Dr. Mo Rastgaar is a Professor at Purdue Polytechnic Institute, Purdue University. He holds a PhD in Mechanical Engineering from Virginia Tech (2008) and completed a postdoctoral fellowship at MIT's Newman Laboratory for Biomechanics and Human Rehabilitation. He leads the Human-Interactive Robotics Lab (HIRoLab), focused on assistive and rehabilitation robots for enhanced mobility, particularly lower-extremity devices. His research emphasizes understanding agile gait dynamics through human experiments and modeling. Research interests include assistive robotics, cyber-physical systems, dynamics, and control systems. Notable awards include the 2014 NSF CAREER Award. He has secured grants such as the 2019 NRI Collaborative Grant on robotic ankle prosthetics and 2020 grants for undersea infrastructure. Dr. Rastgaar's work bridges biomechanics, robotics, and clinical applications, advancing prosthetic designs and human-robot interaction. Key contributions include developing steerable powered ankle-foot prostheses and exploring multi-robot systems for underwater exploration. His labs integrate interdisciplinary approaches to solve complex mobility challenges, emphasizing both technical innovation and real-world clinical impact.
Dr. Baijian "Justin" Yang serves as the Associate Dean for Research at Purdue Polytechnic Institute and is a Professor in the Department of Computer and Information Technology at Purdue University. He earned his Ph.D. in Computer Science from Michigan State University, with Master's and Bachelor's degrees in Automation (EECS) from Tsinghua University. Dr. Yang has established himself as a leader in multiple interdisciplinary research domains. Dr. Yang's educational background includes: PhD in Computer Science, Michigan State University (2002) MS in Automation (EECS), Tsinghua University (1998) BS in Automation (EECS), Tsinghua University (1995) His research interests span multiple cutting-edge domains with practical applications: Cybersecurity : Developing novel approaches for threat intelligence, security education, and network defense Big Data : Creating innovative algorithms for dimension reduction, regression with categorical variables, and tensor decomposition Applied Machine Learning : Implementing AI solutions in healthcare, manufacturing, and forestry applications Digital Forestry : Using UAV imagery and remote sensing for forest management and tree species classification Dr. Yang's publication record demonstrates significant impact across multiple disciplines, with recent work focusing on spatial transcriptomics analysis (SiGra), delirium detection using limited-lead EEG, and visual localization technologies. His research bridges theoretical advances with practical applications in healthcare, manufacturing quality control, and environmental monitoring. The interdisciplinary nature of his work is evident in collaborations spanning computer science, healthcare, forestry, and manufacturing domains. His scientific achievements have been recognized with numerous awards: 2023 HRSA Building Bridges to Better Health Competition Winner (Phase 1) and 2nd place ($100,000 prize) in Phase 3 2023 Outstanding Faculty Award in Engagement, Department of Computer and Information Technology, Purdue University 2021 Leadership in Manufacturing Award, Manufacturing Times Digital (MxD) 2021 Good to Great Award, Purdue Polytechnic 2020 Outstanding Faculty Award in Discovery, Department of Computer and Information Technology 2019 University Faculty Scholars, Purdue University As an educator and mentor, Dr. Yang has advised numerous graduate students through their PhD and Master's research. His leadership extends to significant service roles including serving as Faculty Champion for the Holistic Safety and Security research impact area at Purdue Polytechnic from 2018 to 2021, board membership with ATMAE (2014-2016), and participation in the IEEE Cybersecurity Initiative Steering Committee (2015-2017). He holds valuable industry certifications including CISSP, MCSE, and Six Sigma Black Belt, demonstrating his commitment to bridging academic research with industry practice. Dr. Yang leads multiple research projects including "Digital Forestry" for developing tools to quantify forest function, "CHEESE" (Cyber Human Ecosystem of Engaged Security Education), and "CICI" (Supporting Controlled Unclassified Information with a Campus Awareness and Risk Management Framework). His work on "Applied Machine Learning" focuses on solving real-world problems, while his "Dimension Reduction and Memory Amnestic Big Data Regression" project innovates computational algorithms for large-scale data analysis.
Niels Henze is a Professor at the Chair of Media Informatics within the Faculty of Languages, Literature and Cultural Studies at the University of Regensburg, where he has been serving since May 2018. His research centers on human-computer interaction, with a strong focus on predictive models in interactive systems, mobile interaction, augmented and virtual reality, and attention-aware computing. His research interests include: Human-Computer Interaction (HCI) Predictive modeling for runtime adaptation Mobile and wearable interaction Augmented and Virtual Reality (AR/VR) Attention-aware and context-sensitive systems Sociocognitive aspects of interactive technologies The analysis of his recent publications reveals a consistent focus on leveraging user behavior and contextual cues to build intelligent, adaptive interfaces. His work integrates machine learning with interaction design, emphasizing real-time model updates, implicit feedback, and cognitive load awareness to improve usability and user experience across mobile and immersive platforms. Scientific awards: No awards mentioned in the provided text. Niels Henze leads research in adaptive interactive systems and advises students in the field of media informatics. He has previously held a junior professorship at the University of Stuttgart and completed his doctorate at the University of Oldenburg under Susanne Boll. He is actively involved in advancing the theoretical and practical foundations of predictive and attention-aware computing. Grants and funding sources are not specified in the text. He is associated with the Institute for Information and Media, Language and Culture (I:IMSK) at the University of Regensburg, contributing to a multidisciplinary environment that bridges informatics with cultural and linguistic studies.
Alan Hunter is a Professor in Autonomous Systems at the University of Bath's Department of Mechanical Engineering. He serves as Deputy Head of Department for Workload and Wellbeing and is affiliated with the Water Innovation & Research Centre (WIRC) and the UKRI CDT in Accountable, Responsible and Transparent AI. His research focuses on underwater acoustics, signal processing, imaging, and machine intelligence, with applications in sonar-based remote sensing and marine robotics. Education: B.E. (Hons I) in Electrical and Electronic Engineering from the University of Canterbury (2001), PhD in Synthetic Aperture Sonar (SAS) from the same institution (2006). Career highlights include roles at the University of Bristol (2007-2010), TNO Netherlands (2010-2014), and NATO CMRE (2014). He has led projects on sub-sediment imaging, autonomous mine-hunting systems, and precision navigation algorithms. Research Interests: • Underwater Acoustics & Sonar Imaging • Autonomous Underwater Vehicles • Machine Learning for Acoustic Data Analysis • Non-Destructive Inspection via Ultrasound • Sustainable Coastal Protection (via UN SDG contributions) Active Projects (2023-2025+): - Noise Network Plus : Engineering a Quieter Future (EPSRC) - TESSMEX SR 4 : Naval Mine-Hunting Technology (Defence Lab) - Decision-Making with Ambiguities : Legal AI for Robotics (EPSRC) Professional Affiliations: • Senior Member, IEEE • Associate Editor, IEEE Journal of Oceanic Engineering • Collaborations with NATO, TNO, and UK Defence Orgs. Labs & Teams: • Robotics and Autonomous Systems Lab • Centre for Space, Atmospheric and Oceanic Science • WIRC @ Bath (Water Innovation Hub)
Omobolanle Ogunseiju is an Assistant Professor in the School of Building Construction at Georgia Institute of Technology . She holds a Ph.D. in Environmental Design and Planning from the Department of Building Construction at Virginia Tech. Education: Ph.D. in Environmental Design and Planning, Virginia Tech Current Role: Assistant Professor, Georgia Tech School of Building Construction Her research focuses on integrating wearable robotics and Artificial Intelligence (via digital twin , cyber-physical systems , and data sensing ) to improve construction workforce safety, health, and well-being . She explores ethical implications of automation in construction, particularly in human-technological dynamics. Key research trends include: Advancing smart communities through robotics and AI Exoskeleton evaluation for ergonomic risk reduction Mixed reality environments for construction education Data analytics for cognitive and physical risk assessment Professional identity development in construction engineering students Industry-academia alignment for sensing technology integration Scientific awards: Outstanding Doctoral Candidate, Myers-Lawson School of Construction Outstanding Doctoral Student, College of Architecture and Urban Studies at Virginia Tech Teaching philosophy emphasizes experiential learning , engagement techniques , and hierarchical assessments . She developed the Construction Cost Management course at Georgia Tech and will lead Construction Technology courses. Previously, she taught Smart Construction , Building Systems Technology , and Wireless Sensing in Construction Management at Virginia Tech.
Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols
Dr. Brett J. Borghetti is a Professor of Computer Science in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT), Graduate School of Engineering and Management, Wright-Patterson AFB, OH. He was promoted to Professor in July 2022, following prior appointments as Associate Professor (2017) and Assistant Professor (2008/2013). His expertise lies in artificial intelligence, machine learning, deep learning, cybersecurity, and human-machine teaming. Education: Ph.D. in Computer Science, University of Minnesota, Twin Cities (2008) M.S. in Computer Systems, Air Force Institute of Technology (1996) B.S. in Electrical Engineering, Worcester Polytechnic Institute (1992) Dr. Borghetti's research focuses on applying machine learning to physical science sensors (hyperspectral, seismic, RF), cybersecurity, and enhancing human-machine team performance. He teaches graduate courses in machine learning, AI, data security, and algorithm design, and advises numerous MS and PhD students in areas such as sensor exploitation, cognitive workload, and cyber situational awareness. His recent publications demonstrate strong trends in deep learning for multimodal sensor fusion, nuclear security, and neuroergonomics. Scientific Awards: AETC Educator of the Year (2021, Civilian) AFIT Ezra Kotcher Teaching Award (2021) AFIT Teaching Excellence Award (2019) AF STEM Outstanding Science and Educator Award (2015) Multiple Eta Kappa Nu Outstanding Instructor Awards Air Force Meritorious Service Medal and other military honors Dr. Borghetti has advised numerous graduate students and led research projects with significant funding and applications in defense and national security. He has directed research in AI-driven sensor analysis, cyber defense systems, and adaptive automation. His work often involves collaboration with national labs and DoD agencies. He has contributed to major research initiatives in human factors, cyber intruder detection, and machine learning for operational environments. Labs and Research Teams: His work is associated with AFIT's research in cyber security, sensor exploitation, and human-machine systems. He collaborates with teams working on the Cyber Intruder Alert Testbed (CIAT), neuroergonomic modeling, and machine learning for defense applications.
Dr. Jackie Cha serves as an Assistant Professor in the Department of Industrial Engineering within Clemson University's College of Engineering, Computing and Applied Sciences. Her research bridges human factors engineering with healthcare innovation, focusing on surgical robotics, physiological signal analysis, and wearable medical technologies to enhance clinical performance and safety. Her academic foundation includes advanced degrees from leading institutions: Ph.D. in Industrial Engineering from Purdue University M.S.E. in Biomedical Engineering from the University of Michigan B.S.E. in Biomedical Engineering from the University of Michigan Cha's research program centers on quantifying human performance in high-stakes medical environments through sensor-based metrics. She investigates nontechnical skills in surgical teams, mental workload during robotic procedures, and ergonomics of exoskeleton implementation in operating rooms. Her work integrates physiological signals, eye-tracking, and proximity sensors to develop objective assessment tools for surgical proficiency and team dynamics. Analysis of her 2023-2025 publications reveals consistent thematic focus on human-robot collaboration in surgery, with emerging trends in AI-driven workload detection (s-DResNet), neural correlates of surgical expertise, and environmental factors affecting robotic surgery outcomes. Key methodological approaches include scoping reviews of human-robot interaction metrics, mixed-methods evaluations of exoskeleton efficacy, and extended reality applications for nontechnical skills training. She leads the ECHO Lab (Engineering for Clinical and Human Outcomes) at Clemson, which develops translational solutions for healthcare human factors challenges. Her lab's work spans from fundamental physiological signal analysis to applied interventions in operating rooms and emergency medical settings.
Tarmo Lipping is a Professor in the Department of Computer Science and Engineering at the Faculty of Information Technology and Electrical Engineering, University of Oulu. His work bridges computing sciences with biomedical engineering, environmental modelling, and data-driven societal applications. Doctor of Science (Technology), Information Technology – Awarded 14 Feb 2001 Master of Science (Technology), Information Technology – Awarded 10 Sept 1993 His research focuses on electroencephalography (EEG) , mental workload assessment , depth of anesthesia monitoring , and machine learning applications in healthcare and human-computer interaction. He also contributes to environmental informatics , particularly in land uplift modelling and radionuclide transport , aligning with UN Sustainable Development Goals. Recent publications highlight trends in transformer networks for EEG analysis , wearable HCI systems , data-driven food safety , and participatory municipal governance . His work integrates deep learning, signal processing, and real-world deployment. Scientific awards include: CIMO opettajavaihto (2017) Lipping has supervised numerous master’s students and served as an examiner in diverse topics including data vault modelling , telecom revenue estimation , and EEG hyperscanning . He has evaluated funding applications, acted as a journal reviewer (65 times), and contributed to editorial work. His activities reflect strong engagement in academic service and interdisciplinary research mentorship. He has contributed datasets on Fennoscandian land uplift , lake isolation , and archaeological shorelines to PANGAEA, supporting open science in geosciences and environmental history.
Dikai Liu is a Distinguished Professor and Strategic Research Director at the University of Technology Sydney (UTS), Australia, within the School of Mechanical and Mechatronic Engineering . His work spans field robotics and human-robot collaboration (HRC) , focusing on autonomous systems for infrastructure maintenance, construction automation, and underwater operations. Key research areas: Robotics, Human-Robot Interaction, Bio-Inspired Design, Infrastructure Maintenance Recent publications highlight innovations in trust modeling for HRC, stiffness control in continuum robots, and sociotechnical frameworks for AI-driven robotic systems. His 15 most recent articles emphasize applications in bridge maintenance, construction automation, and ethical AI integration. Awards include the 2019 UTS Medal for Research Impact, ASME DED Leonardo da Vinci Award (USA), and multiple engineering excellence recognitions. His research has generated over $22M in external funding, including 13 ARC grants and industry partnerships.
Bala Balasingam is a Professor at the University of Windsor's Faculty of Engineering, specializing in interdisciplinary research at the intersection of electrical engineering, human factors, and autonomous systems. His work focuses on battery management systems, cognitive load assessment, and the human aspects of automated driving. Collaborating with the Faculty of Human Kinetics, he addresses challenges related to driver distraction and vigilance in autonomous vehicles. Research interests include battery parameter estimation, real-time state-of-charge tracking, and thermal management of lithium-ion batteries. His team employs advanced methods such as electrochemical impedance spectroscopy (EIS), Kalman filtering, and machine learning for battery diagnostics. In human factors, his studies utilize eye-tracking and biometric sensors to evaluate cognitive workload during complex tasks like vehicle takeovers in automated systems. Key contributions include novel approaches to battery internal resistance estimation, optimized charging algorithms, and validation frameworks for battery management systems. His recent work explores the integration of portable devices in automated driving systems and the impact of cognitive load on driver performance. Collaborations span engineering and kinesiology domains, emphasizing practical applications in transportation and energy sectors. Labs/Teams: Leads interdisciplinary projects combining electrical engineering and human kinetics expertise, with a focus on real-world applications in automotive and industrial automation.
Hans Petter Hildre is Head of Department at the Department of Ocean Operations and Civil Engineering , part of the Faculty of Engineering at the Norwegian University of Science and Technology (NTNU). His work focuses on maritime engineering, digital twin technology, and marine operations. Research interests include: Digital Twin Applications in Maritime Industry Offshore Operations and Wind Turbine Installation Marine Robotics and Autonomous Systems Wave Field Estimation and Environmental Load Analysis Human-Machine Interaction in Maritime Contexts Co-simulation and Real-time Monitoring Recent publications highlight trends in: Wave shielding effects for offshore vessels Knowledge transfer from automotive/aviation to maritime Crane path planning using digital twins Visual attention zone recognition systems Hydrodynamic modeling and sensitivity analysis Smart city-maritime integration Scientific collaborations span institutions including: European Commission (Future Skills Reports) Royal Institution of Naval Architects The American Society of Mechanical Engineers (ASME) IEEE Transactions on multiple domains Springer Publishing
David Jensen is a Professor in the College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. He directs the Knowledge Discovery Laboratory and the Computational Social Science Institute. His research focuses on machine learning, causal modeling, and analyzing large social, technological, and computational systems. Jensen's work is supported by organizations like the National Science Foundation and DARPA. Education: DSc in Engineering and Policy, Washington University in St. Louis (1992) MS in Engineering and Policy, Washington University in St. Louis (1988) BS in Mechanical Engineering, University of Nebraska (1986) Research Interests: Causal inference in relational and dynamic systems Machine learning applications in security and privacy Computational social science Large-scale network analysis Achievements: Recipient of teaching awards from UMass College of Natural Sciences (2011) and CICS (2022) 2017 IEEE INFOCOM Test of Time Paper Award Leadership roles in conferences and journals, including action editor for the Journal of Machine Learning Research Labs and Affiliations: Founder of the Knowledge Discovery Laboratory (2000) Director of the Computational Social Science Institute (2018-2022) Member of the Computing Community Consortium (CCC) Council
Carlos Cifuentes is an Associate Professor in Human-Robot Interaction at the Bristol Robotics Laboratory (BRL) , part of the University of the West of England (UWE Bristol) . He also serves as the Deputy Director of the VIVO Hub , a £13.4M UK-funded research initiative (2024-2030) focused on robotics for rehabilitation and healthcare. His research spans Human-Robot Interaction , Rehabilitation Robotics , Healthcare Robotics , and Socially Assistive Robotics , with applications for conditions such as cardiac diseases , post-stroke recovery , spinal cord injuries , cerebral palsy , Parkinson's disease , musculoskeletal disorders , and autism spectrum disorder (ASD) . Carlos has over 15 years of experience and 200+ publications in robotics for rehabilitation and assistive technologies. His recent work explores smart walkers with multimodal feedback, soft prosthetics using polymeric optical fiber sensors , and machine learning models for fatigue and stress estimation. He also investigates inclusive design for social robots in global contexts , including a CASTOR Robot for ASD therapy and collaborative design processes with Colombian communities. Carlos serves as an Associate Editor for IEEE Robotics and Automation Magazine (since 2021), ICRA , and IROS (since 2023). He leads projects integrating wearable sensors , deep learning , and haptic feedback to enhance mobility, autonomy, and quality of life for individuals with disabilities. As Deputy Director of the VIVO Hub, he focuses on long-term deployment of robotic systems in real-world healthcare settings, emphasizing collaboration with clinicians , caregivers , and neurodiverse communities . His work bridges robotics , biomedical engineering , and human-centered design .
Denny Yu is an Associate Professor at the Edwardson School of Industrial Engineering, Purdue University. His work bridges human factors, neuroergonomics, and healthcare safety through advanced sensor systems and AI. Primary Affiliation : Edwardson School of Industrial Engineering, Purdue University Research Themes : Surgical ergonomics, autonomous vehicle human factors, cognitive workload assessment, multimodal physiological sensing Dr. Yu's research focuses on neuroergonomics and human-robot interaction , particularly in surgical and transportation contexts. His team develops sensor-based systems for workload monitoring, including: EEG-eye tracking fusion for situation awareness Wearable exoskeletons for surgical posture support Computer vision tools for lifting task risk analysis Smart infusion pump usability frameworks AI-driven surgical coaching systems Recent publications emphasize deep learning applications in soft tissue deformation estimation and real-time adaptive systems for robotic surgery augmentation. His work spans both occupational health (veterinary surgeons, airport workers) and medical device innovation domains.
