Ankita Raturi is an Assistant Professor in the Department of Agricultural & Biological Engineering at Purdue University, leading the Agricultural Informatics Lab. Her work focuses on human-centered design, information modeling, and software engineering to enhance resilience in food systems. She develops decision support tools for cover cropping, agronomic data services, and soil health technologies. Her research integrates digital agriculture applications across field crops, livestock, and food systems, emphasizing open-source solutions. Key projects include modular decision tools for diversified farming systems and information management frameworks for community food resilience. Publications highlight her expertise in sustainable tech adoption, precision agriculture, and ecosystem impact design. She actively bridges engineering and agriculture through interdisciplinary collaborations. Dr. Raturi's lab explores digital tools for smallholder farmers, pandemic response systems, and ecological wealth restoration through technology. She emphasizes trust-building in tech-mediated research and advocates for nonhuman-centric design in agroecosystems.
Dengfeng Sun is a Professor and Associate Head of the Gambaro Graduate Program in the School of Aeronautics and Astronautics at Purdue University. His research focuses on distributed control systems, autonomy, resilient networks, and air traffic management. Sun holds a B.Eng. from Tsinghua University, an M.S. from The Ohio State University, and a Ph.D. from UC Berkeley. His work spans advanced air mobility, UAV trajectory planning, and stochastic optimization for large-scale systems. Key contributions include resilient UAV traffic control, distributed state estimation algorithms, and fault detection methods for navigation systems. Sun's research has been published in top journals like IEEE Transactions on Intelligent Transportation Systems and Transportation Research Part E. Education: B.Eng., Tsinghua University (2000) M.S., Ohio State University (2002) Ph.D., UC Berkeley (2008) He advises on cutting-edge projects integrating robotics, autonomous systems, and cloud-based traffic modeling. His lab develops solutions for urban air mobility, emergency medical UAV networks, and next-generation air traffic control systems. Notable collaborations include work with NASA and industry partners on continuous descent approach procedures and metroplex routing paradigms. Sun's work bridges theoretical control systems with practical applications in aviation and infrastructure optimization.
Sonia A. Fahmy is a Professor of Computer Science and Associate Department Head at Purdue University's Department of Computer Science (College of Science). She holds a PhD from The Ohio State University (1999). Her research focuses on network architectures, protocols, and security, with over 100 refereed publications. Key areas include virtual reality networking, cellular network optimization, and network experimentation tools like NFV-VITAL and ENVI. Her work is supported by NSF, DHS, industry partners, and she leads Purdue's CERIAS cybersecurity initiatives. Education: PhD in Computer and Information Science from The Ohio State University (1999). Research Interests: Network security, distributed systems, wireless sensor networks, and network function virtualization. Notable contributions include the HEED clustering algorithm and Contain-ed latency management system. Awards: NSF CAREER Award (2003), IEEE Fellow. Grants: NSF, DHS, AT&T, Cisco, Juniper, and Meta-funded projects. Professional service includes leadership roles in IEEE ICNP, INFOCOM, and editorial roles in top journals. Advising: Mentored over 20 PhD students and postdocs. Current advisees include Umakant Kulkarni and Yufeng Chen. Research teams collaborate with industry partners like Hewlett-Packard and Sandia National Labs. Labs/Teams: Active in Purdue's CERIAS, leading projects on secure network protocols and experimentation frameworks. Tools developed include EMIST, Testbed Mapping, and iHEED for sensor networks.
Junhong Chen is the Crown Family Professor of Molecular Engineering at the University of Chicago's Pritzker School of Molecular Engineering and Lead Water Strategist at Argonne National Laboratory. His research focuses on hybrid nanomaterials, 2D materials, sensors for chemical/biological molecules, and energy devices. He has pioneered innovations in real-time water sensing and energy storage, with applications in environmental sustainability and healthcare. Chen holds a PhD from the University of Minnesota (2002) and a postdoc from Caltech (2003). He previously directed the NSF Industry-University Cooperative Research Center on Water Equipment & Policy and served as a NSF program director. Education: PhD in Mechanical Engineering (2002, University of Minnesota), Postdoc in Chemical Engineering (2002–2003, Caltech) Research Interests: Nanomaterials, Sensors, Energy Storage, Water Pollution Control Awards: Fellow of National Academy of Inventors, ASME, IAAM Medal, Wisconsin Innovation Award (2016) Chen's lab group develops nanosensors and energy devices using molecular engineering, with a focus on scalable manufacturing and AI integration. Recent work includes graphene-based sensors for real-time water monitoring and novel battery technologies. His research also addresses global challenges like PFAS contamination and sustainable manufacturing.
Assoc. Prof. Nhien An Le Khac is an Associate Professor at the School of Computer Science, University College Dublin. He serves as Programme Director for the MSc in Forensic Computing & Cybercrime Investigation, which has trained over 1,500 law enforcement officers globally. His research focuses on cybersecurity, digital forensics, AI security, and secure healthcare IT systems. He holds a PhD from Institut National Polytechnique de Grenoble (France) and has supervised 9 PhD students. His work includes pioneering contributions to electromagnetic side-channel analysis (EM-SCA) for IoT forensics, blockchain forensics, and AI-based fraud detection. Education: BSc/MSc: Vietnam National University, Ho Chi Minh City PhD: Institut National Polytechnique de Grenoble, France Professional Certificate in University Teaching & Learning: UCD Research Interests: Cybersecurity, Digital Forensics, AI Security, Machine Learning, Cloud Computing, Big Data Analytics, Healthcare IT Security. Recent Article Trends: Focus on EM-SCA for IoT device forensics, illicit Bitcoin transaction tracking, and cross-device ML portability. His work bridges theoretical AI advancements with practical forensic applications, emphasizing privacy preservation and explainable AI. Awards & Recognition: World’s Top 2% Scientists (2024) UCD Teaching Excellence Awards (2022, 2018) Best Paper Awards at Elsevier, AI-2022, and DFRWS conferences Grants & Advising: Principal Investigator on grants like Cloud Atlas, CERBERUS, and Urban ARK. Advised 9 PhD students who now work in academia/research globally. Active in funding initiatives like ML-Labs (SFI-funded). Labs & Teams: Leads ASEADOS Lab and maintains datasets like EM-SCA and InSDN. Collaborates globally on forensic frameworks and cybersecurity tools.
Rui Teixeira is an Assistant Professor in the School of Civil Engineering at University College Dublin (UCD). He leads UCD's Centre for Critical Infrastructure Research (CCIR) and focuses on Uncertainty Quantification, Safety, and Risk in civil engineering systems, with applications to infrastructure resilience. His research emphasizes reliability analysis, multi-fidelity modeling, and AI-driven risk assessment. Education: MSc in Civil Engineering, University of Porto, Portugal PhD in Civil Engineering, Trinity College Dublin Professional Certificate in University Teaching and Learning, UCD Research Interests: Development of novel reliability analysis techniques Resilience of infrastructure systems Artificial intelligence applications for risk assessment Probabilistic system evaluation and safety standards Grants & Projects: Smart Enforcement of Transport Operations (SETO), Horizon Europe (2023–2026) Optimality-Tracking Civil Engineering Systems, Enterprise Ireland (2023–2025) Floating Offshore Wind Dynamic Cables (FlOWDyn), Sustainable Energy Authority of Ireland (2024–2027) Teaching: Coordinates courses such as 'Civil Engineering Systems' and 'Design of Structures 1'. Labs/Teams: Director of the Centre for Critical Infrastructure Research (CCIR), focusing on interdisciplinary approaches to infrastructure resilience.
Jordon Gilmore, Ph.D., is an Associate Professor in the Department of Bioengineering at Clemson University's College of Engineering, Computing and Applied Sciences (CECAS). He leads the S.M.A.R.T. Lab (Intelligent Biomaterials, Biomedical Textiles, Bioinstrumentation) focusing on cutting-edge research in smart wound care, textile-based sensors, and bioprocess data engineering. Ph.D. in Bioengineering from Clemson University (2015) Expertise spanning biosensors, biomedical textiles, and AI applications Develops real-time biomarker sensing systems and infection management strategies His research interests include: Biosensor development for clinical diagnostics Biomedical textile engineering Machine learning in bioprocess modeling Physiological sensing for psychotherapy applications Contact: jagilmo@clemson.edu | Office: 401-3 Rhodes Engineering Research Center | Phone: 864-656-4262
Stephen E. Still is a Professor of Practice in the Department of Civil, Structural and Environmental Engineering at the University at Buffalo (UB), affiliated with the Institute for Sustainable Transportation and Logistics. His roles include teaching applied transportation planning and technology courses, advising students, and collaborating across disciplines between the School of Engineering and Applied Sciences and the School of Management. Prior to academia, he served as founder and managing director of Seabury Airline Planning Group and Diio, LLC, specializing in aviation consulting and IT. With over 30 years of industry experience, he held leadership roles at US Airways and United Airlines, focusing on strategic route planning, fleet management, and alliance development. Dr. Still holds a PhD in Civil Engineering and Operations Research from Princeton University, with a focus on transportation systems and economics, and a BS in Engineering (magna cum laude) from UB with a concentration in transportation planning. He has also completed advanced coursework in demand modeling at MIT. His research interests emphasize sustainable transportation systems and logistics, integrating engineering principles with operational efficiency. While his academic contributions primarily reside in transportation engineering, his interdisciplinary work incorporates wearable technology and sensor-based solutions for health monitoring, as evidenced by his extensive publication record in smoking cessation and behavioral health research. Scientific awards and grants are not explicitly mentioned in the provided information. Dr. Still’s advising and teaching focus on fostering student engagement in transportation innovation and real-world problem-solving. His professional experience bridges academia and industry, reflecting a commitment to practical applications of engineering and logistics principles.
Tae Eun Kim is an Associate Professor in Maritime Safety Management at UiT The Arctic University of Norway, working within the Department of Technology and Security. Her research, teaching, and industrial collaboration focus on maritime safety and human factors, with particular expertise in maritime safety management, accident analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. Dr. Kim's research spans four interconnected domains: maritime safety management and leadership, maritime accident and casualty analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. She has developed assessment instruments like the Safety Leadership Self-Efficacy Scale (SLSES) and conducted STAMP-based causal analyses of maritime accidents. Her work on MASS addresses safety challenges in mixed navigational environments and examines leadership competencies for autonomous shipping operations. Her human factors research explores how technological advancements impact navigators' performance, crew dynamics, and safety outcomes, including gender parity issues in the maritime industry. Dr. Kim's publication record reveals a strong focus on the intersection of maritime safety, technology, and human performance. Her recent work increasingly addresses autonomous shipping technologies, with numerous publications on AI decision transparency, learning analytics in maritime simulator training, and multi-modal data analysis for nautical skill development. She has conducted systematic reviews on simulator training approaches and scenario design, contributing significantly to methodology development in maritime education and training. Her research demonstrates a clear trajectory toward integrating emerging technologies with traditional maritime safety practices as the industry transitions toward greater automation. Dr. Kim is actively involved in several significant research projects, including the i-MASTER EU Horizon Europe Research and Innovation Project, the REFRAME project, and the SPRICE project (Multidisciplinary approach for spray icing modelling). She is a member of both the Advanced Maritime Ship Operations research group and the Maritime Safety Science (MARSCI) Research Group, demonstrating her commitment to collaborative research in maritime safety science. Dr. Kim teaches several specialized courses at UiT, including SVF-3206 Safety Management and Accident Investigation, TEK-3014 Navigation Technology, MFA-2100 Maritime Digitalization, MFA-8010 Maritime HTO (Human-Technology-Organisation) and Innovation, and MFA-2018 Maritime Administration and Leadership. Her teaching portfolio reflects the interdisciplinary nature of her expertise, bridging engineering, safety science, and organizational behavior in maritime contexts.
Erik Scheme is an Associate Professor in the Department of Electrical and Computer Engineering at the University of New Brunswick (UNB), and serves as Associate Director of the Institute of Biomedical Engineering (IBME). He holds a PhD and is a Professional Engineer (PEng). His roles include advising the Dr. J. Herbert Smith Centre for Technology Management and Entrepreneurship, emphasizing innovation in biomedical technologies and healthcare systems. His research focuses on advanced human-machine interaction through biomedical engineering, with a strong emphasis on myoelectric prosthetics, wearable sensors, and machine learning applications. Key areas include improving neuroprosthetic control via incremental learning, gait analysis using underfoot pressure sensors, and developing robust EMG-based gesture recognition systems. His work bridges clinical needs with technological innovation, addressing challenges in rehabilitation, activity monitoring, and user-centric design. Recent publications highlight advancements in adaptive control systems, sensor fusion, and ethical data practices in healthcare. His contributions span both theoretical frameworks (e.g., self-supervised learning models) and applied technologies (e.g., gold-plated 3D-printed electrodes). Dr. Scheme collaborates across disciplines, integrating robotics, signal processing, and clinical validation to create impactful solutions. His lab, affiliated with IBME, actively explores emerging areas like exhaled breath analysis for disease detection and federated learning in healthcare data analytics.
Doug L. James is a Full Professor of Computer Science at Stanford University since 2015, following roles as Associate Professor at Cornell University (2006-2015) and Assistant Professor at Carnegie Mellon University (2002-2006). He holds a PhD in Applied Mathematics from the University of British Columbia (2001), alongside earlier degrees from the same institution and the University of Western Ontario. His research focuses on computer graphics, sound synthesis, and physically-based modeling, with notable contributions to fluid simulation, cloth animation, and medical modeling. Key achievements include the 2012 Technical Achievement Award from the Academy of Motion Picture Arts and Sciences for 'Wavelet Turbulence,' and the 2013 Katayanagi Prize. He serves as a consulting Senior Research Scientist at Pixar Animation Studios and has led roles like Technical Papers Chair at SIGGRAPH 2015. His work integrates physics-based principles with interactive systems, emphasizing real-time applications and data-driven methods. Research interests span sound synthesis for animations (e.g., cloth, water, impact sounds), deformable models for medical simulation, and tools like 'svMorph' for virtual surgery planning. His publications reflect a blend of algorithmic innovation and practical applications in film, gaming, and healthcare.
Dr. Philippe Dixon is an Assistant Professor in the Department of Kinesiology & Physical Education at McGill University, with a division in Biomechanics and Neuroscience. He holds adjunct professor roles at the University of Montreal (School of Kinesiology and Physical Activity Sciences) and the University of Laval (Department of Kinesiology). His research focuses on human movement biomechanics using motion capture systems and wearable sensors, combined with machine learning for health and athletic performance optimization. He has expertise in gait analysis, muscle coactivation patterns in cerebral palsy, and predictive modeling of physiological states. Dr. Dixon earned a Post-doctoral fellowship in Public Health at Harvard University, a PhD in Engineering Science from the University of Oxford, and dual degrees in Biomechanics and Physics from McGill University. His education includes a Bachelor of Education in Mathematics and Physics (McGill), a Master of Science in Biomechanics (McGill), and a PhD in Engineering Science (Oxford). He has received grants such as the NSERC Discovery Grant (2022–2027) and the FRQSC AUDACE Grant (2022). His work emphasizes wearable sensor integration, with contributions to datasets like NACOB and tools like OpenOFM. He currently supervises Master’s and PhD students in biomechanics and machine learning applications. Key research themes include gait adaptations on uneven surfaces, machine learning for cough detection via smart garments, and musculoskeletal coordination in clinical populations. His articles span biomechanical modeling, wearable sensor validation, and neuro-musculoskeletal analysis, reflecting interdisciplinary innovation in human movement science.
Robert Xiao is an Assistant Professor in the Department of Computer Science at the University of British Columbia (UBC), affiliated with the Designing for People research cluster. He holds a Ph.D. from Carnegie Mellon University and a BMath from the University of Waterloo. His research focuses on interactive technologies, including VR/AR interfaces, sensing systems, and cybersecurity. Notable contributions include Lumitrack (tracking system), TouchTools (touch interaction), and CVE-2023-37271 (Python sandbox exploit). Education: Ph.D., Human-Computer Interaction Institute, Carnegie Mellon University; BMath, Computer Science & Combinatorics, University of Waterloo Affiliations: Core member of UBC's Designing for People cluster Research interests span novel input modalities, mixed-reality systems, and security challenges. He actively competes in DEF CON CTF (multiple 1st places) and publishes in top venues like CHI, UIST, and ISMAR. Recent work explores VR decision-making, low-latency tracking, and collaborative AR/VR environments. Awards: SIGCHI Outstanding Dissertation Award, CHI Honorable Mention, DIS Honourable Mention Teaching includes courses on computer systems (CPSC 213), human-computer interaction (CPSC 554X), and cybersecurity (CPSC 436S). His lab develops tools like SurfShare (surface sharing) and VirtualNexus (collaborative AR).
Zachary E. Ross is a Professor of Geophysics at the California Institute of Technology (Caltech) and holds the William H. Hurt Scholar distinction since 2021. His research integrates machine learning, computational mathematics, and seismology to analyze earthquakes and fault zones using large seismic datasets. Education B.S., University of California, Davis (2009) M.S., California Polytechnic State University, San Luis Obispo (2011) Ph.D., University of Southern California (2016) His research focuses on high-resolution imaging of fault zones, understanding earthquake sequences in space and time, and applying artificial intelligence to seismic data analysis. He develops scalable algorithms for waveform inversion, ground-motion synthesis, and real-time seismic monitoring. Recent publications highlight his work on neural operators for wave propagation, AI-driven seismicity analysis, and induced earthquake dynamics. He teaches advanced courses including Ge 264 – Machine Learning in Geophysics and Ge 271 – Dynamics of Seismicity . Scientific Awards William H. Hurt Scholar (2021–present)
Professor Marius Portmann is the UQ-Cisco Chair of Network Security at the School of Electrical Engineering and Computer Science (EECS), University of Queensland. His expertise spans Cybersecurity, IoT, and Applied AI. He holds a PhD from ETH Zurich (2003) and has led research in Software Defined Networking (SDN), blockchain, and energy-harvesting IoT systems. Education: PhD in Electrical Engineering from Swiss Federal Institute of Technology (ETH Zurich), 2003. Research focuses on securing IoT networks, AI-driven intrusion detection, and sustainable sensor systems. He has pioneered self-powered IoT systems using energy harvesters and developed frameworks like FlowTransformer for network analysis. His work bridges theoretical advancements with practical applications in smart tourism, energy efficiency, and edge computing. Recent publications highlight innovations in DDoS detection (P4-Secure), sensor-based environmental monitoring (EcoShower), and graph-based anomaly detection (XG-BoT). His datasets (e.g., NF-ToN-IoT-v3) are widely used in ML-based cybersecurity research. Collaborations include industry partners like Cisco and institutions like RMIT. Grants and leadership roles in interdisciplinary projects underscore his impact. He advises on IoT security standards and contributes to open-source tools for network research. Current projects explore edge-AI integration and sustainable sensor networks.
