Marinko Sarunic is an Adjunct Professor at the School of Engineering Science , Simon Fraser University . He holds a PhD in Biomedical Engineering from Duke University and has been recognized as a Michael Smith Foundation for Health Research Scholar . His research focuses on biomedical imaging , particularly optical coherence tomography (OCT) , microscopy , and low-coherence interferometry , with applications in diabetic retinopathy , Alzheimer’s disease , and age-related macular degeneration . Dr. Sarunic's work spans adaptive optics , deep learning , and sensorless OCT systems , emphasizing clinical translation and open-source software development (e.g., OCTAVA ). His Google Scholar publications highlight multimodal imaging , vascular heterogeneity analysis , and AI-driven diagnostics for retinal diseases. His contributions include the Michael Smith Foundation for Health Research Scholar award. Though not currently teaching courses, his collaborations and leadership in retinal imaging and medical device innovation are pivotal for advancing non-invasive diagnostics in neurodegenerative and diabetic conditions .
Grant Van Horn is an Assistant Professor at the University of Massachusetts Amherst, affiliated with the College of Information and Computer Sciences. He specializes in computer vision and machine learning, focusing on applications in biodiversity and conservation. His work underpins popular tools like iNaturalist, Seek, and Merlin Bird ID. Prior to UMass, he held roles at AWS and the Cornell Lab of Ornithology. Education: PhD in Computer Science, California Institute of Technology (2019) MS in Computer Science, University of California San Diego (2014) BS in Computer Science, University of California San Diego (2012) Research Interests: Grant’s research bridges computer vision and machine learning to create systems that integrate human expertise and large datasets for environmental conservation. Key areas include wildlife species identification, acoustic monitoring, and ecological modeling. His work emphasizes leveraging technology for public engagement and scientific impact. Articles & Trends: Recent publications focus on audio geolocation, species range estimation, and satellite imagery analysis, reflecting his commitment to advancing tools for biodiversity conservation. His work often combines citizen science data with machine learning innovations. Awards: Computing Research Association Outstanding Undergraduate Researcher Honorable Mention (2012) Ben P.C. Chou Doctoral Prize (2019) Fast Company’s 2021 Recognition Advising & Labs: Grant advises students in computer science and conservation technology through the Computer Vision Research Laboratory. He has collaborated on projects like the iWildCam dataset and systems for salmonid counting in sonar data.
Krzysztof Czarnecki is a Professor at the University of Waterloo's Department of Electrical and Computer Engineering, with a cross-appointment to the School of Computer Science. He serves as leader of the Waterloo Intelligent Systems Engineering Lab and holds the title of University Research Chair. His research focuses on generative software development, model-driven engineering, and autonomous systems, particularly in automotive cybersecurity and perception safety. Education: Doctorate in Computer Science, Technical University of Ilmenau (1999) Master of Science in Computer Science, Technical University of Ilmenau (1995) Bachelor of Science in Computer Science, California State University (1994) Research Interests: Dr. Czarnecki's work spans generative programming, software product lines, and safety-critical AI for autonomous vehicles. Recent projects address robust perception systems, uncertainty quantification in neural networks, and strategic driving behavior modeling. He co-authored Generative Programming (Addison-Wesley, 2000), a foundational text in the field. Publications Trends: Recent work emphasizes multimodal AI integration (e.g., LEO-MINI), 3D object detection improvements (OV-SCAN), and safety assurance frameworks for autonomous systems. His research bridges theoretical software engineering with applied robotics challenges. Awards: Premier’s Research Excellence Award (2004) British Computing Society’s Upper Canada Award (2008) University Research Chair, University of Waterloo (2023) Teaching & Leadership: Teaches courses like ECE 495 (Autonomous Vehicles) and ECE 651 (Software Engineering Foundations). Oversees WatCAR initiatives and collaborates on industry projects through the NSERC Bank of Nova Scotia Industrial Research Chair (previous). Labs & Teams: Directs the Waterloo Intelligent Systems Engineering Lab, focusing on AI-driven solutions for autonomous systems and safety-critical software. Active in cross-disciplinary collaborations with automotive and robotics partners.
Martin Steinberger is an Associate Professor at the Institute of Control and Automation (IRT) at Graz University of Technology (TU Graz). His work focuses on advanced control systems, networked control, model predictive control (MPC), and automation in manufacturing and autonomous systems. He leads research into real-time optimization, fault diagnosis, and safety-critical applications in industries like pharmaceuticals and automotive. Research interests include: Networked Control Systems Model-Based Control Autonomous Vehicle Trajectory Planning Process Automation Robotics and Industrial Automation His work bridges theoretical control engineering with practical applications in manufacturing lines, chemical processes, and autonomous driving. Recent studies emphasize digital real-time release testing for pharmaceuticals, universal control concepts for manufacturing systems, and safety-aware trajectory optimization for automated vehicles. His publications frequently address challenges in time-varying delays, packet loss mitigation, and robust observer design for nonlinear systems. Steinberger collaborates on EU-funded projects and regularly contributes to conferences like the International Workshop on Variable Structure Systems. His research often involves experimental validation, as seen in work with compact pharmaceutical manufacturing setups and small-scale autonomous vehicle testing platforms.
Dr. Chunming Qiao is a SUNY Distinguished Professor and Chair of the Department of Computer Science and Engineering at the University at Buffalo (SUNY) , leading the Lab for Advanced Network Design, Evaluation and Research (LANDR) since 1993. His work spans cyber-physical systems , optical networks , and Internet of Things (IoT) , with a focus on safety, reliability, and protocol design. Education: PhD in Computer Science from the University of Pittsburgh (1993) BS in Computer Science and Engineering from the University of Science and Technology of China (1985) Dr. Qiao’s research interests combine theoretical and applied network design, including autonomous vehicles , quantum computing , and cloud services . He pioneered optical burst switching (OBS) and iCAR systems for wireless convergence, cited in BusinessWeek and Wireless Europe . His recent publications emphasize quantum networking , federated learning , and autonomous driving security , with projects on entanglement routing , edge inference optimization , and LiDAR adversarial attacks . Articles span IEEE and ACM venues , and include best paper awards . Scientific Awards: TC-CSR Distinguished Technical Achievement Award (2015) SUNY Chancellor's Award for Excellence (2013) IEEE Fellow (2009) UB Exceptional Scholar-Sustained Achievement Award (2005) Dr. Qiao has secured over two dozen NSF grants and collaborations with Google , Cisco , and NEC Labs . His 7 US patents and consulting experience highlight his industry impact, while his editorial roles and conference leadership underscore academic influence. He actively contributes to multi-disciplinary research through the New York State Center of Excellence in Bioinformatics and Life Sciences and CEDAR , advancing high-performance computing and document analysis .
Jakob Puchinger is a Professor in Supply Chain Management and Logistics at EM Normandie since 2022. He also serves as an affiliate professor at the Laboratoire Génie Industriel at CentraleSupélec, Université Paris-Saclay, and co-director of the Future Cities Lab with Centrale Pékin. He holds a PhD in Computer Science from TU Wien (2006), focusing on metaheuristics and integer programming for cutting and packing problems. His research spans logistics, urban mobility, disruptive technologies, and transport system optimization. Professional roles include Head of the Operations Management team at CentraleSupélec (2019–present), holder of the Anthropolis Chair at IRT SystemX (2015–2022), and scientist at the Austrian Institute of Technology (2008–2014). He has authored over 80 publications and supervised six theses, with five ongoing. Research interests emphasize sustainable urban logistics, last-mile delivery optimization, and shared mobility systems. Key contributions include studies on electric vehicles, autonomous systems, and policy frameworks for decarbonization. His work integrates optimization algorithms, agent-based modeling, and real-world case studies to address complex mobility challenges. Recent publications focus on route optimization for cold chain logistics, decarbonization policies, and collaborative truck-robot delivery systems. He actively contributes to conferences like Transportation Research Board and ROADEF, and co-authored books on urban mobility futures and robomobility revolution.
Kyle J. M. Bishop is Professor of Chemical Engineering at Columbia University's Fu Foundation School of Engineering and Applied Science (Columbia Engineering), where he leads research at the intersection of active matter, soft materials, and micro-robotics. Appointed in 2016 after serving as Assistant Professor at Penn State and postdoctoral fellow with George Whitesides at Harvard, his work focuses on non-equilibrium assembly of colloidal systems. Education: BS in Chemical Engineering (highest distinction), University of Virginia PhD, Northwestern University Professor Bishop's research pioneers strategies for directing colloidal assembly outside thermodynamic equilibrium, with emphases on magnetic micro-robot navigation, synchronization phenomena in active matter, and electrochemical control of soft materials. His lab develops fundamental principles for programming collective behavior in synthetic systems, bridging chemical engineering, physics, and robotics to create materials with lifelike functionalities. Recent work explores biomolecular condensates, field-driven transport, and non-equilibrium information processing. Analysis of his 2023-2025 publications reveals a cohesive trajectory toward autonomous control of active systems: magnetic micro-robots navigate complex landscapes through field programming, enzymatic coacervates implement biological feedback loops, and oscillator networks achieve emergent synchronization. These studies span soft matter physics, electrochemistry, and microfluidics, consistently targeting applications in programmable materials and environmental engineering while advancing non-equilibrium thermodynamics. Scientific Awards: 3M Non-tenured Faculty award NSF CAREER award for 'Contact Charge Electrophoresis for Mobile Microfluidics' Professor Bishop secures substantial research funding including his NSF CAREER grant developing contact charge electrophoresis for microfluidic applications. While current students aren't listed in source materials, his lab trains graduate researchers in experimental soft matter physics and micro-robotics. His group collaborates across disciplines to translate fundamental discoveries into technologies for targeted delivery and environmental remediation. The Bishop Lab at Columbia Engineering operates as an interdisciplinary hub where chemical engineers, physicists, and materials scientists develop experimental platforms for manipulating colloids at fluid interfaces, with recent work focusing on magneto-capillary dynamics and field-programmable micro-robot swarms.
Sheldon Andrews is an Associate Professor of Software Engineering and IT at École de technologie supérieure (ETS) in Montreal, Canada, with an adjunct appointment in Computer Science at McGill University. He is a member of the Multimedia Research Laboratory and has established himself as a leading researcher in physics-based computer animation and simulation. Andrews earned his Ph.D. in Computer Science from McGill University (2015), MASc in Electrical and Computer Engineering from the University of Ottawa (2007), and B.Eng. in Computer Engineering from Memorial University (2004). His academic journey reflects a strong foundation in both theoretical and applied aspects of computer engineering and graphics. His research focuses on real-time physics simulation, articulated mechanism simulation, 3D character animation, motion capture, computational contact mechanics, and virtual environment modeling. Andrews' work bridges the gap between theoretical physics and practical applications in computer graphics, with particular emphasis on creating physically plausible animations that can run in real-time. His research has significant implications for video games, virtual reality, and robotics applications. Analysis of his recent publications (2022-2025) reveals a strong trend toward increasingly sophisticated physics-based character animation techniques, with growing integration of machine learning approaches. His work spans multiple subfields including collision detection, deformable object simulation, vehicle physics, and reinforcement learning for character control, demonstrating both breadth and depth in his research program. VRIPHYS 2012 best paper award for 'Policies for goal directed multi-finger manipulation' Andrews has advised numerous graduate students through their PhD and Master's degrees, with many going on to positions at major companies like DNEG, CM Labs Simulations, and AMD. His professional service is extensive, having served as Program Chair for SCA 2025 and MIG 2024, Conference Chair for I3D 2019, and on program committees for major conferences including SIGGRAPH, SCA, and MIG for multiple years. He has also been active in the Montreal SIGGRAPH Chapter as Secretary from 2018-2021. As a core member of the Multimedia Research Laboratory, Andrews collaborates with researchers across multiple disciplines to advance the state of the art in physics-based simulation. His lab maintains strong industry connections, including a visiting researcher position at Roblox Research, ensuring that theoretical advances translate to practical applications in gaming and virtual environments.
Professor Bridgette Wessels holds the position of Professor of Social Inequalities at the University of Glasgow's School of Sociological & Cultural Studies within the College of Social Sciences. Her research focuses on social change in the digital age, particularly addressing inequalities, digital divides, and cultural participation. She has a PhD from the University of Sussex (2000), an MA from the University of York (1994), and a BA from the University of Durham. Affiliations: Glasgow Social and Digital Change Group, ESRC Productivity Institute Scottish Forum, Digital Technology and Social Change hub (CIVIS network) Roles: Editor of Participations: Journal of Audience and Reception Studies , Co-Lead of the ESRC Productivity Institute's Scottish Forum Her research interests include digital society dynamics, methodological innovation, and the societal impacts of technology. Recent projects explore inclusive productivity, AI ethics in smart homes, and telehealth equity. Key contributions include foundational work on digital divides, e-inclusion policies, and participatory design in health services. Her publications span film audience studies, smart city technologies, and digital sociology. She leads interdisciplinary teams on EU and UKRI-funded projects, emphasizing policy impact in areas like open data, health equity, and regional film culture. Grants and collaborations include funding from AHRC, ESRC, EU Horizon, and industry partners like ProQuest and Securekey. She advises on research strategies and has influenced UK and EU policies on digital inclusion and responsible innovation.
Dr. Paulo Santos is a Senior Lecturer at Flinders University's College of Science and Engineering, specializing in Artificial Intelligence with a focus on explainable AI systems. He holds a PhD from Imperial College London (2003) and has over 20 years of research experience in spatial reasoning, machine learning, and robotics. His work bridges knowledge representation with deep learning to enhance transparency in AI decision-making. Dr. Santos has led research groups in Brazil, collaborated internationally, and secured funding from organizations like the British Council and EU. His expertise spans robotics, computer vision, and cognitive science. Notable achievements include the British Computer Science Machine Intelligence Prize (2004) and the Santander Prize for Science and Innovation (2006). Research interests include reinforcement learning for autonomous underwater vehicles (AUVs), scene graph generation in computer vision, and spatial reasoning for multi-robot systems. Recent work emphasizes sim-to-real transfer learning and fault recovery in underwater robotics.
Pedro Nardelli is a Full Professor (tenured) of IoT in Energy Systems at the LUT School of Energy Systems, Lappeenranta University of Technology (Finland). He holds a double doctoral degree in electrical engineering from the University of Campinas (Brazil) and communications engineering from the University of Oulu (Finland). As a Docent in Information Processing and Communications Strategies for Energy Systems, he leads research in cyber-physical systems, smart grids, and 6G-enabled energy networks. Research Interests : His work focuses on integrating IoT, AI, and communication technologies into energy systems. Key areas include cyber-physical systems, UAV-enabled networks, sustainable energy management, and cybersecurity in critical infrastructure. He emphasizes interdisciplinary approaches to address challenges in the green-digital transition. Projects & Leadership : He is Principal Investigator for projects such as 'Energy-Conscious Operation: Network Efficiency for Wireless Sustainability' (2024–2026) and coordinates the Finnish-Brazilian AI and 5G training program. Past roles include leadership in the 'Hydrogen and Carbon Value Chains in Green Electrification' initiative (2021–2024). Publications : Recent work explores topics like hybrid optimal power flow models, UAV-IRS NOMA systems, and energy-centric analysis. His research bridges theoretical frameworks with practical applications, emphasizing sustainability and resilience in energy networks. Labs & Teams : Leads the IoT Solutions group within LUT's MORE SIM research platform, focusing on simulation-driven innovation for energy systems.
Ashish Gupta holds the Globe Life Professor title in the Department of Business Analytics & Information Systems at Auburn University and serves as an Adjunct Professor in the Department of Computer Science and Software Engineering. His research focuses on Deep Learning, Machine Learning, AI, Natural Language Processing, and Social Network Analytics. Education: Ph.D. in Management Science and Information Systems from Oklahoma State University. Research trends in his articles emphasize AI-driven solutions for misinformation detection, healthcare analytics, smart grids, and educational pedagogy. Notable themes include real-time fake news detection, pandemic impact studies, and predictive modeling in healthcare and agriculture. No scientific awards or grants are explicitly listed. He advises no formally listed students. His work integrates computational methods with societal challenges, particularly in healthcare, education, and agriculture. Collaborations span interdisciplinary domains, though specific lab affiliations are not mentioned.
J. Sean Humbert is a Professor at the University of Colorado Boulder, holding a courtesy appointment in the College of Engineering and Applied Science (AES). He serves as Director of the Robotics Program and Faculty Director for the Aerospace and Defense Western Colorado University Partnership Program. His research focuses on bio-inspired robotics, autonomous systems, and advanced control methodologies. Key research areas include flight dynamics, bio-inspired perception, micro-robotics, and soft robotics. He leads the Robotics and Systems Design group, affiliated with the Hypersonic Vehicles IRT. His work integrates bio-mimetic principles with engineering challenges, emphasizing robust control in unstructured environments. Recent publications span topics like soft robotic actuators, distributed sensing, and neural dynamics in robotics. His lab develops cutting-edge technologies for subterranean exploration, UAV navigation, and bio-inspired sensor systems. Collaborations include industry partnerships and interdisciplinary projects at the intersection of robotics, biology, and control theory. Awards and recognitions are not explicitly mentioned in the provided texts. Sean Humbert’s lab is located at ECES 1B14, with an office in ECES 146. His academic contributions bridge theory and application, addressing real-world challenges in autonomous systems and robotics innovation.
Vuk Gajić is an Assistant Professor at the Faculty of Applied Ecology, Singidunum University, where he has held academic roles since 2016. His career progression includes positions as a teaching associate (2016), assistant (2019), and current role (2023). He earned a Ph.D. in Environment and Sustainable Development from Singidunum University (2019–2022), following prior studies in environmental protection and risk management at the same institution. Research interests span environmental science, sustainable development, GIS applications, and radiation technology for waste and food treatment. He has contributed to interdisciplinary studies, including soil contamination analysis in Libya, microbial decontamination via ionizing radiation, and machine learning applications for software defect prediction and agricultural weed detection. His work bridges environmental engineering with technological innovation, emphasizing sustainability and ecological conservation. Publications reflect a focus on environmental monitoring, pollution assessment, and eco-technologies. Key themes include GIS-based environmental databases, forest fire prevention through sensor networks, and agricultural waste reuse. His research often integrates quantitative methods with geospatial tools, addressing both local and global environmental challenges. Teaching responsibilities include courses on geodiversity, sustainable development, and natural hazards. He actively participates in academic conferences, contributing to peer-reviewed journals and presenting at events like Sinteza and SETI. Current projects likely explore emerging technologies in environmental management and sustainable practices.
Dr. Martin Reisslein is a Professor in the School of Electrical, Computer, and Energy Engineering at Arizona State University (ASU), where he also serves as Program Chair of Computer Engineering. He earned his Ph.D. in Systems Engineering from the University of Pennsylvania (1998) and holds degrees from the University of Pennsylvania and Fachhochschule Dieburg, Germany. His research focuses on communication networks (e.g., 5G, optical networks, software-defined networking) and engineering education, with over 200 journal articles and 60 conference papers. He has led NSF-funded projects on network architecture optimization and K-12 engineering education. Education : Ph.D. (Systems Engineering, UPenn, 1998), M.S.E. (Electrical Engineering, UPenn, 1996), Dipl.-Ing. (FH) (Electrical Engineering, Fachhochschule Dieburg, 1994) Awards : NSF Career Award (2002), IEEE Fellow (2014), Bessel Research Award (2015), DRESDEN Fellowship (2016) Editorial Roles : Co-Editor-in-Chief of Optical Switching and Networking , Associate Editor for multiple IEEE journals His research spans communication networks (e.g., multimedia networking, optical systems) and engineering education (e.g., K-12 outreach, instructional design). Recent articles address cloud computing, 5G architectures, and cybersecurity in satellite systems. He teaches courses such as Communication Networks and oversees graduate research.
