Find Academic Supervisors

• Internal Combustion Engine
• Fuel cell
• Battery
• +5 more

Professor Jin Kusaka is a distinguished faculty member at Waseda University's Faculty of Science and Engineering and Graduate School of Environment and Energy Engineering. With a Doctor of Engineering degree from Waseda University, he has established himself as a leading researcher in thermal engineering, particularly in the fields of internal combustion engines, fuel cells, batteries, and catalysts. His research interests span across several critical areas of modern energy systems: Internal Combustion Engine technologies for improved efficiency and reduced emissions Fuel cell development and optimization Battery thermal management systems for electric vehicles Catalyst design and performance enhancement for emission control Waste heat recovery systems using thermoelectric generators Alternative and synthetic fuels for decarbonization of transportation Professor Kusaka's extensive publication record (179 papers with 2,548 Google Scholar citations and an h-index of 23) demonstrates his significant contributions to the field. His recent research focuses on cutting-edge topics including battery thermal management under various driving conditions, thermoelectric waste heat recovery systems for natural gas engines, machine learning applications for engine control systems, and advanced combustion strategies for alternative fuels. His work bridges fundamental research with practical automotive applications, addressing critical challenges in energy efficiency and emission reduction. His notable scientific achievements have been recognized through several prestigious awards: JSAE Oral Presentation Award (October 2005) SAE SETC 2003 Paper Award (October 2003) JSAE Asahara Memorial Award (2001.05) Professor Kusaka is an active member of several professional societies including The Japan Society of Mechanical Engineering, Combustion Society of Japan, and The Society of Automotive Engineers, reflecting his commitment to advancing engineering knowledge and practice. His research group appears to be highly productive, with numerous publications featuring collaborations with researchers like Ratnak Sok, who frequently appears as first author on papers with Professor Kusaka as corresponding author.

• Experimental psychology
• memory
• source monitoring
• +3 more

Eriko Sugimori is an Associate Professor at the School of Human Sciences, Faculty of Human Sciences. She holds a Ph.D. in Education and has established herself as a prominent researcher in experimental psychology with a focus on memory processes and cognitive phenomena. Her research interests span across several key areas of experimental psychology: Memory and source monitoring processes Action and implicit memory Individual differences in cognitive processing Nostalgia and autobiographical memory Schizotypal personality traits and cognitive functioning Dr. Sugimori's work demonstrates a consistent pattern of investigating how cognitive processes interact with emotional states, social contexts, and perceptual experiences. Her research spans from basic cognitive mechanisms to applied settings in clinical, educational, and social contexts. A significant portion of her work examines how memory processes are influenced by emotional states, social interactions, and individual differences in personality traits. Among her notable achievements is the Japanese Psychological Association Excellent Paper Award received in 2006. Her research has been published in numerous high-impact journals across psychology and cognitive science. Dr. Sugimori has mentored numerous students through research projects and has been involved in various research collaborations across different institutions. Her work has received significant attention in the field, as evidenced by her 504 citations and h-index of 12 across 43 publications. She is actively involved in several professional organizations including the Japanese Society of Sport Psychology, Japanese Society of Applied Psychology, Psychonomic Society, Japanese Psychological Association, and Japanese Society of Cognitive Psychology, demonstrating her commitment to advancing psychological science across multiple subdisciplines.

Pedro M. B. Silva GirãoView profile

Professor

• Instrumentation
• Transducers
• Wireless Sensor Networks
• +6 more

Pedro M. B. Silva Girão is a Full Professor in the Department of Electrical Engineering at Instituto Superior Técnico (IST), University of Lisbon (UL), and a Senior Researcher at Instituto de Telecomunicações where he heads the Instrumentation and Measurements Group and coordinates the Basic Sciences and Enabling Technologies area. His dual institutional roles position him at the forefront of academic research and technological innovation in Portugal. His research program focuses on instrumentation, transducers, and measurement techniques with specialized applications in biomedical and environmental domains. Key interests include wireless sensor networks for health monitoring, metrology standards, and digital data processing methodologies. This work bridges engineering principles with real-world healthcare and ecological challenges, emphasizing practical implementations in diagnostic systems and environmental sensing. Analysis of his 2019-2024 publications reveals a strong thematic trajectory in IoT-enabled healthcare solutions and precision environmental monitoring. Recurring motifs include gait rehabilitation through mixed reality systems, advanced dosimetry for liver cancer radioembolization, microvascular reactivity assessment, and water quality sensor networks. His output demonstrates consistent interdisciplinary collaboration between engineering, medical, and environmental science communities. Dr. Girão's scientific recognition includes: IEEE Senior Member status IEEE IMS Distinguished Lecturer appointment Honorary Chairmanship of IMEKO TC19—Environmental Measurements As leader of the Instrumentation and Measurements Group at Instituto de Telecomunicações, he directs a multidisciplinary team developing next-generation measurement systems. Current initiatives integrate microwave Doppler radar, wearable biopotential sensors, and wireless networks for unobtrusive health monitoring and environmental assessment, with active partnerships across medical institutions and ecological agencies.

• Human-Computer Interaction
• Augmented Reality
• Computer Vision
• +4 more

Karan Ahuja is the Lisa Wissner-Slivka & Benjamin Slivka Assistant Professor in Computer Science at Northwestern University, where he directs the Sensing, Perception, Interactive Computing & Experiences (SPICE) Lab. He will begin this position in September 2024, transitioning from his role as a Visiting Research Scientist at Google where he led Augmented Reality initiatives. Education: Ph.D. in Human-Computer Interaction from Carnegie Mellon University (2023) B.Tech. in Computer Science (2017) His research creates cutting-edge technologies that sense, track, and understand humans to augment daily interactions. The SPICE Lab tackles high-impact problems in: Mobile health sensing : Developing unobtrusive monitoring systems Extended reality : Creating immersive AR/VR experiences Embodied perception : Advancing full-body motion capture Natural interfaces : Designing intuitive interaction paradigms The lab leverages expertise in novel sensors, embedded systems, computer vision, and on-device machine learning to deploy real-world solutions. Ahuja's publications demonstrate strong focus on human sensing technologies, particularly in motion capture (full-body and hand pose estimation), eye/gaze tracking, and multimodal interaction systems. Recent work shows increasing emphasis on practical applications of extended reality and wearable computing. Awards and honors: Forbes 30 Under 30 - Asia, Healthcare & Science (2024) MIT 35 Innovators Under 35 Asia Pacific ACM SIGCHI Special Recognition ACM SIGCHI Outstanding Dissertation Award He actively recruits post-docs, PhD students, and researchers for the SPICE Lab. His industry experience includes research positions at Apple, Microsoft Research, Meta Reality Labs, and IBM Research, with technologies shipped to over 100 million users.

• Biomechanics
• Biomedical Engineering
• Computational Modeling
• +6 more

Lindsey Westover, PhD, PEng, serves as an Associate Professor in the Department of Mechanical Engineering and Associate Dean in the Faculty of Engineering at the University of Alberta. Her research and teaching activities are centered in the Biomedical Engineering program, with her laboratory located in the Donadeo Innovation Centre for Engineering (13-224, 9211 116 St, Edmonton, AB T6G 2H5). She maintains an active research profile while contributing to academic leadership through her deanship. Her educational background includes: 2018: Postdoctoral Fellowship in Rehabilitation Medicine, University of Alberta 2016: Ph.D. in Mechanical Engineering, University of Alberta 2011: M.Sc. in Mechanical Engineering, University of Calgary 2007: B.Sc. in Mechanical Engineering, University of Calgary Dr. Westover's research program spans biomechanics and biomedical engineering with emphasis on noninvasive assessment of biological structures, vibration analysis for percutaneous implants, joint biomechanics (ligaments and cartilage), spinal deformity analysis through asymmetry metrics, mechanical testing of biological tissues, and computational modeling of biological systems. Her work integrates laboratory experiments, computational methods, and in vivo studies to develop innovative diagnostic and therapeutic approaches. Analysis of her 15 most recent publications (2018-2020) reveals consistent focus on bone mechanics, implant stability, and symmetry analysis across orthopedics, audiology, and dentistry. Key themes include osseointegration evaluation using ASIST technology, pelvic/spinal deformity quantification, and computational modeling of biological structures. Her work appears in high-impact journals spanning engineering and clinical disciplines, demonstrating strong interdisciplinary collaboration. Scientific recognition includes: Nomination for Ear and Hearing 2018 Editor's Award for bone conduction device research Dr. Westover mentors graduate students through co-authorship on numerous publications and teaches core mechanical engineering courses including MEC E 451 (Vibrations and Sound), MEC E 390 (Numerical Methods), and MEC E 200 (Introduction to Mechanical Engineering). Her research is supported by collaborative grants with clinical partners and engineering colleagues. She leads biomechanics research within the Department of Mechanical Engineering, collaborating extensively with the Faculty of Rehabilitation Medicine and surgical departments. Her laboratory develops advanced testing systems like ASIST for implant stability evaluation across hearing devices and dental applications, while her computational work informs clinical approaches to scoliosis management and fracture reconstruction.

Brian HorsakView profile

Associate Professor

• Clinical biomechanics
• Gait analysis
• Musculoskeletal loading
• +5 more

Brian Horsak is a Privatdozent (equivalent to Associate Professor) at the University of Vienna, affiliated with the Department of Sport and Human Movement Science within the Faculty of Sports Sciences. He serves as a member of the PI Panel/Supervisors for the Sport Science program at the Vienna Doctoral School of Pharmaceutical, Nutritional and Sport Sciences (VDS PhaNuSpo). His research group is located at the St. Pölten University of Applied Sciences with strong collaboration to the Centre for Sport Science and University Sports at the University of Vienna. Dr. Horsak's primary research interests focus on clinical (gait) biomechanics and interdisciplinary approaches between therapy and technology. His work is dedicated to understanding musculoskeletal loading of the lower extremities during locomotion and exercise, and developing assistive technologies such as machine learning algorithms and virtual reality applications to support patients and therapists during rehabilitation. Specific areas include: Clinical gait analysis and biomechanics Musculoskeletal loading in lower extremities Patellofemoral instability and joint biomechanics Machine learning applications for gait classification Virtual reality for rehabilitation Biomechanics of obesity and pediatric movement disorders 3D motion capture and markerless technology His recent publications demonstrate a strong trend toward integrating advanced computational methods with clinical biomechanics. Over the past five years, his work has increasingly focused on smartphone-based motion capture systems, deep learning applications for gait analysis, and virtual reality environments. His research bridges engineering technology and clinical rehabilitation, with particular attention to knee biomechanics, patellofemoral disorders, and movement analysis in pediatric obesity. Dr. Horsak teaches courses including 'Methods and Concepts of Biomechanics and Sports Informatics' and serves as supervisor for PhD students Bernhard Dumphart and Mark Simonlehner. His research group maintains strong collaborations with the St. Pölten University of Applied Sciences and appears to be involved in multiple interdisciplinary projects combining sports science, engineering, and clinical rehabilitation.

Pedram JohariView profile

Researcher

• Intra-body Communications
• Wireless Networking
• Internet of Medical Things
• +4 more

Pedram Johari serves as a Principal Research Scientist at Northeastern University's Institute for Wireless Internet of Things, working under Prof. Tommaso Melodia in the Department of Electrical and Computer Engineering within the College of Engineering. His research focuses on next-generation wireless communications with particular emphasis on medical applications and nanoscale networks. Dr. Johari earned his Ph.D. in Electrical Engineering from the University at Buffalo, State University of New York in 2018 under the supervision of Prof. Josep M. Jornet. Prior to joining Northeastern, he served as CTO of an IoT-tech startup in New York (2018-2019) and held academic positions at University at Buffalo as Adjunct Instructor and Research Assistant Professor (by courtesy appointment). His research spans four interconnected domains: Intra-body Communications and Networking focusing on nanoscale electromagnetic and optical communications within biological tissues; Internet of Medical Things developing wireless systems for healthcare applications; Low Power Wireless IoT creating energy-efficient communication protocols; and Vehicular Communications advancing cooperative driving systems. His work bridges theoretical modeling with practical implementation, often incorporating AI techniques for network optimization. Analysis of his recent publications reveals a strong trend toward digital twin technology for wireless networks, AI-enabled communication systems, and medical applications of nanoscale communications. His research increasingly integrates machine learning with traditional communication theory, particularly in Open RAN systems and seizure prediction technologies, demonstrating cross-disciplinary impact across engineering, computer science, and biomedical fields. Best Paper Award at IEEE Global Communications Conference (GLOBECOM) Best Short Paper Award at IEEE Vehicular Networking Conference (VNC) Best Presentation Award at IEEE Conf. on Computer Communications Workshops (INFOCOM WKSHPS) Dr. Johari actively contributes to academic service as a reviewer for numerous prestigious journals including IEEE Transactions on Wireless Communications, IEEE Transactions on Mobile Computing, and IEEE Internet of Things Journal. He has served on technical program committees for major conferences including IEEE/ACM CHASE and IEEE SECON. His teaching experience includes courses in programming, circuit analysis, and digital principles at University at Buffalo. As a key member of the Wireless Networks and Embedded Systems Lab at Northeastern University, Dr. Johari contributes to the Colosseum wireless network emulator project - recognized as the world's largest wireless network emulator. His work with the Institute for Wireless Internet of Things involves collaboration with industry partners to translate research into practical wireless communication solutions.

Dongmei ZhaoView profile

Professor

• Wireless Networking
• Network Resource Management
• Mobile Edge Computing
• +4 more

Dr. Dongmei Zhao is a Professor in the Department of Electrical & Computer Engineering at McMaster University, part of the Faculty of Engineering. She specializes in wireless networking, network resource management, mobile edge computing, mobile computation offloading, and digital twins. Her research clusters focus on Digital & Smart Systems. Dr. Zhao holds a Ph.D. from the University of Waterloo. She teaches courses such as COMPENG 4DK4 (Computer Communication Networks), COMPENG 4DN4 (Advanced Internet Communications), and graduate-level courses like ECE 729 (Resource Management in Wireless Networks). Her research interests span cutting-edge topics including UAV-enabled edge computing, digital twin migration, vehicular networks, and reinforcement learning applications in resource allocation. She actively contributes to advancing 6G networks, security redundancy in autonomous systems, and decentralized manufacturing platforms. Dr. Zhao's recent publications emphasize optimization techniques for dynamic networks, platooning systems, and multi-agent learning frameworks. She has been recognized for her work in vehicular edge computing and digital twin integration, though explicit awards are not listed here. She advises on graduate studies in networking and edge computing, though no specific student names are provided in the text. Her work often intersects with practical challenges in smart infrastructure and autonomous vehicle systems.

• Information Processing Systems
• Internet of Things (IoT)
• Edge Computing
• +4 more

Marcello Pietri is a Researcher (td art. 24 c. 3 lett. A) and Contract Professor at the Department of Engineering Sciences and Methods (DISMI) at the University of Modena and Reggio Emilia. His work focuses on Information Processing Systems, with expertise in IoT, Edge Computing, and Digital Twins. He teaches courses like 'Sistemi Informativi' (Information Systems) for the Engineering Management program, emphasizing database design, SQL, and web application development with Python. His research explores advanced topics including Digital Twin integration in Industry 5.0, Fluid Computing in IoT ecosystems, and Smart City data fusion using 5G MEC architectures. He collaborates with institutions like the DIPI Lab (Distributed and Pervasive Intelligence Group), contributing to projects on telecom security, energy forecasting, and human-centric manufacturing systems. Recent publications highlight innovations in operator digital twins for workplace well-being, distributed data mesh models for IoT-edge-cloud systems, and adaptive monitoring algorithms for large-scale cloud environments. His work bridges theoretical advancements with practical implementations, addressing challenges in scalability, real-time data processing, and interdisciplinary collaboration.

• Virtual Reality
• Augmented Reality
• Human-Computer Interaction
• +3 more

Matteo Bosco is a PreDoc Researcher at the Department of Software Technology and Interactive Systems, TU Wien, within the Virtual and Augmented Reality group. His work focuses on advancing human-computer interaction in immersive environments, particularly through conversational agents, neurotechnology integration, and circular economy frameworks. He contributes to the Circular Twin research project, addressing sustainable building design through digital twins and generative algorithms. Education & Roles: PreDoc Researcher (PhD candidate) at TU Wien Research Interests: His primary areas include: VR/AR interfaces enhanced by large language models BCI-driven human-robot interaction systems Procedural building design using conversational AI Sustainable architecture via circular twin frameworks He explores how immersive technologies can bridge human-centric design with computational efficiency, emphasizing accessibility and environmental sustainability. Key Projects: Circular Twin (2022–2025): Developing digital ecosystems for circular buildings using BIM and VR. Neurotag Visualization Media: Comparing AR/VR/monitor-based BCI interfaces. Labs & Teams: Active in the Mixed Reality Lab and collaborates with the Virtual Meeting Room initiative at TU Wien.

• Database Systems
• Distributed Systems
• Cloud Computing
• +4 more

Dr. Kenneth Salem is a Professor at the University of Waterloo, Canada , with a distinguished career spanning over three decades in database systems, distributed computing, and data management. His work has significantly influenced transaction processing, replication, and scalability in modern databases. Institution: University of Waterloo Collaborations: Frequent co-author with Hector Garcia-Molina, Ashraf Aboulnaga, Umar Farooq Minhas, Khuzaima Daudjee Research Interests: Dr. Salem’s research focuses on database systems, particularly in transaction processing , distributed databases , cloud computing , and energy-efficient data storage . He has pioneered techniques for schema design in NoSQL , adaptive caching , and RDMA-based data transfer . His work often addresses challenges in high availability , workload-aware optimization , and cardinality estimation . Recent Article Trends: His latest publications (2023-2025) explore ad hoc transactions , eventual durability , and summary-based cardinality estimation , emphasizing practical solutions for real-world database scalability and consistency. Earlier works (2018-2022) covered memory power optimization , RDMA abstractions , and workload-aware CPU scaling , reflecting a sustained focus on performance and efficiency. Advising and Collaborations: Dr. Salem has mentored numerous co-authors in database research, including Ashraf Aboulnaga, Umar Farooq Minhas, and Khuzaima Daudjee. His collaborative projects span Apache Spark caching , RemusDB high availability , and DimmStore memory optimization . Labs and Teams: He has been a key contributor to the DaMoN and Versatile Database Systems workshops, focusing on hardware-aware database design. His work with teams at Waterloo and collaborations with institutions like ETH Zurich and MIT has advanced self-managing databases and edge replication technologies.

• Software Engineering
• Cybersecurity
• Formal Methods
• +5 more

Role & Affiliation: Jean-Christophe BACH is an Associate Professor at IMT Atlantique's Computer Science department since 2015. He leads the PASS research group (IRISA) and focuses on software security, model-driven engineering, and cybersecurity applications. Previously, he held roles as a teaching assistant (ATER) at University of Lille (2014–2015) and completed his PhD on model transformations at Inria/LORIA under Pierre-Étienne Moreau and Marc Pantel (defended 2014). Research Interests: His work centers on improving software trustworthiness through 'security by design' principles. Key areas include model federation, formal methods for software verification, transformation traceability, and cybersecurity in industrial systems. He actively contributes to frameworks like Openflexo and PAMELA, emphasizing practical tooling for secure systems engineering. Teaching & Education: Teaches advanced topics such as object-oriented design, functional programming (OCaml), concurrency modeling, and cybersecurity. Supervises student projects on Openflexo, game development, and network security (IPv6/Tor). Courses include INF301, INF447, and others. Labs & Collaborations: Engaged with IRISA and Lab-STICC research centers. Collaborates on projects like the European Space Agency's SSE4Space framework for secure space missions and the Quarteft project (aerospace software). Active in open-source initiatives and scientific mediation for K-12 programming education.

• Power Electronics
• Semiconductor Device Modeling
• Electromagnetic Modeling
• +2 more

Dr. Ivana Kovacevic is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich. Her research focuses on power electronics, semiconductor device modeling, and electromagnetic analysis of wide bandgap devices. ETH Zürich, Department of Information Technology and Electrical Engineering Contact: kovacevic@aps.ee.ethz.ch Her research explores SiC power MOSFETs, emphasizing their dynamic performance, reliability, and optimization through advanced modeling techniques like the Partial Element Equivalent Circuit (PEEC) method. She investigates parasitic extraction, thermal behavior, and stability issues in power modules, contributing to design improvements for high-efficiency systems. Her publications highlight trends in electromagnetic modeling, device-circuit interactions, and reliability analysis under extreme conditions. Key subfields include gate resistance dynamics, frequency-dependent capacitances, and multi-chip module design. Current projects involve virtual prototyping for power electronics and mission profile-based optimization of wearable power systems.

Haijian SunView profile

Assistant Professor

• Wireless Communication
• 5G and Beyond Networks
• Internet of Things (IoT)
• +4 more

Haijian Sun is an Assistant Professor at the University of Georgia's School of Electrical & Computer Engineering. His research focuses on advanced wireless communication systems, including 5G/6G networks, federated learning, mobile edge computing, and physical layer security. He explores cutting-edge topics like reconfigurable intelligent surfaces (RIS), hybrid active-passive symbiotic radio systems, and UAV-enabled communication. His work integrates machine learning and optimization techniques to address challenges in channel modeling, energy efficiency, and network security. Recent projects include autonomous agricultural monitoring via drones and energy-harvesting sensors, as well as secure IRS-VLC communication strategies. Publications highlight innovations in dynamic wireless charging for electric vehicles, graph-based phishing detection, and radio radiance field modeling. While no specific awards are listed, his contributions reflect significant engagement with industry-relevant 6G research. Research collaborations involve digital twin networks, IoT systems, and smart grid applications. His team develops practical solutions for real-world communication challenges, emphasizing both theoretical rigor and deployable technologies.

Lynne GreweView profile

Professor

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +3 more

Lynne Grewe serves as a Professor in the Department of Computer Science at California State University, East Bay, where she maintains active research and teaching responsibilities with current office hours and contact information. Her work bridges theoretical computer science with real-world applications across healthcare, education, and emergency response domains. Her research portfolio centers on three interconnected thrusts: Medical Technology : Development of computer vision systems for stroke detection through facial pattern analysis (StrokeChange), infrared-based disease monitoring, and assistive navigation tools for the visually impaired (Seeing Eye Drone) Educational Innovation : Creation of multimodal systems like ULearn that detect student frustration using deep learning, alongside community college partnerships to broaden participation in computing Sensor Fusion Applications : Integration of multi-modal data for disaster response, infrastructure monitoring, and mobile health platforms using advanced machine learning techniques Publication analysis reveals consistent evolution toward real-time, deployable systems—particularly mobile health applications and educational tools—while maintaining foundational work in sensor fusion. Her 2020-2024 output shows increasing emphasis on healthcare applications (40% of recent work) and educational technology (25%), often combining computer vision with mobile platforms. Grewe demonstrates significant commitment to educational equity through the Faculty in Residence program, collaborating with community colleges to prepare underrepresented students for computing careers. Her Google partnership and focus on practical applications indicate strong industry engagement, though specific grant details aren't documented in source materials. Current projects suggest ongoing expansion into in-situ health monitoring and AI-driven educational support systems.