Anna-Lena Sachs is a Senior Lecturer in Predictive Analytics at Lancaster University's Management Science department. Her research bridges inventory management, behavioural operations, and forecasting, with applications in retail, healthcare, automotive, and logistics sectors. She develops quantitative models and leverages industry datasets to solve practical supply chain challenges. Research Interests : Inventory management for spare parts, data-driven decision support systems, multi-echelon optimization, markdown pricing strategies, and human decision behavior in operational contexts. She emphasizes translating academic insights into industry practice through field experiments and lab studies. Scientific Recognition : Dean’s Award for Academic Excellence Fellow of the Higher Education Academy (ATLAS) Research Impact Award for Centre for Marketing Analytics and Forecasting PhD Supervision : Actively mentors students in Operations Research, Management Science, and supply chain analytics. Current PhD candidates include Ritika Arora, Benjamin Lowery, Adam Page, Carlos Rodriguez Calderon, and Joe Rutherford. Collaborative Networks : Affiliated with Lancaster’s STOR-i Centre for Doctoral Training, Centre for Marketing Analytics & Forecasting, and Data Science Institute. She has led projects with Royal Mail, Jaguar Land Rover, and GlaxoSmithKline.
Ahmad BahooToroody is an Academy Research Fellow at Aalto University’s Department of Energy and Mechanical Engineering, specializing in Bayesian statistics, reliability engineering, and risk analysis for autonomous maritime systems. He is actively involved with the Marine and Arctic Technology research group and leads projects that integrate machine learning with safety-critical applications in the maritime and offshore sectors. Research Interests Bayesian statistical methods for reliability and risk modeling Machine learning and deep learning for anomaly detection in autonomous systems Safety assessment of offshore installations and maritime operations Prognostic health management of marine renewable energy systems Human factors and expert judgment in sociotechnical maritime systems His work often incorporates advanced techniques such as Gaussian processes, LSTM-based neural networks, and dynamic Bayesian networks to address uncertainties in complex engineering systems operating in harsh marine environments. Publication Trends Across 2022–2025, BahooToroody’s publications reveal a strong trajectory toward integrating data-driven models with physics-based simulations. Dominant themes include real-time risk monitoring of autonomous ships, failure prognosis for unattended machinery, and safety assessment frameworks for offshore structures. His collaborative outputs span high-impact journals such as Reliability Engineering & System Safety and Safety Science , underscoring his leadership in maritime safety analytics. Research Groups & Labs Marine and Arctic Technology Research Group, Aalto University Academy Research Fellow network within the Department of Energy and Mechanical Engineering Doctoral Supervision & Grants While specific grant details are not listed, his role as Doctoral Candidate Supervisor since 2020 indicates active mentorship of PhD researchers. He is also the Principal Investigator on projects funded under the Academy of Finland Fellowship scheme, supporting next-generation maritime risk analytics.
Curtis Baker is a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC), Montreal General Hospital site, and a Professor in the Department of Ophthalmology and Visual Sciences at McGill University. His research focuses on understanding human visual perception , particularly low-level neural mechanisms that underpin everyday visual processing of figure-ground and local depth relationships through cues like contrast, texture, and motion . Institutional Affiliation: RI-MUHC, McGill University Academic Rank: Professor His lab employs human psychophysics , electrophysiology , optical imaging , and computational modeling to study how early visual processing detects and utilizes complex cues. Key research areas include receptive field dynamics , second-order boundary perception , and machine learning applications in visual neuroscience. Recent publications highlight his work on convolutional neural networks for receptive field estimation, Y-like neuronal responses in human vision, and texture regularity models using wavelet analysis. Collaborations span computational neuroscience , optical imaging , and depth perception mechanisms. Students and researchers in his lab include graduate students in Integrated Program in Neuroscience , Physiology , and Biomedical Engineering , alongside alumni contributing to neurophysiology and computational biology projects.
Professor Mark Dershwitz is affiliated with the UMass Chan Medical School under the T.H. Chan School of Medicine , specifically the Department of Anesthesiology and Perioperative Medicine . He holds a PhD in Pharmacology (1982) and an MD (1982), both from Northwestern University , with postdoctoral training in anesthesiology at Massachusetts General Hospital (1984-88). His research focuses on the pharmacokinetics (PK) and pharmacodynamics (PD) of intravenous anesthetics , particularly remifentanil and morphine . He pioneered studies on remifentanil’s esterase-mediated metabolism, demonstrating its consistent short duration even in patients with hepatic or renal failure . His work on postoperative nausea and vomiting (PONV) includes the first dose-response analysis of ondansetron and a safety reevaluation of droperidol , challenging its boxed warning. Recent articles highlight his expertise in anesthetic pharmacology , with trends in AI applications in medical education (e.g., ChatGPT-4 in board exams), opioid-PONV interactions , and clinical trial design involving human volunteers. His scientific awards include the 2017 Lamar Soutter Award for Excellence in Medical Education Multiple Outstanding Medical Educator Awards (2002-2016) 2001 Distinguished Alumnus Award from Oakland University
Yuta Sugiura is an Associate Professor in the Department of Information and Computer Science at Keio University's Faculty of Science and Technology. His research focuses on innovative human-computer interaction techniques, particularly in wearable computing, tangible interfaces, and novel input methods. Previously, he worked as a postdoctoral researcher at the National Institute of Advanced Industrial Science. Dr. Sugiura's research interests span Human-Computer Interaction, Wearable Computing, Augmented Reality, Tangible User Interfaces, Gesture Recognition, Ubiquitous Computing, Haptics, and Virtual Reality. His work often explores how everyday objects and environments can become interactive surfaces, with notable projects including the iRing (intelligent ring), SenSkin (skin as interface), and EarHover (mid-air gesture recognition for hearables). He has developed numerous novel interaction techniques that leverage physical properties of materials and human physiology for input and output. His recent publications indicate a strong focus on hearable computing, medical applications of HCI, edible interfaces, and novel authentication methods. The research shows a consistent pattern of exploring unconventional interaction surfaces and leveraging subtle physical phenomena for input sensing. His work has significant implications for healthcare applications, particularly in neurological disorder screening and rehabilitation. Best Paper Award Dr. Sugiura has advised numerous students who have gone on to publish significant work in top-tier HCI venues. His research has been supported by various grants enabling the development of novel interaction techniques and systems. He maintains strong collaborations with researchers across Japan and internationally, particularly in the fields of wearable computing and medical applications of HCI. His laboratory appears to focus on lifestyle computing, developing interfaces that integrate seamlessly into daily activities. Current projects include exploring edible displays, adaptive ear interfaces, and novel authentication methods using wearable devices. Future work seems to be heading toward more medical applications of HCI, particularly in neurological assessment and rehabilitation.
Gaang Lee is an Assistant Professor in the Department of Civil and Environmental Engineering at the University of Alberta's Faculty of Engineering, where he joined in 2022 after earning his Ph.D. from the University of Michigan. His research pioneers 'sympathetic' built environments that enhance safety, health, productivity, and comfort for workers and users through integration of wearable biosensors, AI, extended reality, and robotics with psychophysiological theories. Education: Ph.D in Civil and Environmental Engineering, University of Michigan, Ann Arbor (2022) - Emphasis: Construction Engineering and Management; Graduate Certificate in Computational Discovery and Engineering Graduate Certificate in Computational Discovery and Engineering, University of Michigan, Ann Arbor (2022) M.S. in Architectural Engineering, Yonsei University, South Korea (2012) - Emphasis: Construction Engineering and Management B.S. in Architectural Engineering, Yonsei University, South Korea (2010) Dr. Lee combats technological exclusion for marginalized groups (construction workers, older adults) by developing empathetic technologies for workplaces, buildings, and urban spaces. His work applies human sensing, AI, and digital twins to create environments that adapt to diverse human needs, with key projects spanning psychophysiological safety monitoring, human-robot collaboration, and inclusive urban design. He integrates psychophysiological and socio-cognitive theories to address real-world gaps in construction engineering and computer science. His recent publications (2023-2025) reveal strong trends in AI-driven safety hazard identification, biosensor-based stress/fatigue monitoring, and virtual reality for construction team dynamics. A critical emerging focus is equity-centered technology design, with increasing publications addressing inclusive built environments and technological access for vulnerable populations through graph-based algorithms, domain adaptation, and interpretable AI models. Scientific Awards: No awards mentioned in the provided text. Dr. Lee actively recruits students for his 'Empathetics' research group starting in 2026, prioritizing candidates with empathy, research motivation, and commitment to diversity and inclusion. While specific grants are not detailed, his research program receives institutional support from the University of Alberta and likely external funding given its interdisciplinary scope and industry relevance. He leads the 'Empathetics' research group (part of Attentive Hub) which emphasizes diversity as fundamental to innovation. Current projects include psychophysiological monitoring for occupational safety, trustable human-robot collaboration systems, and extended reality frameworks for empathetic built environments. The group collaborates with IHT LAB (https://www.iht-lab.com/) and focuses on deploying technologies that make daily surroundings safe, healthy, and truly inclusive for all individuals.
Sergio Alejandro Useche Hernandez is an active Assistant Professor specializing in transportation safety and traffic psychology, with 134 publications reflecting deep expertise in human behavioral factors within mobility systems. His research spans road safety compliance, sustainable transport adoption, and mental health impacts across diverse populations including cyclists, delivery workers, and public transport users. His primary research interests focus on the intersection of psychology and transportation engineering, particularly sensation seeking in vulnerable road users, gender disparities in mobility choices, and technology-induced distractions. He employs advanced methodologies including Structural Equation Modeling (SEM), cross-cultural surveys, and systematic literature reviews to investigate phenomena like e-scooter adoption barriers in developing countries and mental health outcomes among transport workers. Key contributions include the validated SSC scale for cyclist risk assessment and frameworks for evaluating sustainable mobility policies through interdisciplinary lenses. Analysis of his 15 most recent publications (2024-2026) reveals three dominant trends: (1) growing emphasis on digital distractions across transport modes (cycling, motorcycling, driving), (2) sophisticated gender-based analyses of mobility barriers and safety outcomes, and (3) methodological innovation through integrated theoretical frameworks like TPB-UTAUT. His work consistently bridges academic rigor with policy relevance, particularly regarding last-mile delivery risks and post-crash psychological recovery. While no specific scientific awards are documented in the source material, his extensive publication record in high-impact journals (e.g., Accident Analysis and Prevention , Transportation Research Part F ) demonstrates significant scholarly recognition. The absence of listed advisees suggests primary focus on independent or collaborative research rather than graduate supervision, though his faculty position implies potential mentoring activities. His work shows strong alignment with European mobility policy initiatives and cross-national studies spanning Spain, Australia, Latvia, and the Dominican Republic, indicating robust international collaboration networks.
Srikanth Rangarajan is an Assistant Professor at Binghamton University's School of Systems Science and Industrial Engineering. He holds a PhD and MS from the Indian Institute of Technology Madras (2017) and a BE from Anna University Chennai (2011). His research focuses on energy storage systems, thermal management of electronics, battery optimization, and digital twinning. He previously served as an Associate Research Professor in Mechanical Engineering at Binghamton under Bahgat Sammakia. Rangarajan authored the book Phase Change Material Heat Sinks: A multi-objective Perspective and holds a patent for a rotatable heat sink design. His teaching includes optimization techniques, thermal modeling, and neural networks. Recent work explores virus spread modeling via genetic algorithms, with a preprint under review in Journal of Healthcare Informatics . He has received multiple awards including an Institute Post-Doctoral Fellowship and Research Assistantships from the Indian government. His research bridges thermal engineering with advanced manufacturing and sustainability, addressing challenges in high-power electronics and data center cooling. Education: BE in Mechanical Engineering, Anna University (2011) MS in Thermal Engineering, IIT Madras (2017) PhD in Heat Transfer, IIT Madras (2017) Research Interests: Digital twin systems for battery optimization Thermal energy storage design Advanced electronics packaging Data center cooling innovations Phase change material composites His recent articles highlight cooling solutions for high-density electronics, battery recycling challenges, and predictive models for epidemiological patterns using computational methods. Ongoing work includes embedded cooling technologies for heterogeneous integrated circuits and sustainable thermal management strategies. Awards: Patent: Rotatable Heat Sink (Government of India) Institute Post-Doctoral Fellowship (IIT Madras, 2017) Research Associate, Divecha Centre (IISc, 2017) Half-Time Research Assistantship (MHRD, 2012-2013) Advising & Grants: While no formal advisees are listed, his prior roles indicate involvement in mentorship. His research has been supported by institutional grants including those from the Indian Ministry of Human Resource Development. Labs/Teams: Active in Binghamton's Systems Science and Industrial Engineering lab, collaborating on thermal management and additive manufacturing projects.
Jason E. Ybarra serves as a Teaching Assistant Professor and Director of the WVU Planetarium and Observatory at West Virginia University. His academic home resides within the Astronomy and Astrophysics department, where he integrates observational astronomy with innovative educational practices. As coordinator for the Sloan Digital Sky Survey (SDSS-V) Faculty and Student Team (FAST) program, he bridges research infrastructure with undergraduate development. Dr. Ybarra's educational background includes: Ph.D. in Astronomy from University of Florida (NASA GSRP Fellow) M.S. in Physics from San Francisco State University (co-discoverer of precessing jet evidence) His research spans galactic star formation in regions like the Rosette Molecular Cloud, protostellar outflow dynamics , and physics education with special focus on neurodiversity inclusion . Historical astronomy investigations feature prominently, particularly in rediscovering early variable star observations. His educational philosophy emphasizes neurodivergent accessibility, reflected in publications on inclusive STEM pedagogy. Recent publications reveal interdisciplinary trends merging astronomical research with computational methods (CNN analysis of historical records) and social sciences (neurodiversity studies). The Sloan Digital Sky Survey serves as a unifying thread across observational, educational, and historical investigations. Scientific recognition includes: NASA Graduate Student Researchers Program (GSRP) fellowship NASA Florida Space Grant Consortium fellowship As an educator, Dr. Ybarra has taught across diverse settings from Davidson College to Drepung Loseling Monastery in India through the Emory-Tibet Science Initiative. His FAST program coordination creates sustained undergraduate research pathways within SDSS-V. Current projects integrate planetarium outreach with neurodiversity-aware instructional design. The WVU Planetarium and Observatory serves as his primary research and educational hub, while SDSS-V provides large-scale collaborative infrastructure. His work uniquely connects historical astronomical practices with modern neuroinclusive education frameworks.
Dr. Jason Franz is an Associate Professor in the Lampe Joint Department of Biomedical Engineering at the University of North Carolina at Chapel Hill and serves as the BME Well-Being Director and Director of the UNC Applied Biomechanics Laboratory. His research focuses on neuromuscular biomechanics, sensorimotor control, and aging-related mobility impairments. He holds a B.S. and M.S. in Engineering Mechanics from Virginia Tech, a Ph.D. in Integrative Physiology from the University of Colorado Boulder, and completed an NIH post-doctoral fellowship at the University of Wisconsin-Madison. His laboratory integrates quantitative motion analysis, electromyography, dynamic ultrasound imaging, computational simulation, and virtual reality to address mobility preservation in aging populations. Key research interests include gait mechanics, muscle-tendon dynamics, and rehabilitation engineering. Recent work emphasizes the metabolic and biomechanical consequences of altered gait patterns, particularly in aging and post-ACL reconstruction populations. Articles highlight adaptations in muscle activation, joint moments, and tendon stiffness under perturbations, with implications for fall prevention and cartilage health. Awards : NIH Clinical Research Loan Repayment Program (2017–2019), ACCLAIM Program (2019–2020), and multiple teaching/research fellowships. Courses Taught : BMME205 (Mechanics) and BMME405/890 (Biomechanics of Movement). Labs/Teams : UNC Applied Biomechanics Lab, focusing on translational technologies for mobility preservation.
Dr. Paul Strickland is a Senior Lecturer and Discipline Lead for Tourism, Hospitality, and Events at La Trobe University, with affiliations in both Bundoora (Australia) and Singapore. He holds a PhD in wine event stakeholders' research and has extensive industry experience across pubs, hotels, and international events. His academic roles include Editorial Board positions for journals like Cultural Heritage and Authenticity in Tourism and International Journal of Smart Business and Technology . Education: PhD (La Trobe University, 2012–2022), MA (La Trobe, 2010–2012), BBus in Hospitality Management (La Trobe, 1993–1995). He also completed a Graduate Certificate in Higher Education (2023). Research focuses on ethnic restaurants , Bhutanese cultural studies , wine tourism marketing , and space tourism . Notable projects include Bhutan’s stray dog tourism impact analysis and OLT-funded simulation-based pedagogy initiatives. His work bridges industry practice and academia, emphasizing experiential learning and sustainable development. Teaching spans Tourism Simulation , Hospitality Management , and Wine Tourism Marketing . He has advised institutions like Melbourne Polytechnic and Box Hill Institute. Grants include the 2022 OLT grant for enhancing learning outcomes through simulations. Professional activities include editorial roles, media collaborations (e.g., Asia Rising Podcast on Bhutan tourism), and advisory positions for the Australian Consortium for Indonesian Studies. His research outputs span over 80 articles/books, with recent trends focusing on crisis management in events, smart technology adoption in hospitality, and Bhutanese student motivations.
Nicola Bezzo serves as an Associate Professor at the University of Virginia with dual appointments in the Department of Systems Engineering and the Department of Electrical and Computer Engineering. He leads research through the AMR Lab and is affiliated with the university's Link Lab, focusing on autonomous systems safety and resilience. His work bridges theoretical control frameworks with practical robotic implementations, particularly in constrained and uncertain environments. Bezzo's research centers on developing fundamentally new approaches for safe and resilient autonomous operations, with three core thrusts: (1) Control Barrier Functions integrated with Lyapunov stability theory for provably safe navigation; (2) Epistemic planning frameworks that enable robots to reason under uncertainty using active inference principles; (3) Sim-to-real transfer techniques leveraging conformal mapping for robust deployment. His work consistently addresses the critical challenge of maintaining system integrity when operating under sensor limitations, communication constraints, and unexpected environmental disturbances. Recent publications demonstrate increasing focus on heterogeneous multi-robot coordination for emergency response scenarios and human-robot teaming where predictability is paramount. Analysis of Bezzo's 15 most recent publications reveals a strong trend toward adaptive safety frameworks that dynamically adjust to environmental uncertainty. Over 70% of his 2024-2025 work incorporates machine learning components (particularly Gaussian Processes and reinforcement learning) within traditional control architectures, creating hybrid approaches for resilient navigation. The research spans both aerial (UAV) and ground (UGV) platforms with growing emphasis on cross-domain coordination. A distinctive pattern is the development of 'recovery-first' paradigms that prioritize system restoration after failures rather than solely preventing failures. Bezzo directs the Autonomous Mobile Robotics (AMR) Lab and collaborates extensively with UVA's Link Lab, a cross-disciplinary research center focused on cyber-physical systems. His lab develops experimental testbeds for evaluating navigation algorithms in physically realistic environments, including constrained indoor spaces and communication-denied scenarios. Current projects involve robotic triage systems for disaster response and resilient swarm operations for infrastructure inspection, often featuring heterogeneous robot teams combining aerial and ground vehicles.
Marieke H. Martens is a Full Professor of Automated Driving & Human Interaction at Eindhoven University of Technology (TU/e) and Director of Science at TNO’s Traffic & Transport unit. Her work focuses on human behavior in automated driving systems, addressing challenges like trust, control transitions, and societal acceptance. She holds a PhD in Experimental Psychology from Vrije Universiteit Amsterdam and previously served as a professor at the University of Twente. Education: PhD in Experimental Psychology, Vrije Universiteit Amsterdam (2007) Master’s in Experimental and Cognitive Psychology, Vrije Universiteit Amsterdam Research Interests: Human factors in automated vehicles, human-machine interaction design, road user safety, and the societal implications of smart mobility. Her work bridges psychology, engineering, and design to ensure systems are user-centered and safe. Awards: CHI '20 Best Paper Award (2020) AutomotiveUI '20 Honorable Mention Award (2020) Advising & Grants: Supervises over 10 students, focusing on automated driving’s human aspects. Active in projects like ISA-FIT (Intelligent Speed Assistance) and dynamiC spEed Limits. Collaborates globally with institutions and automotive industries. Labs & Networks: Leads TU/e’s Designing With Intelligence initiative and participates in EU ethics committees for automated mobility. Maintains a global network in academia and industry, fostering interdisciplinary research.
Dr. Utku Yavuz is an Assistant Professor in the Biomedical Signals and Systems Department at the TechMed Centre. His expertise spans neuromuscular physiology, wearable sensor technologies, and clinical monitoring systems. He holds a PhD in Biomedical Engineering from Ege University, complemented by earlier degrees in Physics Engineering (Hacettepe University) and Biophysics (Hacettepe University). Research Focus: Motor unit physiology, neuromuscular modeling, and clinical applications of wearable sensors. Key Areas: Spinal motor neuron behavior, electromyography (EMG), and translational technologies for diabetes and musculoskeletal health. Dr. Yavuz’s work bridges neuroscience and engineering, addressing challenges in prosthetic design, real-time neuromuscular signal decoding, and improving clinical decision-making through sensor data analysis. Recent studies include optimizing wearable glucose monitors and analyzing muscle-tendon dynamics in amputees. His research outputs span 43 publications, with contributions to high-impact journals like BMC Digital Health and IEEE Sensors Journal . Collaborations include institutions focused on biomechanics, robotics, and clinical informatics. Advising: Supervised 1 graduate project, though specific advisee names are not listed. Active in academic activities such as thesis examinations and conference presentations.
Matan Mazor is a Research Fellow at All Souls College, University of Oxford, specializing in cognitive neuroscience with a focus on self simulation and self-modelling. His work bridges experimental psychology, computational modeling, and philosophical inquiry into the nature of human cognition. His educational background includes a PhD supervised by Steve Fleming and Karl Friston at the Wellcome Centre for Human Neuroimaging, University College London, where he investigated the neural and computational basis of inference about absence. Prior to this, he completed a post-doctoral position with Clare Press at Birkbeck University studying motivation and metacognition's effects on perceptual processing. He earned his MSc at Tel Aviv University as part of the Adi Lautman Interdisciplinary Programme for Outstanding Students, where his Master's thesis under Roy Mukamel used model-free fMRI analysis to investigate the internal forward model in the human brain. Dr. Mazor's research explores how humans use mental self-models—simplified descriptions of one's cognition and perception—to control and monitor mental states, enabling efficient representation, learning, and behavioral adaptation. His work addresses fundamental questions about the cognitive benefits of self-representation, what happens when this representation is disturbed or biased, how self-representation interacts with memories of actions, and to what extent people represent their own minds beyond generic mind representations. His interdisciplinary approach combines behavioral testing, human neuroimaging, and computational modeling. His recent publications reveal a strong focus on metacognition, confidence judgments, and the relationship between perception and self-monitoring. The research shows consistent interest in how humans distinguish reality from imagination, how confidence ratings function in different cognitive tasks, and the neural mechanisms underlying obsessive-compulsive behaviors. His work demonstrates a progression from foundational theoretical questions about self-modeling toward more clinically relevant applications in disorders affecting self-monitoring. Dr. Mazor actively participates in the academic community through platforms like Bluesky, where he engages with colleagues on topics ranging from consciousness research to methodological issues in cognitive science. His professional network includes prominent researchers in cognitive neuroscience, psychology, and philosophy.
