Find Academic Supervisors

• Agricultural Safety and Health
• Occupational Ergonomics
• Biomedical Engineering for Rural Populations
• +6 more

Aaron M. Yoder, PhD , is an Associate Professor jointly appointed in the Department of Biological Systems Engineering at the University of Nebraska–Lincoln (UNL) and the Department of Environmental, Agricultural and Occupational Health at the University of Nebraska Medical Center (UNMC). He devotes 10 % effort to UNL and 90 % to UNMC, directs or co-directs the Central States Center for Agricultural Safety and Health (CS-CASH) and Nebraska AgrAbility , and is a key faculty member of the Biomedical Engineering, Health, and Safety Systems emphasis area. Education & Certifications: PhD — field not explicitly stated in text, but research record indicates advanced training in agricultural safety/ergonomics/biomedical engineering. Research Interests: Yoder’s work sits at the intersection of engineering, public health, and behavioral science . He designs and evaluates technology-enabled interventions —from wearable sensors that monitor heat strain during field work to immersive virtual reality modules that teach youth safe tractor operation. His portfolio spans: ergonomic redesign of agricultural machinery for vulnerable populations (women, aging farmers, workers with disabilities); implementation-science approaches that translate evidence-based safety programs into real-world practice across U.S. states and low-middle-income countries; use of social marketing and narrative storytelling to shift attitudes and behaviors around roll-over protective structures (ROPS), all-terrain vehicles, and colorectal cancer screening in rural communities; real-time IoT dashboards for first responders and heavy-machinery operators that fuse environmental and physiological data to prevent injury and illness; mental health and substance-use surveillance among farming populations, with recent work in Nigeria and the Central States cattle-feeding sector. Publication Trends: Across the 15 most recent papers (2023-2025) a clear trajectory emerges: rigorous mixed-methods evaluation of large-scale safety interventions ; integration of wearable sensors, VR, and IoT into occupational health practice; and a growing global focus on low-resource settings. Heat-stress mitigation, cancer-screening promotion, and ATV/ROPS safety dominate the engineering–public-health interface. Scientific Awards & Recognition: No specific awards are enumerated in the supplied text. Funding, Leadership & Mentorship: Principal or Co-Investigator on numerous CDC/NIOSH and USDA-NIFA grants supporting CS-CASH, AgrAbility, and international collaborations. Leads multidisciplinary teams of engineers, epidemiologists, extension educators, and community partners across Nebraska, the Midwest, and sub-Saharan Africa. Active mentor to graduate students and post-doctoral fellows in Biological Systems Engineering and the College of Public Health (specific student names not provided). Labs & Centers: Yoder directs activities within the Central States Center for Agricultural Safety and Health (a CDC/NIOSH-funded Agricultural Safety and Health Center) and Nebraska AgrAbility (USDA-NIFA), leveraging state-of-the-art motion-capture, sensor fabrication, and VR development laboratories shared between UNL and UNMC.

• Parallel Computing
• Distributed Systems
• Intelligent Storage Systems
• +5 more

Cheng Li is an Associate Professor at the School of Computer Science, University of Science and Technology of China , and Director of the Information Computing Platform at the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center. His research focuses on parallel and distributed intelligent computing systems, with an emphasis on optimizing computational efficiency through data-centric approaches. Education: PhD in Computer Science from Max Planck Institute for Software Systems (MPI-SWS) and Saarland University (2016) Bachelor's degree in Computer Science from Nankai University (2009) Research interests include distributed systems, machine learning optimization, database systems, and high-performance computing. Notable contributions include innovations in distributed training of deep neural networks, geo-replicated databases, and efficient graph processing. His work has been published in top-tier conferences like NSDI, AAAI, VLDB, and SOSP. Professional Activities : PC member at OSDI 2025, EuroSys 2024/2025, FAST 2024, and SOSP 2021. Teaching includes Systems Seminar and Compiler Principles at USTC since 2017. Grants : Secured $500k/year funding from Chinese government agencies and collaborations with Huawei/Alibaba. Active in cloud-native systems and AI infrastructure research.

Bo JiView profile

Associate Professor

• Networking
• Machine Learning
• Security and Privacy
• +5 more

Bo Ji is an Associate Professor in the Department of Computer Science and a Faculty Fellow in the College of Engineering at Virginia Tech. He holds a Ph.D. in Electrical and Computer Engineering from The Ohio State University (2012) and M.E. and B.E. degrees in Information Science from Zhejiang University (China). Prior to Virginia Tech, he was an Associate Professor at Temple University and a Senior Member at AT&T Labs. Research Interests: His work focuses on the synergy between networking and artificial intelligence/machine learning, addressing challenges in wireless networks, edge computing, data centers, and IoT systems. Key areas include optimizing data freshness (Age of Information), security/privacy in AR/XR, and efficient resource allocation. His research combines theoretical insights with empirical studies, supported by NSF awards and industry collaborations. Awards and Recognition: Bo Ji has received the NSF CAREER Award (2017), IEEE INFOCOM Best Paper Award (2019), IEEE TNSE Excellent Editor Award (2021-2024), and Dean's Faculty Fellow Award (2023). He is a Senior Member of IEEE/ACM and serves on editorial boards for journals like IEEE/ACM Transactions on Networking and ACM SIGMETRICS. Grants and Labs: Leads the Synergistic Networking and Augmented Intelligence Lab (SNAIL). Active in securing grants from NSF, Amazon, and ICAT/CHCI for projects on AR privacy, AI-augmented decision-making, and federated learning systems. Collaborates on interdisciplinary projects with experts in cybersecurity and human-computer interaction. Teaching: Teaches courses in algorithms (CS 4104/6104) and online learning at Virginia Tech, with prior experience at Temple University.

Trish M. PerlView profile

Professor

• Antimicrobial Resistance
• Healthcare-Associated Infections
• Respiratory Infections
• +4 more

Trish M. Perl, M.D., M.Sc. serves as Professor in the Department of Internal Medicine at UT Southwestern Medical Center and Chief of the Division of Infectious Diseases and Geographic Medicine. She holds the H. Ben and Isabelle T. Decherd Chair in Internal Medicine and maintains active leadership roles on national committees including the WHO’s COVID-19 Ad-Hoc IPC Experts Panel, CDC’s COVID Team B Advisory Committee, and NIH/NIAID Microbiology and Infectious Diseases study section. Medical Degree: University of North Carolina at Chapel Hill Residency & Fellowship: McGill University’s Royal Victoria Hospital Advanced Training: University of Iowa Hospitals and Clinics (Infectious Diseases & Clinical Epidemiology) Master of Science: Epidemiology and Biostatistics from McGill University Dr. Perl’s research focuses on antimicrobial resistance mechanisms, C. difficile epidemiology, respiratory infection prevention, and healthcare-associated transmission dynamics. Her work integrates clinical epidemiology with practical infection control interventions, particularly in pandemic settings. She pioneered the Respiratory Protection Effectiveness Clinical Trial (ResPECT) investigating N95 respirator efficacy against influenza transmission among healthcare personnel. Her publication trends reveal consistent focus on emerging pathogens, with recent work analyzing socioeconomic drivers of antimicrobial resistance, pandemic response strategies, and innovative infection control technologies. Key thematic evolution shows progression from classic healthcare epidemiology to complex systems analysis of pandemics and health disparities. Senior Scholar Award, Society for Healthcare Epidemiology of America (2020) H. Ben and Isabelle T. Decherd Chair in Internal Medicine Dr. Perl directs significant NIH-funded research on infection prevention, with emphasis on pragmatic clinical trials and policy-relevant outcomes. Her grant portfolio includes multi-center studies on respiratory pathogen transmission, antimicrobial stewardship implementation, and healthcare worker protection during pandemics. She actively mentors trainees through UT Southwestern’s infectious diseases fellowship program and contributes to national guideline development. Her laboratory and team focus on the ResPECT research network, which conducts cluster-randomized trials in healthcare settings. Current initiatives include evaluating novel disinfection systems, developing predictive models for infection outbreaks, and implementing community-based surveillance for antimicrobial-resistant pathogens.

• Robotics
• Computer Vision
• 3D Reconstruction
• +2 more

Anurag Dalal is a PhD Research Fellow at the University of Agder's Department of Engineering Sciences, actively contributing to the Robotics and automation research group. His work focuses on cutting-edge computer vision and 3D reconstruction methodologies. His research interests center on Robotics , Computer Vision , and 3D Reconstruction , with specific expertise in neural rendering techniques and automated scene modeling. Current projects involve advancing Gaussian Splatting methodologies for real-time applications in robotics and virtual environments. Dalal's publication record demonstrates specialization in novel view synthesis and 3D scene representation, with a 2024 IEEE Access review establishing him as an emerging expert in point-based rendering techniques. His work bridges theoretical computer graphics with practical robotics applications. As a Research Fellow, he participates in the university's Robotics and automation research ecosystem, collaborating with senior researchers on projects involving 3D perception systems. His technical contributions support the department's focus on intelligent automation solutions.

• Human Activity Recognition
• Wearable Technology
• Machine Learning
• +4 more

Dr. Thomas Ploetz is a researcher at Newcastle University, specializing in human activity recognition, wearable technology, and machine learning applications across healthcare and agriculture. His work spans clinical applications such as stroke rehabilitation, mental health monitoring, and Parkinson's disease assessment, alongside agricultural advancements in livestock health and behavior analysis. He has pioneered methods using accelerometers and deep learning for automated health monitoring and behavior tracking in both humans and animals. Key projects include the WAVES initiative (using wristband accelerometers to motivate post-stroke arm exercises), automated detection of respiratory diseases in pigs, and the development of sensor-based systems for surgical skill assessment. His interdisciplinary collaborations involve experts from computer science, veterinary medicine, and clinical neuroscience. While no formal educational background is explicitly stated, his research demonstrates expertise in sensor data analysis, machine learning algorithms, and human-computer interaction. Dr. Ploetz's contributions include over 150 publications (selected in the articles list) on topics like activity recognition models, health monitoring systems, and smart environment technologies. His work emphasizes practical applications of ubiquitous computing in healthcare, agriculture, and education.

Robert LoftinView profile

Lecturer

• Ad Hoc Human-AI Cooperation
• Human-AI Alignment
• Human-in-the-loop Machine Learning
• +6 more

Dr. Robert Loftin is a Lecturer in Machine Learning at the University of Sheffield’s School of Computer Science. His research focuses on Ad Hoc Human-AI Cooperation, Human-AI Alignment, and Human-in-the-loop Machine Learning, with expertise in Deep Reinforcement Learning and Multi-Agent Systems. He holds a PhD from North Carolina State University (2019) and a Bachelor’s from Georgia Tech (2011). Postdoctoral work includes roles at Microsoft Research Cambridge and TU Delft, exploring AI applications in gaming and multi-agent cooperation. His research interests span AI ethics, human-robot interaction, and games, with a strong emphasis on practical applications of interactive learning. Recent work includes advancements in entropy-based coordination for multi-agent systems (2023–2025) and theoretical studies on cooperation in socially rational agent populations. He contributes to the Machine Learning research group and has published extensively in top venues like NeurIPS, AAMAS, and AAAI. Publications highlight innovations in curriculum design, exploration strategies, and adaptive feedback mechanisms. His work bridges theoretical foundations and real-world applications, particularly in cooperative and competitive multi-agent environments. Current projects explore safe team coordination and scalable strategies for high-dimensional state spaces.

• Human Computer Interaction
• Digital Transformation
• User Experience Design (UX)
• +7 more

Maurizio Caon is a Full Professor and Head of Institute at the Fribourg School of Management (HES-SO), specializing in Human-Computer Interaction and Digital Transformation. His research focuses on health technology interventions for aging populations and adolescents, with a particular emphasis on e-coaching systems, wearable devices, and participatory design. He leads EU-funded projects like NESTORE (2017-2021), developing virtual coaches for older adults' well-being, and PEGASO (2013-2017), targeting adolescent health through gamified mobile platforms. Education: Not explicitly stated in text, but expertise in Ergonomics and Information Systems is implied through research focus. Research Interests: Designing human-centered technologies for health promotion, including tangible interfaces, behavior change models, and cross-cultural co-design. Key areas include aging workforce strategies, digital self-tracking, and ethical data practices. His work bridges HCI, healthcare innovation, and social impact. Publications highlight innovations in e-coach systems (e.g., NESTORE's multi-domain pathway), wearable technology's psychological impact, and VR exergames for seniors. Projects involve partnerships with Politecnico di Milano, EIA HumanTech Institute, and international teams. Grants: Principal investigator and co-investigator on EU H2020 and FP7 grants totaling over 890,000 CHF. Team: Collaborates with researchers like Leonardo Angelini, Elena Mugellini, and Omar Abou Khaled on interdisciplinary projects. Labs/Teams: Leading the NESTORE and PEGASO teams, focusing on digital health solutions for aging and youth populations. Involved in design processes for inclusive public spaces and ergonomic interfaces for cyclists.

Azalia MirhoseiniView profile

Assistant Professor

• AI Systems
• Chip Design Automation
• Deep Reinforcement Learning
• +3 more

Azalia Mirhoseini is an Assistant Professor of Computer Science at Stanford University and founder of the Scaling Intelligence Lab. She also serves as a Senior Staff Scientist at Google DeepMind. Her research focuses on scalable and self-improving AI systems, including advancements in chip design automation, large language models, and reinforcement learning applications. Prior roles include co-founding the ML for Systems team at Google Brain. Education: BSc in Electrical Engineering from Sharif University of Technology; PhD in Electrical and Computer Engineering from Rice University. Awards include MIT Technology Review’s 35 Under 35 and Best ECE Thesis Award. Research highlights include AlphaChip (deep RL for chip layout optimization), Mixture-of-Experts (MoE) architectures, and Constitutional AI frameworks for alignment. Her work bridges AI and systems, addressing real-world challenges in hardware design and scalable AI. Key contributions span over 50 publications in top venues like Nature , NeurIPS , and ICLR . Media coverage includes MIT Tech Review, IEEE Spectrum, and WIRED. Teaching includes CS229s: Systems for Machine Learning. Labs/Teams: Scaling Intelligence Lab (Stanford), collaborations with Google Research/DeepMind. Advising/Grants: Mentors students through Stanford; her work is funded via industry-academic partnerships.

• Maritime Informatics
• Autonomous Systems
• Big Data Analytics
• +4 more

Associate Professor Dimitris Zisis leads the Smart Move Laboratory at the University of the Aegean's Department of Product & Systems Design Engineering, focusing on autonomous vessels and marine robotics. His research spans maritime informatics, trajectory analytics, and Big Data applications. He has published over 80 works with 3,900+ citations, including a top-0.1% cited paper on cloud computing security. As a Horizon Europe National Representative for Cluster 4 (Digital, Industry, Space), he advises EU digital policy. He previously led BDVA's Data Science/AI Task Force and participated in EU High-Level Expert Groups on B2G data sharing. He chairs the IEEE's maritime systems committees and edits Elsevier's Future Generation Computer Systems journal. Projects: Horizon 2020 VesselAI, INFORE, BigDataOcean Awards: Top 2% scientist in Information Systems (2019-2021) Memberships: IEEE Senior Member, Hellenic Institute of Marine Technology Fellow His lab develops advanced maritime systems, including the Accu-Waves platform for port safety and the Ro-Boat Race for autonomous vessel innovation. Recent work emphasizes federated learning for vessel location forecasting, scalable maritime event detection, and digital twin applications.

• Timber Construction
• Structural Engineering
• Sustainable Architecture
• +3 more

Emre Ilgin is a Postdoctoral Research Fellow within the Faculty of Built Environment at Tampere University, specializing in Civil Engineering. His research focuses on timber construction, structural engineering, and sustainable architecture, with a particular emphasis on tall timber buildings and fire safety solutions. He holds a strong interest in analyzing space efficiency in supertall towers, aerodynamic design considerations, and innovative timber-based construction technologies. His work bridges architectural innovation with structural practicality, addressing challenges in contemporary building practices while advocating for eco-friendly materials and methods. Key research areas include cross-laminated timber (CLT) applications, dovetail massive wood board elements, and the integration of renewable energy systems into tall structures. Ilgin has contributed to over 60 peer-reviewed articles since 2021, with recent studies evaluating fire performance comparisons between dovetail and CLT elements, analyzing global supertall building typologies, and examining Finnish timber construction trends. His work frequently addresses the interplay between architectural form, structural integrity, and environmental sustainability. Ilgin’s expertise extends to suburban development strategies in Finland, wood preservation practices, and life-cycle assessments of hybrid, concrete, and timber apartment buildings. His research also explores residents’ perceptions of timber apartment living and the future prospects of cross-laminated timber in global construction markets. He is actively involved in experimental studies on sound insulation properties of timber elements and the aerodynamic optimization of tapered supertall forms. While no specific awards or grants are highlighted, his extensive publication record reflects a dedication to advancing sustainable construction practices and tall timber building technologies. Ilgin collaborates with international experts and industry stakeholders, aiming to shape future standards in eco-conscious architectural and engineering design.

Lena ErikssonView profile

Senior Lecturer

• Forensic Mental Health
• Medico-Legal Decision-Making
• Public Health Policy
• +3 more

Lena Eriksson is a Senior Lecturer and Associate Professor in Theory of Science at the University of Gothenburg's Department of Linguistics and Theory of Science. Her work focuses on decision-making processes at the intersection of state institutions, professions, and citizens, particularly in medico-legal contexts. She holds a PhD from Cardiff University and has managed projects funded by the Swedish Research Council and the Swedish Social Insurance Agency. Her research examines sick leave practices, coerced care decisions, and forensic psychiatric discharge processes, exploring how medical needs are defined and assessed across legal and administrative frameworks. She has held leadership roles including Vice-Dean for Education (2016-2020). Key research areas include healthcare ethics, policy implementation, and the sociology of scientific knowledge. Her work bridges public health, law, and philosophy, analyzing how institutional decisions shape individual rights and responsibilities. Notable contributions address the role of standards in stem cell research and the governance of post-normal science in healthcare settings. Recent publications explore therapeutic logic in mental health law, balancing orders of worth in healthcare implementation, and the material dimensions of post-evidence-based practice. Her interdisciplinary approach engages psychiatry, law, and public health to uncover systemic implications of medico-legal assessments on welfare state operations.

Andrew T. DuchowskiView profile

Professor

• Visual Perception
• Human-Computer Interaction (HCI)
• Eye Tracking
• +6 more

Andrew T. Duchowski is a Professor and Chair of the Visual Computing Division at Clemson University's School of Computing (part of the College of Engineering and Science). He holds a Ph.D. in Computer Science from Texas A&M University (1997) and a B.Sc. in Computer Science from Simon Fraser University (1990). His academic roles include service as Focus Area Chair at SIGGRAPH 2019 and Co-organizer of multiple workshops such as MobileHCI 2018 and ETRA 2018. His research focuses on eye tracking, visual perception, human-computer interaction, and computer graphics. Key areas include gaze analytics, virtual environments, and applications in healthcare, education, and cultural heritage. He has pioneered methodologies like the 'Gaze Analytics Pipeline' and authored Eye Tracking Methodology: Theory & Practice (Springer, 3rd ed., 2017). R&D interests span cognitive load measurement via pupil dynamics, ambient/focal attention modeling, and gaze-based interaction design. His work bridges computer science with fields like spatial cognition and neuroergonomics. Recent projects include studies on attention in VR, neurocognitive biomarkers, and sustainable cultural landscape management. Awarded multiple honors including the NSF CAREER Award (2000-2003) and Clemson's Faculty Excellence Award (2001), Duchowski has authored over 150 peer-reviewed papers. He led educational initiatives such as the 'Groovy Graphics Assignments' for SIGGRAPH and co-organized global conferences like ETRA and EuroGraphics. His service includes editorial roles in journals like Transactions on Applied Perception and reviewing for NIH, NSF, and international universities.

• Human-Computer Interaction
• Online Safety
• Youth and Adolescent Digital Well-being
• +5 more

Jinkyung Katie Park is an Assistant Professor in the School of Computing at Clemson University, an affiliated faculty member of the Media Forensics Hub, and co-director of the Human And Technology Lab (HATLab). Her work sits at the intersection of Human-Computer Interaction, online safety, and human-centered AI, with a passionate focus on protecting vulnerable populations—especially adolescents—in digital spaces. Education: Ph.D. in Information Science, Rutgers University, 2022 M.A. in Records & Archives Management, 2017 B.B.A. in Business Administration, 2011 Research Interests: Dr. Park’s scholarship centers on Human-Computer Interaction for Online Safety . She investigates the psychological and social mechanisms behind online risk (e.g., incivility, privacy violations) and designs socio-technical interventions that empower youth rather than merely restrict them. Her recent projects span: Resilience-based frameworks for adolescent digital well-being Human-AI collaborative systems for real-time risk detection on social media Participatory co-design of privacy and safety tools with teens Ethical, explainable AI that encodes human values for mental-health and conversational agents Methodologically, she integrates qualitative, quantitative, and computational techniques—interviews, participatory design, surveys, NLP, and machine learning—to produce actionable insights for designers, policymakers, and educators. Publications Trend: Across her 15 most recent papers (2024-2025) she consistently tackles youth online safety through interdisciplinary lenses—HCI, AI, social computing, and health informatics. Collectively this corpus signals a shift from adult-centric, fear-based models toward resilience, empowerment, and community-oriented solutions, often co-created with adolescents themselves. Scientific Awards & Recognition: Rutgers iSchool Dissertation Award (runner-up) Outstanding Graduating Student Award, Rutgers University Multiple NSF-funded project grants (PI/co-PI) Funding & Advising: Dr. Park has served as PI or co-PI on several NSF awards focusing on youth online safety, AI-mediated risk detection, and community-based interventions. While specific grant codes and dollar amounts are not listed, the narrative emphasizes sustained federal support for her interdisciplinary work. No individual student names are disclosed in the provided source. Labs & Teams: At Clemson she co-directs the Human And Technology Lab (HATLab) and holds an affiliated appointment with the Media Forensics Hub , positioning her to collaborate with computing, social science, and forensics researchers on large-scale, convergent projects.

Xi LuView profile

Assistant Professor

• Human-Computer Interaction
• Health
• Social Computing
• +3 more

Xi Lu is an Assistant Professor at the University at Buffalo, holding dual appointments in the Department of Computer Science and Engineering (School of Engineering and Applied Sciences) and the Department of Information Science (Graduate School of Education). Their research focuses on Human-Computer Interaction (HCI), Health Technologies, Social Computing, and Design, with emphasis on topics such as self-tracking, virtual/augmented reality applications, and culturally aware health technologies. Dr. Lu's educational background includes a PhD in Informatics from the University of California, Irvine (2024), an MS in Human-Computer Interaction/Design from Indiana University (2019), and a BE in Industrial Engineering from Xi'an Jiaotong University (2017). Their work bridges technical innovation with user-centered design, addressing societal challenges in healthcare, education, and everyday well-being. Research Interests Dr. Lu's research explores how technology can enhance health behaviors, social interactions, and cultural contexts. Key themes include: Design of health-tracking systems for chronic conditions (e.g., PCOS) Social VR applications for mindfulness and group therapy Cultural influences on persuasive technology adoption Conversational AI for food journaling and dietary support Ethical implications of AI in analyzing social behaviors Recent Work Trends Their publications (2020–2025) reflect a focus on: Multi-modal AI ethics in social behavior analysis Cultural dimensions in health app design Collaborative health tracking in pregnancy AR/VR systems for mindfulness Awards & Grants No awards or grants explicitly listed in provided materials. Labs & Teams Affiliated with the Human-Computer Interaction Lab and Health Informatics Group at UB, though specific lab names are not explicitly stated in the text.