 2024) UPC Duran Farell Award (2008) HiPEAC 2024 Paper Award (twice) González has supervised several PhD students and leads competitive R&D+i projects, including those funded by ICREA and the European Research Council. His research group collaborates extensively within UPC and with international institutions. He is actively involved in advancing computer architecture through innovation in simulation, hardware design, and AI acceleration. He is a member of IEEE and ACM, and his work continues to influence both academic and industrial developments in high-performance and energy-efficient computing.
Matthew B. Blaschko is a Professor in the Department of Electrical Engineering at KU Leuven, Belgium. He serves as director of the KU Leuven ELLIS unit and is a fellow in the ELLIS Health program. He is a Core PI in the Flanders AI Research Program, working as a workpackage lead for Decision Support Systems and Medical Imaging. Blaschko is also a member of the KU Leuven Institute for Artificial Intelligence and one of the leaders of the working group on Machine Learning and Data Science. Professor Blaschko received his B.S. from Columbia University, M.S. from the University of Massachusetts Amherst, and Dr. rer. nat. from Technische Universität Berlin (awarded for work at Max Planck Institutes Tübingen). He was a Newton International Fellow at the University of Oxford and received his Habilitation (HDR) from École Normale Supérieure de Cachan. Prior to joining KU Leuven, he was a Permanent Research Scientist in the INRIA Saclay Research Center and a Faculty Member at Ecole Centrale Paris. His research focuses on machine learning techniques applied to visual data, with particular emphasis on calibration in deep learning, medical image analysis, and federated learning. Blaschko's work bridges theoretical foundations with practical applications, as evidenced by technology developed in his research being incorporated into MONA, software for ophthalmic image analysis. His research group has made significant contributions to the fields of model calibration, uncertainty estimation, and medical imaging analysis, with recent publications showing strong trends toward improving reliability of AI systems in medical contexts and advancing theoretical understanding of calibration metrics. Professor Blaschko has been recognized with several awards including the Université Paris-Saclay STIC Doctoral School Best Scientific Contribution Award, Best Paper Award at CVPR 2008, Main Award at DAGM 2008, and Best Student Paper Award at ECCV 2008. Professor Blaschko has supervised numerous PhD and Master's students, with current and former students including Deniz Soysal, Claire Marchal, Dongli Xu, Sebastian Gruber, Jiameng Li, Marco Mezzina, and many others working on diverse topics from Alzheimer's disease analysis to surgical phase recognition. His research has been supported by various funding sources including the Flanders AI Research Program. He has co-organized several influential workshops including the "Another Brick in the AI Wall: Building Practical Solutions from Theoretical Foundations" at CVPR 2025, Commands 4 Autonomous Vehicles workshop at ECCV 2020, and the Learning from Limited Labeled Data workshop series at NIPS 2017 and ICLR 2019. His laboratory focuses on machine learning for medical image analysis, with applications in ophthalmology, neurology, and surgical robotics. The group maintains active collaborations with medical institutions and participates in international challenges such as the KNee OsteoArthritis Prediction (KNOAP2020) challenge.
Dr. Xinwen Fu is a Professor in the Miner School of Computer & Information Sciences at the University of Massachusetts Lowell, where he also serves as Director of the iSAFER Center. He received his Ph.D. in Computer Engineering from Texas A&M University (2005), M.S. in Electrical Engineering from University of Science and Technology of China (1998), and B.S. in Electrical Engineering from Xi'an Jiaotong University (1995). Research Interests Dr. Fu specializes in Computer Security and Privacy , with particular focus on IoT Security , Mobile Security , Network Security , and Digital Forensics . His research has been published in all four top computer security conferences: IEEE Symposium on Security and Privacy (S&P/Oakland), ACM Conference on Computer and Communications Security (CCS), USENIX Security Symposium, and Network and Distributed System Security Symposium (NDSS), as well as prestigious journals like ACM/IEEE Transactions on Networking and IEEE Transactions on Dependable and Secure Computing. His work has gained significant media attention from CNN, Wired, Huffington Post, Forbes, Yahoo, MIT Technology Review, and PC Magazine, including multiple appearances on CNN Domestic and International. He has also served as TPC member for numerous prestigious conferences including ACM CCS, IEEE INFOCOM, and IEEE ICDCS. Scientific Awards Best paper award at IEEE International Conference on Industrial Internet (ICII) 2019 Best paper award, International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2017 Teaching Excellence Award of Department of Computer Science, UMass Lowell, 2016 Best paper award, International Performance Computing and Communications Conference (IPCCC) 2016 Award of Excellence, GeekPwn 2016 Ethic Smart Life Hack Competition Erich Spengler Student Cyber Paper Award with students, The Colloquium for Information Security Education (CISSE), 2016 Spotlight Paper of the IEEE Transactions on Mobile Computing (TMC), February 2014 Best paper award, International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2013 Best paper award, IEEE International Conference on Communications (ICC): Communications and Information Security Symposium, 2013 Teaching award, Department of Computer Science, University of Massachusetts Lowell, 2011
Dr. Auzeen Shariati is an Associate Professor and Director of Undergraduate Programs in the Department of Criminology, Law and Society at George Mason University. She holds a Ph.D. in Public Affairs and Criminal Justice from Florida International University (2017), an M.A. in Criminal Law and Criminology from Allameh Tabataba’I University (2010), and a B.A. in Judicial Law from the University of Tehran (2006). Prior to academia, she practiced as a defense attorney at the Iranian Bar Association. Her research focuses on environmental criminology, crime prevention, victimization, policing strategies, and comparative criminal justice systems. Key areas include pandemic impacts on domestic violence, school safety through Crime Prevention Through Environmental Design (CPTED), and policy evaluation in criminal justice. She has published extensively in journals like American Journal of Criminal Justice , Journal of Family Violence , and Security Journal . Recent work examines how the Covid-19 pandemic and social upheavals like the murder of George Floyd influenced domestic violence reporting and victim experiences. Her studies combine quantitative and qualitative methods, emphasizing real-world policy implications. Dr. Shariati teaches courses such as Introduction to Criminology , Law and Justice Around the World , and Evaluation of Crime and Justice Policies . She actively presents at conferences like the American Society of Criminology and has contributed to public discourse on campus safety and criminal justice reform through media engagements.
