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Derek CovillView profile

Senior Lecturer

• Sports Engineering
• Digital Fabrication
• Additive Manufacturing
• +3 more

Dr. Derek Covill is a Senior Lecturer at the University of Brighton, affiliated with the School of Architecture, Technology and Engineering and the Advanced Engineering department. He holds roles as Principal Lecturer and serves as an External Examiner for multiple universities, including Robert Gordon University and Sheffield Hallam University. His academic journey includes a BEng in Medical Engineering from Queensland University of Technology and a PhD in Engineering from the University of Brighton. Dr. Covill’s research spans sports engineering, additive manufacturing for medical devices, digital fabrication tools, and engineering education. Notable projects include the Steel Bicycle Project exploring frame design and the development of electrochemical sensors for biomedical applications. He has collaborated with industries like Clarks International and OSET Bikes through Knowledge Transfer Partnerships (KTPs). His recent publications focus on dyslexic student support in design education, bicycle dynamics optimization, and learning analytics tools. Dr. Covill has advanced degrees in Data Analytics (MSc, 2026), an MBA (2023), and a Postgraduate Certificate in Teaching and Learning in Higher Education (2007). His external roles include examiner positions across product design and engineering programs.

• Digital Twin
• Manufacturing Engineering
• Aircraft Assembly
• +5 more

Tengfei Long serves as a Research Fellow at Coventry University's Centre for Manufacturing and Materials, specializing in digital twin applications for advanced manufacturing systems. His active involvement spans multiple high-impact research projects including Power electronics Upscale for Localisation and Sustainable Electrification (2024-2027), WAVETAILOR modular laser production systems (2024-2027), and CLEAN sustainable logistics initiatives (2022-2024). Dr. Long's research integrates Digital Twin technology with manufacturing engineering to solve critical challenges in aircraft assembly, power electronics, and sustainable production. His work employs advanced computational methods including dynamic Bayesian networks, fuzzy rule systems, and IIoT architectures to enhance productivity, accuracy, and resource allocation in complex production environments. Key focus areas include intellectual property management within digital frameworks, lightweight process twin development, and real-time simulation of manufacturing systems. Recent publications demonstrate consistent innovation in applying digital twin technology across diverse manufacturing contexts, with particular emphasis on data capture methodologies, simulation accuracy improvements, and sustainable production integration. His research bridges theoretical computational models with practical industrial applications in aerospace, CNC machining, and personalized production systems. As a Research Fellow, Dr. Long contributes significantly to three major funded projects: Power electronics Upscale (focusing on sustainable electrification), WAVETAILOR (developing modular laser sources for short-run production), and CLEAN (addressing African logistics challenges). These initiatives involve cross-disciplinary collaboration with industry partners and academic researchers across multiple European institutions. He operates within Coventry University's Centre for Manufacturing and Materials, participating in a dynamic research ecosystem that combines additive manufacturing, digital twin technologies, and sustainable production methodologies to advance next-generation manufacturing solutions.

• Innovation and entrepreneurship
• Healthcare leadership
• Strategic management
• +2 more

Joel H. Dobbs is Senior Instructor in the Department of Management, Information Systems and Quantitative Methods at the University of Alabama at Birmingham’s Collat School of Business, where he also serves as Executive-in-Residence and co-director of the Healthcare Leadership Academy. He is a veteran life-sciences executive with more than three decades of leadership experience spanning pharmaceutical, biotechnology, regulatory, and academic arenas. Education Doctor of Pharmacy (PharmD), University of Tennessee System – Knoxville, 1976 Master of Public Health (MPH), University of Alabama at Birmingham, 1982 Bachelor of Science in Pharmacy, Samford University, 1975 Research & Teaching Interests Dr. Dobbs focuses on innovation, entrepreneurship, strategic management, and leadership within healthcare ecosystems. His pedagogy integrates multidisciplinary team science, bringing together engineering, business, and clinical trainees to tackle real-world medical-device challenges. He routinely leads executive-education modules, boot camps, and capstone experiences that emphasize translational research, commercialization pathways, and transformational leadership. Publication Trends Across four decades his peer-reviewed work has migrated from clinical pharmacology and regulatory informatics in the late 1970s–1990s to contemporary scholarship on experiential, cross-disciplinary education. Recent outputs emphasize team-based medical-device design, commercialization curricula, and integrative capstone models that leverage university–industry partnerships. Grants & Programs CTSA UM1 – National Center for Advancing Translational Sciences/NIH (2022) UAB Master of Engineering in Design and Commercialization – VentureWell (2015) Engineering Design Projects to Aid Persons with Disabilities – NSF (2012) Invention 2 Innovation at UAB – National Collegiate Inventors and Innovators Alliance (2011) Labs, Teams & Initiatives Dr. Dobbs co-directs the Healthcare Leadership Academy and mentors within the NSF I-Corps, UAB Innovation Council, and Blazer Innovation Challenge ecosystems. Through The Compass Talent Management Group LLC—where he is CEO—he advises organizations on talent strategy and structural design for innovation.

John ChivertonView profile

Senior Lecturer

• Signal Processing
• Medical Imaging
• Computer Vision
• +4 more

Dr. John Chiverton is a Senior Lecturer at the University of Portsmouth within the Faculty of Technology, School of Electrical and Mechanical Engineering and affiliated with the Institute of Life Sciences and Healthcare and Portsmouth AI and Data Science Centre . He specializes in signal and image processing with applications across biomedical engineering, computer vision, and assistive technologies. Research Interests : Automated 3D Imaging Analysis Physiological Signal Processing (Blood Pressure Forecasting) Computer Vision for Human Activity Recognition Machine Learning in Medical and Industrial Applications Multi-modal Sensor Data Integration Scientific Contributions include 49 research outputs (17 articles, 28 conference contributions) and 15 projects funded by entities like Google and Mitsui Sumitomo Insurance Welfare Foundation . His work spans biomedical imaging, robotics, and smart environment systems. Awards : IEEE Award IPEM Award Collaborations include institutions like University of Surrey, University of Bristol, and cross-disciplinary teams in medical imaging and smart material analysis . He supervises PhD students in areas like 3D Imaging and Physiological Signal Analysis .

• Human Factors
• Human-Robot Interaction
• Human-in-the-Loop Systems
• +4 more

Dr. Yang Jing is an Assistant Professor in the Department of Industrial and Systems Engineering at the University at Buffalo. Their research focuses on human-robot interaction, adaptive automation, and human factors in healthcare and autonomous systems. Dr. Yang holds a PhD in Industrial Engineering from Purdue University (2023). Research Interests: Human factors engineering, robotic-assisted surgery, cognitive modeling, medical performance assessment, and multimodal sensing for situation awareness. Their work integrates physiological measurements (EEG, eye-tracking) with computational intelligence to improve human-technology collaboration. Key Research Contributions: Pioneered adaptive human-robotic interaction architectures for surgical environments, developed EEG-based techniques for driver state monitoring, and created computer-vision systems for ergonomics assessment. Recent work explores neurotechnological aids for semi-autonomous surgical tools and automated driving situation awareness classification. Labs & Teams: Leads the Human Factors in Robotics Lab, focusing on interdisciplinary projects at the intersection of industrial engineering, neuroscience, and medical technology. Collaborates with automotive and healthcare industries to translate research into practical applications.

Faheem KhanView profile

Professor

• 6G Communications
• Integrated Sensing and Communication Systems
• Full-duplex Communications
• +6 more

Dr. Faheem Khan is a Reader in Electronic Engineering at the University of Huddersfield's School of Computing and Engineering, and Course Leader for the MSc in Electronic and Automotive Engineering. With over 20 years of academic and research experience across institutions in the UK, Oman, UAE, and India, he has contributed significantly to wireless communications and signal processing. His career includes postdoctoral research at the University of Edinburgh, where he managed EU and EPSRC projects. Education: PhD, Electrical and Electronic Engineering, Queen’s University Belfast (2012) MSc, Communication and Radar Engineering, Indian Institute of Technology Delhi (India) BSc, Electronics Engineering, Aligarh Muslim University (India) Research Interests: Focuses on 6G Communications, Full-duplex Systems, IoT Networks, and Cognitive Radio. His work integrates machine learning, MIMO systems, and spectrum sharing to advance wireless technologies. He leads projects funded by Innovate UK (e.g., RF transceiver design for deep space) and EU Horizon grants (e.g., AI-driven spectrum sharing in 6G). Grants & Contributions: Principal Investigator of £0.5M Innovate UK AKTP grant for RF transceiver design Co-investigator in EU Horizon projects (e.g., EVOLVE, MOTOR5G) totaling €4M Authored successful EPSRC proposals like MANGO (Non-orthogonal access in 5G) Awards: Fellow of the Higher Education Academy (FHEA) Over 600 citations and an h-index of 18 Teaching & Supervision: Leads modules like Analogue System Integration and supervises PhD students in wireless systems and IoT. Collaborations: International partnerships include National Sun Yat-sen University (Taiwan) for AI-driven spectrum sharing and European institutions for 6G research.

Philip FergusonView profile

Associate Professor

• Satellite guidance and control
• CubeSats
• Drone control and navigation
• +3 more

Dr. Philip Ferguson is an Associate Professor of Mechanical Engineering and Magellan Industrial Research Chair at the University of Manitoba's Price Faculty of Engineering. He leads the Space Technology and Advanced Research Laboratory (STARLab) and collaborates with the Centre for Earth Observation Science (CEOS). His work focuses on making aerospace technology accessible through low-cost, reliable solutions for Arctic communities and search-and-rescue operations. Dr. Ferguson holds a PhD from MIT and has industry experience with Magellan Aerospace and PrecisionHawk Inc. Education: PhD in Aerospace Engineering, MIT (2006) SM in Aerospace Engineering, MIT (2003) B.A.Sc. in Engineering Science (Aerospace Option), University of Toronto (2000) Dr. Ferguson's research spans satellite guidance, drone navigation, Arctic remote sensing, and machine learning. His projects include CubeSats for climate change monitoring, drones for search-and-rescue, and airships for Arctic communications. He emphasizes interdisciplinary collaboration to address challenges in Northern Canada and Indigenous communities. His recent articles explore fault detection in spacecraft systems, drone-based payload control, and innovative navigation algorithms. He actively recruits graduate students interested in advancing aerospace accessibility. Labs/Teams: STARLab (founded 2014), CEOS collaborations, and industry partnerships with Magellan Aerospace.

Marija Zahar ĐorđevićView profile

Researcher

• Quality Management
• Digital Manufacturing
• Logistics Systems
• +3 more

Marija Zahar Đorđević is a Researcher at the University of Kragujevac's Faculty of Engineering, affiliated with the Department of Production Engineering. Her work focuses on advanced manufacturing systems, quality management, and digital transformation in industrial and business processes. She holds a position since 2020 and contributes to research in technical-technological sciences with a specialization in mechanical engineering. Her research interests span Quality 4.0/5.0 systems, digital manufacturing technologies, logistics optimization, and software engineering applications. She has extensively explored smart quality frameworks, IoT-enabled logistics systems, and the integration of fuzzy logic methodologies in decision-making processes. Publications highlight her expertise in cloud-based ecological solutions, game development methodologies, and vulnerability assessment tools for projects in uncertain environments. Her work emphasizes real-world applications of theoretical models in SMEs and military logistics contexts. Her contributions include developing web-based applications using modern architectures (e.g., SPA) and ERP software analysis. She has also addressed challenges in project lifecycle quality, risk exposure in startups, and economic factors influencing quality of life.

• Digital Twins
• AI in Construction
• Robotic Automation
• +2 more

Dr. Yiping Meng is a Lecturer in Construction Management at Teesside University's School of Computing, Engineering and Digital Technologies. She holds a PhD in Multi-objective Optimisation from the University of Sheffield and has postdoctoral research experience at Loughborough University and University of Cambridge. Her research integrates digital twins, AI, and robotic automation for sustainable construction. Key areas include dynamic digital twin systems for building performance tracking, multi-criteria decision support for automation construction, and computer-aided design of complex architectural geometries. She currently leads research on RECONSTRUCT: A Territorial Construction System for Circular Low-Carbon Environments. Publications demonstrate cross-disciplinary approaches combining computational optimization, material science, and building information modeling. Recent work emphasizes machine learning applications in energy management and robotic fabrication. Dr. Meng collaborates with national and international partners on circular economy frameworks and net-zero construction initiatives. She teaches digital technologies in construction and mentors students in sustainable design principles.

Murali ParanandiView profile

Professor

• Computational Design
• Digital Pedagogy
• Target Value Design
• +3 more

Professor Murali Paranandi is a faculty member at Miami University, serving as a Professor in the Department of Architecture and Interior Design since 1996. He holds affiliate status in the Emerging Technology in Business and Design (ETBD) program. His educational background includes a Master of Architecture from Ohio State University and Kent State University, as well as a Bachelor of Architecture from Jawaharlal Nehru Technological University. His research focuses on Computational Design , Digital Pedagogy , Target Value Design , Digital Fabrication , and Mass Timber Architecture , emphasizing the integration of technology into architectural education and practice. He has received the 2015 Crossan Hays Curry Award for his contributions to the field. Teaching highlights include courses such as ARC 101 Beginning Design Studio , Architecture Studio , and Trends in Computational Design . His scholarly work spans over three decades, addressing topics like Building Information Modeling (BIM), daylighting simulation, and virtual reality applications in architecture. He has authored notable publications, including Alter Studio: 6 Houses (2014) and Alter Studio: 6 Houses (2014), and co-authored articles in journals like the International Journal of Architectural Computing . Prof. Paranandi’s professional experience includes roles as a Technical Support Engineer at auto•des•sys, Inc., and adjunct teaching positions. His work bridges theoretical research with practical applications, advocating for innovative pedagogical approaches to leverage emerging technologies.

Junghwan KimView profile

Professor

• Communication Systems
• Satellite Systems
• Anti-jamming Technologies
• +7 more

Junghwan Kim is a Professor in the Department of Electrical Engineering and Computer Science at the University of Toledo's College of Engineering. His research focuses on advanced communication systems, including satellite architectures, wireless sensor networks, and anti-jamming technologies. He also explores physical layer encryption and digital multimedia broadcasting (DMB). His work emphasizes practical applications such as improving bit error rate (BER) in wireless systems through innovative modulation techniques like APSK-TCM and LDPC coding. Recent contributions include secure physical layer key generation for autonomous vehicles and machine learning approaches to face detection in noisy channels. Publications highlight advancements in satellite communication synchronization, cooperative localization in cellular networks, and error correction techniques for CDMA systems. His research bridges theoretical foundations with real-world challenges in telecommunications and cybersecurity.

Lawrence M. WolfView profile

Associate Professor

• Organic Chemistry
• Organometallic Chemistry
• Computational Chemistry
• +6 more

Lawrence M. Wolf is an Associate Professor of Chemistry in the College of Sciences at the University of Massachusetts Lowell. His research focuses on computational and theoretical approaches to understanding organic and organometallic reaction mechanisms, with particular expertise in catalysis. Dr. Wolf's work bridges experimental chemistry with computational modeling to elucidate fundamental principles of chemical reactivity. Education: Ph.D. in Organic Chemistry (2012), University of Illinois at Urbana-Champaign Computational/Theoretical Chemistry (2016), Max-Planck-Institut für Kohlenforschung, Mülheim an der Ruhr, Germany B.S. in Chemistry (2006), Drexel University, with Physics as supporting area Dr. Wolf's research interests center on developing modern reactivity models for elucidating reactivity and selectivity principles in transition metal-mediated catalysis and organocatalysis. His work employs computational chemistry approaches including quantum mechanical calculations, molecular dynamics simulations, and quantitative structure-activity relationship (QSAR) methods. He has made significant contributions to understanding asymmetric phase transfer catalysis, palladium-mediated reactions, and ruthenium-catalyzed alkyne transformations. His research group applies strategies in computer-aided catalyst design to develop more efficient and selective catalytic systems. Analysis of Dr. Wolf's publication record reveals a strong focus on computational investigations of reaction mechanisms across organic and organometallic chemistry. His recent work has expanded into materials science applications, particularly regarding graphene functionalization and 2D materials. The research consistently combines theoretical calculations with experimental validation, demonstrating the power of computational chemistry to predict and explain chemical behavior. Key thematic areas include transition metal catalysis, reaction dynamics, and the development of computational tools for predicting stereoselectivity. Dr. Wolf has presented his research at numerous international conferences including the Symposium on Electronic Structure and Dynamics of Complex Systems in Beijing (2019), the International Kyoto Conference on New Aspects of Organic Chemistry (2015), and multiple Gordon Research Conferences. His presentations consistently focus on mechanistic insights gained through computational studies of catalytic reactions.

• Wireless Networks
• Machine Learning
• 6G Communication
• +4 more

Zhu Han is a Professor at the University of Houston, TX, USA, with a PhD from the University of Maryland, College Park. He is affiliated with the Chinese Academy of Sciences' Aerospace Information Research Institute in Beijing, China. His research spans wireless networks, 6G communication, and machine learning applications in telecommunications. Key areas: Semantic communication, UAV networks, IoT security, quantum networking. Recent publications focus on federated learning, optical IRS for VLC, and resource allocation in LEO satellite systems. His work integrates AI with network security and edge computing. He collaborates extensively on topics like reconfigurable intelligent surfaces, quantum-assisted optimization, and privacy-preserving protocols. No specific awards or student details are provided in the dataset.

Dan MitchellView profile

Lecturer

• Computer-Aided Design
• Computer-Aided Manufacturing
• Industrial Prototyping
• +3 more

Dan Mitchell serves as an Instructor in the Department of Technology and Applied Science at Wayne State College. He teaches courses in industrial technology, including solid modeling, drafting, electronics, applied engineering, industrial prototypes, and manufacturing design. Prior to this role, he spent 34 years teaching at Yankton High School, where he instructed drafting, architecture, cabinetry, Cisco networking, and computer programming, alongside coaching football and wrestling. Education: MSE in Industrial Education, Wayne State College (1984) BAE in Industrial Education, Wayne State College (1989) His research interests focus on computer-aided design (CAD), computer-aided manufacturing (CAM), and project design for CNC equipment, 3D printers, and laser technology. Mitchell is actively involved with organizations such as the South Dakota Association for Career and Technical Education (SDACTE) and the National High School Coaches Association (NHSCA). In his personal time, he enjoys woodworking and traveling.

Jérémy VezinetView profile

Researcher

• Multi-sensor Hybridization
• GNSS
• Inertial Navigation
• +3 more

Jérémy Vezinet is a Researcher at Ecole Nationale de l’Aviation Civile (ENAC) since 2014, affiliated with the TELECOM Research Team. He holds a Ph.D. in multi-sensors hybridization and specializes in navigation systems. His research interests encompass GNSS technology, inertial navigation, multi-sensor hybridization, integrity monitoring, and video-based navigation. These areas emphasize robust navigation solutions in challenging environments, integrating diverse sensor modalities for enhanced accuracy and reliability. Notable research trends include hybrid navigation systems leveraging GPS/Galileo/5G, spoofing attack analysis (e.g., meaconing), and innovative applications like inertial-vision fusion for aircraft precision approaches. His work also extends to railway positioning systems and biomedical device accuracy assessments using Kalman filters. No scientific awards explicitly mentioned in the provided texts. His advisory role shows no listed students, but he has contributed to projects involving multi-antenna GNSS receivers, space launcher navigation, and diagnostics of virtual balises in rail systems. Collaborations likely exist through his research team affiliations. He is part of the TELECOM Research Team at ENAC, which operates under the Signal Processing and Navigation (SIGNAV) group. This team focuses on interdisciplinary navigation solutions combining telecommunications and sensor technologies.