جست‌وجوی استاد و پژوهشگر

• Heart Failure
• Implementation Science
• Data Science
• +۵ مورد دیگر

Harriette Van Spall is an Associate Professor in the Department of Medicine at McMaster University and a practicing cardiologist at Hamilton Health Sciences . She holds scientist appointments at the Population Health Research Institute and Research Institute of St. Joe's, Hamilton , and serves as an Associate Member of the Department of Health Research Methods, Evidence, and Impact . Her clinical focus includes Heart Failure , Echocardiography , and Acute Care Cardiology , with active involvement in training medical students and fellows. Education : Bachelor of Science and Doctor of Medicine (University of Toronto) Master of Public Health (Harvard School of Public Health) Fellow of the Royal College of Physicians and Surgeons of Canada (Internal Medicine, Cardiology, Level III Echocardiography) Research Interests : Heart failure epidemiology and outcomes Implementation science for guideline adherence Diversity and inclusion in clinical trials Digital health technology in cardiology Sex and gender disparities in cardiovascular care Recent Publications span heart failure risk prediction, digital health equity, gender-specific outcomes, and global implementation guidelines. Her work appears in JAMA , Lancet , Circulation , and European Heart Journal . Scientific Awards : CIHR-Institute of Circulatory and Respiratory Health Mid-Career Lectureship Award in Cardiovascular Sciences American Heart Association Nanette Wenger Research Award Grants and Mentorship : She has secured over $6.0 million in research funding from CIHR , Heart and Stroke Foundation of Canada , and other agencies. She mentors postgraduate fellows, graduate students, and medical residents.

Nidhi Seethapathiمشاهده پروفایل

استادیار

• Human Movement Science
• Computational Neuroscience
• Biomechanics
• +۳ مورد دیگر

Nidhi Seethapathi is the Frederick A. (1971) and Carole J. Middleton Career Development Assistant Professor of Brain and Cognitive Sciences and Electrical Engineering and Computer Science at MIT. She holds a shared affiliation with the Schwarzman College of Computing. Her research focuses on building predictive computational models to understand human movement, integrating theory, modeling, and experimental approaches. Key areas include analyzing computational objectives in movement decisions (e.g., energy, stability, time), studying internal variables guiding locomotion control, and developing theories of adaptive motor learning. Her lab emphasizes practical applications in neuromotor rehabilitation and explores strategies to enhance learning efficiency. They employ a 'nails-not-hammers' approach, letting scientific questions drive methodological choices rather than vice versa. Current projects include markerless motion capture for gait analysis and developing therapeutic tools for Parkinson's disease using magnetoelectric nanodiscs. Seethapathi is actively recruiting graduate students, postdoctoral researchers, and undergraduates. The lab collaborates across disciplines, combining neuroscience, engineering, and computer science to advance translational research in movement science.

• Artificial Intelligence
• Robotics
• Ethics of AI
• +۴ مورد دیگر

Benjamin Kuipers is a Professor in the Department of Computer Science and Engineering at the University of Michigan. His research focuses on artificial intelligence, robotics, and the ethical implications of autonomous systems. He emphasizes human-like morality and ethical frameworks for robots, with contributions to navigation algorithms, tactile servoing, and trustworthiness in AI. Dr. Kuipers mentors PhD students with a focus on self-motivation and clear communication. He encourages internship experiences and teaching roles (e.g., GSI positions) to broaden professional development. His advising style adapts to students' progress, prioritizing intellectual leadership and publication impact over mere productivity metrics. Key research areas include social navigation, robot-human interaction, and developmental learning. He advocates for conferences like AAAI and ICRA to ensure visibility for research. His work bridges technical innovation with societal impacts, addressing challenges in autonomous vehicles and ethical AI governance. Although no explicit awards are listed, his contributions to AI ethics and robotics have positioned him as a thought leader in the field. He collaborates on projects like the spatial semantic hierarchy and cognitive mapping, emphasizing embodied intelligence and sensorimotor learning.

Michael Bruenigمشاهده پروفایل

استاد

• Robotics
• Cybersecurity
• Data Innovation
• +۶ مورد دیگر

Professor Michael Bruenig is the Head of School for the School of Electrical Engineering and Computer Science (EECS) at The University of Queensland (UQ), a position he has held since 2016, with an interim role as Head of UQ’s Business School from 2019–2021. He previously led the CSIRO’s $140m National Research Flagship on Digital Productivity and co-founded Data61. With a PhD from RWTH Aachen University, his career spans automotive R&D in Germany, Silicon Valley, and Australia. He holds a Master’s and PhD in Science from RWTH Aachen University, Germany. His research focuses on strategic innovation, entrepreneurship, and translating research into industry impact through ventures like UQ Cyber, the National Industry 4.0 Energy Testlab, and the QLD Government AI Hub. He pioneered UQ’s Bachelor of Computer Science, Master of Cyber Security (based on US NICE Framework), and online Master of Business Analytics. His work spans robotics, sensor networks, and terahertz technology, with recent articles addressing lidar-based navigation, terahertz imaging, and cybersecurity. He advises startups and sits on boards, driving commercialization and spin-offs. Key initiatives include UQ Innovate and UQ Ventures, fostering student and faculty entrepreneurship. Labs and teams include collaborations on AI, Industry 4.0, and energy systems. His leadership emphasizes cross-disciplinary projects and curriculum innovation in tech and data fields.

Meiyi Maمشاهده پروفایل

استادیار

• Artificial Intelligence
• Formal Methods
• Cyber-Physical Systems
• +۷ مورد دیگر

Introduction Dr. Meiyi Ma is an Assistant Professor in the Department of Computer Science and the Institute for Software Integrated Systems at Vanderbilt University . Her research integrates machine learning and formal methods to build safe, reliable Cyber-Physical Systems (CPS), with applications in Smart Cities , Healthcare , and Emergency Response . She holds a PhD from the University of Virginia under Professors John A. Stankovic and Lu Feng. Education PhD in Computer Science, University of Virginia Research Interests Dr. Ma’s work focuses on risk-aware AI systems , verified AI , and explainable machine learning . She develops solutions for safety-critical CPS in domains like urban infrastructure, healthcare, and emergency management. Key projects include: - Formal methods for federated learning and unlearning attacks - AI-driven systems for non-emergency call handling - Runtime monitoring in smart cities using temporal logic Award Highlights Google Academic Research Award (2024) NSF grants for GenAI in emergency response and STEM education (2024) Best Service Award at IEEE/ACM CHASE (2024) VUSE Community Impact Research Award (2024) Grants & Advising Dr. Ma leads NSF-funded projects on GenAI in dispatcher training and emergency response. She advises multiple PhD students, including Ziyan An (federated learning) and Hanchen Wang (remote physical therapy systems). Undergraduate researchers contribute to projects like AI route generation and safety monitoring. Labs & Collaborations Her lab collaborates with Metro Nashville Government on emergency response systems and Nashville Public Schools on AI-driven alert systems. Recent activities include organizing workshops on Future Technologies for Emergency Response and hosting industry visits to Vanderbilt’s CPS research facilities.

Alireza Tamaddoni-Nezhadمشاهده پروفایل

دانشیار

• Machine Learning
• Artificial Intelligence
• Computational Intelligence
• +۵ مورد دیگر

Dr. Alireza Tamaddoni-Nezhad is a Reader (Associate Professor) in Machine Learning and Computational Intelligence at the University of Surrey's School of Computer Science and Electronic Engineering. He holds a PhD from Imperial College London and is a Fellow of the Higher Education Academy (FHEA). His research focuses on Machine Learning, particularly Inductive Logic Programming (ILP), and its applications in ecology, medicine, and autonomous systems. Education: BSc, MSc, DIC (Imperial College London), PhD (Imperial College London). Research interests emphasize symbolic-probabilistic approaches for ecological network discovery, explainable AI, and combining ILP with neural networks. He leads projects like the EPSRC-funded COMFOCUS initiative (2018–2022, £1.6M), focusing on food consumer communities. His work bridges theory and real-world applications in agriculture, healthcare, and autonomous systems. He supervises postdoctoral researchers such as Dr. Stassa Patsantzis and Dr. Dany Varghese, both working on explainable AI under EPSRC grants. Teaching includes leading modules like Machine Learning and Data Mining (COMM055). His Human-Machine Learning and Reasoning Lab explores human-AI collaboration for decision-making in legal and safety contexts.

Masa Noguchiمشاهده پروفایل

دانشیار

• Sustainable Housing
• Zero Energy Building Design
• Mass Customization in Construction
• +۳ مورد دیگر

Associate Professor Masa Noguchi leads the ZEMCH (Zero Energy Mass Custom Home) research initiatives at the University of Melbourne's Melbourne School of Design, part of the Faculty of Architecture, Building and Planning. He specializes in sustainable housing solutions, having pioneered the ZEMCH Network—a global collaboration spanning 40+ countries—organizing international conferences, workshops, and technical missions. His work emphasizes mass customization systems for affordable, net-zero energy housing, demonstrated through projects like Canada’s first net-zero home (EcoTerra House) and Scottish/Brazilian ZEMCH construction collaborations. Research focuses include environmental experience design, prefabricated construction, and climate-responsive housing models. He coordinates ZEMCH design studios like the 'Travelling Studio' and 'Design Thesis Studio' at MSD, while maintaining editorial roles in 10 journals and delivering keynote lectures globally on sustainable architectural practices. His certifications include Chartered Engineer (UK), Certified Passive House Designer (Germany), and Royal Architectural Institute of Canada membership. Current projects explore human-robot collaboration in construction, social housing thermal performance, and age-friendly third-place environments. ZEMCH Network partnerships with institutions in UAE, Brazil, Italy, and UK drive interdisciplinary knowledge exchange across academia and industry.

• Nanotechnology
• Quantum Computing
• Atom Scale Fabrication
• +۴ مورد دیگر

Robert Wolkow is a Professor in the Department of Physics at the University of Alberta, holding the iCORE Chair of nanoscale Information and Communication Technologies. He leads the Hybrid Nano-Electronic Systems program at the National Institute for Nanotechnology and serves as Chief Technical Officer of Quantum Silicon Inc. His research focuses on atom-scale fabrication, quantum computing, and ultra-low-power electronics. Wolkow has pioneered techniques in atomic-scale device manufacturing using scanning probe microscopy and hydrogen lithography. Education: BSc (Waterloo, 1982), PhD (Toronto, 1987). Postdoctoral training at IBM Yorktown Heights and AT&T Bell Laboratories preceded his senior roles at the National Research Council of Canada. He has held leadership positions including Scientific Director of the Hitachi electron microscopy product development Centre. Research interests emphasize atomic-scale engineering of silicon surfaces, including dangling bond logic systems, quantum dots, and nanoelectronic devices. His work bridges fundamental physics with applied technologies like quantum computing and nanofabrication automation. Recent publications highlight advancements in editable atomic-scale devices, charge defect simulations, and machine learning-driven nanoscale manufacturing. Wolkow’s innovations include the first atomic-scale transistor and methods for precise atomic positioning. His labs integrate scanning tunneling microscopy, nanomanipulation, and computational modeling to explore silicon’s quantum and electronic properties at the atomic limit. Collaborations span academia and industry, driving applications from quantum sensors to next-generation computing architectures.

Peter W.A. Zegelaarمشاهده پروفایل

استاد

• Advanced Driver Assistance Systems (ADAS)
• Vehicle Dynamics and Control
• Cooperative Driving Systems
• +۳ مورد دیگر

Peter W.A. Zegelaar is a part-time Professor of Smart Vehicle Technology at the Department of Mechanical Engineering, Eindhoven University of Technology (TU/e). His academic role is within the Dynamics and Control research group. He holds dual affiliations: as Technical Expert Brake Controls at Ford Research and Advanced Engineering Europe (since 2003) and former research roles at Robert Bosch GmbH (1998–2003). He earned his MSc (1991) and PhD (1998) in Mechanical Engineering from Delft University of Technology (TU Delft). Education: MSc in Mechanical Engineering, TU Delft (1991) PhD in Mechanical Engineering, TU Delft (1998) His research focuses on advanced driver assistance systems (ADAS) , including cooperative driving strategies, collision avoidance, and sensor integration. Key projects include Simultaneous Localization and Mapping (SLAM) with radar sensors, trajectory planning for parking, and platooning control algorithms. His work bridges theoretical control systems with automotive industry applications. Recent research trends emphasize cooperative autonomous platooning and merging control strategies , addressing challenges like gap management and sensor noise mitigation. His publications highlight innovations in merging algorithms and lane-change dynamics for automated vehicles. Advising & Grants: Supervised 8 academic works (names unlisted). Collaborations include Ford, Bosch, and TU/e’s Dynamics and Control group. His research aligns with UN Sustainable Development Goals related to road safety and sustainable transport. Labs/Teams: Active in TU/e’s Dynamics and Control group and Ford’s Vehicle Dynamics department, focusing on brake control systems and cooperative driving solutions.

• Artificial Intelligence
• Recommender Systems
• Natural Language Processing
• +۳ مورد دیگر

Benjamin Uwe Kille is an Associate Professor in the Department of Computer Science at NTNU, affiliated with the Faculty of Information Technology and Electrical Engineering. His research focuses on artificial intelligence, particularly in recommender systems, natural language processing, fairness in AI, and political text analysis. He leads initiatives involving large language models (e.g., SP-BERT for Scandinavian languages) and explores ethical challenges in AI applications like healthcare and education. Kille is actively involved in organizing workshops (e.g., INRA) and contributes to public outreach through lectures and media engagements. Research Interests: His work spans algorithmic fairness, news personalization, political discourse analysis, and generative AI applications in healthcare and public services. Recent studies include detecting political viewpoints in Norwegian texts and ensuring fairness in recommendation systems for previously unseen users. Publications: His recent work addresses topics like transparent fairness mechanisms, news image-text alignment, and Scandinavian language models. He co-authored reports on AI in healthcare (AIFAL project) and presented at venues like ACM RecSys and NorwAI events. Outreach & Teaching: Teaches TDT4215 - Recommender Systems at NTNU. Engages in public discourse via talks at companies (e.g., Nordea, Statsbygg) and media interviews (e.g., Gemini.no, Digi.no). Collaborates with institutions like SINTEF and the Norwegian Directorate of Health on AI applications. Labs & Teams: Active in the NAIL (Norwegian Artificial Intelligence Lab) and NorwAI initiatives, driving advanced AI research and development in Norway.

Hormoz Marzbaniمشاهده پروفایل

دانشیار

• Mechanical Engineering
• Automotive Engineering
• Vehicle Dynamics
• +۷ مورد دیگر

Associate Professor Hormoz Marzbani is affiliated with the School of Engineering at RMIT University. His roles include teaching and research supervision in areas such as Dynamics and Vibration, Vehicle Dynamics, Autonomous Systems, and Mechanical Design. He actively supervises research projects focusing on autonomous vehicle control, safety enhancements, and advanced manufacturing techniques. Research Interests Mechanical Engineering Automotive Engineering Autonomous Systems Motion Sickness Mitigation Additive Manufacturing Infrastructure Integration for Automated Vehicles Recent research trends include optimizing autonomous vehicle trajectories, enhancing safety through infrastructure collaboration, and mitigating motion sickness via ergonomic path planning. His work frequently addresses challenges in control systems, sensor fusion, and experimental validation with scaled prototypes. Supervision & Grants Supervision projects include topics like Autonomous Optimal Vehicle Control , Trajectory Optimization for Active Safety , and 3D Printed Mycelium Composites . His research often intersects with industry needs, leveraging grants for experimental setups and computational modeling. Labs & Collaborations Engages in collaborative projects involving scaled autonomous vehicle testing and infrastructure-based sensor networks, emphasizing real-world application of theoretical advancements.

• Electrical Engineering
• Control Engineering
• Mechatronics
• +۴ مورد دیگر

Mr. Luke McNabb is a Research Fellow in the Research & Innovation department at RMIT University, located at the City Campus in Australia. His work focuses on electrical and electronic engineering with particular emphasis on control systems, energy conversion, and renewable energy technologies. Dr. McNabb's research interests span across several key areas of engineering: Electrical Engineering and Power Electronics Control Engineering and Mechatronics Robotics and Automation Maritime and Wave Energy Systems Mechanical Engineering applications Communications Engineering His recent publications demonstrate a strong focus on current regulation techniques, anti-windup mechanisms in control systems, and innovative approaches to renewable energy conversion, particularly in wave energy applications. McNabb's work often involves the development of novel control algorithms for electrical machines and power electronic systems, with applications ranging from industrial motor drives to marine energy harvesting. Dr. McNabb has contributed to significant advancements in model-predictive control for induction machines, permanent magnet drives for wave energy converters, and vibration energy harvesting systems. His research frequently appears in high-impact journals such as IEEE Transactions on Control Systems Technology, IEEE Transactions on Industrial Informatics, and Mechanical Systems and Signal Processing. His scientific contributions include: Development of novel anti-windup mechanisms for current regulators Innovative designs for wave energy converters and associated power take-off systems New concepts for electromagnetic vibration energy harvesters Planar generators for multi-directional wave energy extraction Dr. McNabb collaborates with researchers across multiple institutions, as evidenced by his co-authored publications. His work bridges theoretical control system design with practical implementation in renewable energy applications, particularly focusing on improving efficiency and reliability of electrical power conversion systems.

Daniel Johnsonمشاهده پروفایل

استاد

• Motivations for Videogame Play
• Player Experience
• Impact of Videogames on Wellbeing
• +۵ مورد دیگر

Professor Daniel Johnson holds a position in the School of Computer Science at Queensland University of Technology (QUT), where he leads the QUT Games Research and Interaction Design Lab. He earned a PhD from the University of Queensland, focusing on the psychology of human-computer interactions and video games. His research interests span motivations for videogame play, player experience analysis, gamification, and the impact of games on wellbeing. Johnson is also Chair of the ACM CHI PLAY Steering Committee and maintains an affiliation with the Cambridge University Well-being Institute. Johnson’s educational background includes Bachelor’s and Honours degrees in Psychology, a Graduate Certificate in Higher Education, and postdoctoral work at the University of Cambridge’s Engineering Design Centre. His teaching focuses on game design, innovation, and computer game studies at QUT. His research collaborations include projects with the Movember Foundation (MindMax and WellPlayed initiatives), The Binary Mill, and cooperative research centers like Young and Well CRC. He has secured significant grants, including CAT 1 funding for projects like Engaging Augmented Reality on 3D Head Up Displays to Reduce Risky Driving and Make and Connect: Enabling People to Connect through their Things . Johnson’s work bridges academia and industry, emphasizing real-world applications in usability, user experience, and inclusive design. His lab explores cutting-edge topics such as VR/AR in geoscience, esports physiology, and ethical design of immersive technologies.

Jason Millarمشاهده پروفایل

دانشیار

• Ethical Engineering
• Artificial Intelligence Ethics
• Robotics Policy
• +۵ مورد دیگر

Dr. Jason Millar is an Associate Professor at the University of Ottawa's School of Electrical Engineering and Computer Science, with a cross-appointment to the Department of Philosophy in the Faculty of Arts. He holds the Canada Research Chair in Ethical Engineering of Artificial Intelligence and Robotics and directs the Canadian Robotics and Artificial Intelligence Ethical Design Lab (CRAiEDL). His work focuses on integrating ethical thinking into engineering workflows, particularly in automated vehicles, healthcare robotics, and military robotics. He provides expert testimony on AI ethics at international forums like the United Nations and advises on policy for autonomous systems. Education: Engineering Physics degree with prior engineering practice before transitioning to academic ethics research. His research emphasizes ethical frameworks for emerging technologies, including privacy preservation in automated systems and liability issues in advanced driver assistance systems. Research Interests: Ethical engineering of AI/robotics, policy development for autonomous systems, human-robot trust dynamics, and societal impacts of automation. His work bridges engineering, philosophy, and law, advocating for interdisciplinary approaches to ethical technology design. Scientific Awards: Canada Research Chair in Ethical Engineering of AI and Robotics (2015–present). Advising & Grants: Advises on policy for autonomous vehicles and military robotics. Has secured grants for ethical AI design and public engagement initiatives. Labs/Teams: Leads the CRAiEDL lab, exploring ethical design principles for robots and AI systems. Collaborates with interdisciplinary teams across engineering, philosophy, and legal disciplines.

Tanya Vladimirovaمشاهده پروفایل

استاد

• Embedded Systems
• Artificial Intelligence
• Space Systems Engineering
• +۵ مورد دیگر

Professor Tanya Vladimirova is a Professor of Electronic and Computer Systems Engineering at the University of Leicester, affiliated with the School of Engineering's Mathematical Sciences department. Her research focuses on custom computing for edge intelligence, embedded systems design, and space-based applications. She pioneered innovations in satellite computing systems, including reconfigurable on-board computers, fault-tolerant designs, and FPGA-accelerated image processing. Her work integrates AI, digital signal processing, and hardware acceleration for applications in autonomous vehicles, spacecraft, and IoT. Key achievements include the first FPGA-based on-board hyperspectral image compression systems, fault-tolerant distributed computing frameworks for satellites, and self-healing distributed intra-satellite systems. Current projects explore machine learning for satellite reliability and autonomous vehicle vision systems. Prior to Leicester, she led a globally recognized group at the Surrey Space Centre, collaborating with Surrey Satellite Technology Limited (SSTL). Her research spans satellite miniaturization, wireless sensor networks for planetary exploration, and radiation-hardened computing. Her publications address challenges in satellite data processing, fault tolerance, and embedded AI. Notable contributions include novel algorithms for landmine detection, radiation mitigation strategies for FPGAs, and adaptive middleware for distributed space systems. Her work bridges theoretical computing with practical aerospace engineering, emphasizing resilience and efficiency in hostile environments.