جست‌وجوی استاد و پژوهشگر

Javad Zeinaliمشاهده پروفایل

استادیار

• AI in advanced manufacturing
• Predictive data analytics
• Computational Fluid Dynamics (CFD)
• +۵ مورد دیگر

Dr. Javad Zeinali is an Assistant Professor of Digital Manufacturing at the University College Dublin (UCD), School of Mechanical and Materials Engineering. He serves as Programme Director for Digital Manufacturing at UCD's Advance Centre and leads the Laboratory for Advanced Manufacturing Simulation and Robotics (LAMS). His academic career includes roles at the University of Limerick as Lecturer and Research Fellow before joining UCD in 2023. Dr. Zeinali holds a PhD (2015) and MEng (2012) from Universiti Teknologi Malaysia (UTM), with postdoctoral training at Kyushu University (Japan). He has industry experience as Technical Manager at RS Co., Iran. Professional certifications include the U21 Mid-Career Researcher Programme and Universal Design in Teaching & Learning. Research Focus: His work integrates AI, predictive analytics, and CFD with advanced manufacturing. Key areas include digital twins, magneto-rheological devices, and AR/VR solutions for sustainable manufacturing. He leads projects like RTForm (robotic toolkits), ARIOS (AR operator support), and VRSafe (VR workplace safety training). Awards & Grants: Recipient of Bronze Medal (MTE 2014), Merit Thesis Award (2015), and Gold Medal (UTEMEX 2013). Active in EU funding, he coordinates grants including the €2.5M ARIOS project and leads initiatives at SSPC and DPTC dairy technology centers. Teaching: Teaches Industrial Data Analytics, Engineering Project Management, and Automation modules. Uses active learning and technology-enhanced methods. Coordinates courses like Industrial Data Analytics and Engineering Project Management at UCD. Collaborations: Serves on EU-NESA Agri-Food Sector Network and co-leads international projects. Supports Chinese PhD candidates via UCD-CSC funding schemes. Open to collaborations in AI-driven manufacturing and predictive analytics.

Sidney Givigiمشاهده پروفایل

استاد

• Robotics
• Machine Learning
• UAV Control
• +۵ مورد دیگر

Sidney Givigi is a Professor at Queen's University, associated with the School of Computing within the Faculty of Arts and Science. His research focuses on Robotics, Machine Learning, UAV Control, and Multi-Vehicle Systems. He leads projects in autonomous systems, swarm intelligence, and reinforcement learning applications. His work addresses challenges in autonomous vehicle coordination, adversarial attack mitigation in intelligent systems, and real-time decision-making algorithms. Collaborative perception under adverse conditions and dynamic system control are key research themes. Research highlights include the TRATSS task scheduling system for autonomous vehicles, the IPRPAS benchmark dataset for adversarial sample analysis, and innovations in UAV software update protocols. His contributions span theoretical frameworks and practical implementations in robotics and AI. He is affiliated with the Ingenuity Labs Research Institute, advancing translational research in automation and intelligent systems. No academic awards or student advisement information is explicitly documented in the provided texts.

Nataliya Chukhrovaمشاهده پروفایل

پژوهشگر

• Data Science
• Business Analytics
• Soft Computing
• +۹ مورد دیگر

Dr. Nataliya Chukhrova is a Researcher at the Institut für Mathematik und Statistik within the University of Hamburg Business School . Her research focuses on Data Science, Business Analytics, Fuzzy Statistics, and Quantitative Risk Management, with applications in Finance, Health, and Industrial Engineering. She has received notable awards including the Hamburger Lehrpreis 2015 for innovative teaching and the Jahrgangsbestenpreis 2011 for academic excellence. Her teaching portfolio includes courses such as Angewandte Statistik für Fortgeschrittene , Statistik mit SPSS , and Statistische Qualitätskontrolle . Her publications emphasize statistical methods in quality control, fuzzy hypothesis testing, and stochastic modeling, with a focus on practical applications in healthcare and finance. In recent years, her work has explored the intersection of fuzzy logic with traditional statistical techniques, particularly in addressing challenges posed by the COVID-19 pandemic. She collaborates extensively, often with co-author Arne Johannssen, on projects that bridge theoretical statistics and real-world operational problems.

Gajendra Kumarمشاهده پروفایل

استادیار

• Neuroscience
• Neural Circuits
• Electrophysiology
• +۴ مورد دیگر

Gajendra Kumar is an Assistant Professor of Molecular Biology, Cell Biology, and Biochemistry at Brown University, affiliated with the Data Science Institute and Carney Institute for Brain Science. His research focuses on neurodegenerative diseases, combining electrophysiology, optogenetics, neurocomputation, and AI/ML to study motor neural circuits. Notable contributions include developing closed-loop deep brain stimulation platforms for ataxia and AI-driven tools for depression detection using EEG/facial recognition. Education: PhD (2013), MSc (2007), BSc (2005) from All India Institute of Medical Sciences. Awards include Gold Medal (IGED 2022) and Hong Kong SciTech Pioneer (2022). Collaborates with experts like Prof. Eric Morrow and Prof. Judy Liu. His work spans neural circuit modeling, neuroregeneration, and neurotechnology commercialization through ventures like AniTech Limited.

Hossein Mirinejadمشاهده پروفایل

استادیار

• Optimal Drug Dosing
• Healthcare Automation
• Optimal Control Theory
• +۴ مورد دیگر

Hossein Mirinejad is an Assistant Professor in the College of Aeronautics and Engineering at Kent State University. He previously served as a Research Fellow at the FDA (2017-2019) and Postdoctoral Fellow at the University of Michigan. His research focuses on healthcare automation, optimal control applications in critical care, and autonomous robotic systems. Key research areas include precision dosing algorithms for fluid resuscitation, reinforcement learning for medical decision-making, hardware-in-the-loop testing of medical devices, and control systems for flexible manipulators. His work bridges engineering and clinical applications, emphasizing personalized treatment and medical device innovation. Mirinejad directs the Control, Automation, and Mechatronics (CAM) Lab and has secured multiple NSF grants including a CAREER award. He mentors graduate students in projects spanning medical AI, control theory, and robotic systems.

• Systems Engineering
• Operations Management
• Engineering Economics
• +۴ مورد دیگر

Dr. Paul J. Componation serves as the Associate Dean of Graduate and Interdisciplinary Affairs in the College of Engineering at The University of Texas at Arlington (UTA), where he previously held the positions of Professor and Chair of the Industrial, Manufacturing, and Systems Engineering (IMSE) Department and Executive Director of the University of Texas at Arlington Research Institute (UTARI). His distinguished career spans over three decades with significant academic appointments at Iowa State University and the University of Alabama in Huntsville, complemented by research experience at NASA's Marshall Space Flight Center. Dr. Componation earned his PhD in Industrial Engineering from West Virginia University in 1995, with an MS in Management from Troy State University (1987) and BS in Industrial Engineering from West Virginia University (1982). His educational background established the foundation for his expertise in systems engineering and operations management. His research portfolio demonstrates remarkable breadth across systems engineering, operations management, and engineering economics with practical applications in aerospace, healthcare, energy systems, and manufacturing. Dr. Componation has made seminal contributions to understanding how systems engineering practices influence project success, particularly in NASA and government contexts. His pioneering work on lean principles has provided frameworks for organizational transformation across multiple industries. Recent research directions include IoT integration in supply chain management, AI applications in manufacturing decision-making, and systems thinking approaches to healthcare improvement. Dr. Componation's scholarly impact is reflected in numerous prestigious recognitions including the 2025 Bernard R. Sarchet Award from the American Society for Engineering Management and his designation as a Fellow of the same organization. His research has attracted substantial funding from NASA, NSF, Department of Education, and industry partners including Foxconn Technology. As an educator and mentor, Dr. Componation has guided numerous doctoral and master's students through dissertation and thesis research on topics ranging from biofuel production systems to lean implementation assessment methodologies. His teaching focuses on decision analysis, engineering management, and engineering economy, with particular emphasis on developing innovative hybrid and online educational models for STEM disciplines that accommodate working professionals.

• Industrial Engineering
• Sustainability in Engineering
• Supply Chain Management
• +۴ مورد دیگر

Dr. Jamie James Rogers is a Professor and Associate Chair in the Department of Industrial, Manufacturing, and Systems Engineering at the University of Texas at Arlington (UTA). She has been on the faculty since 1994 and holds the George & Elizabeth Pickett Endowed Professorship (2021–2026). Her roles include leadership in ABET as a Fellow and former President, and she has served as IISE President. She has extensive industry experience at Texas Instruments before academia. Education: B.S. (Industrial Engineering, University of Missouri, 1979), M.S. (UT Arlington, 1981), Ph.D. (UT Arlington, 1985). Professional certifications include P.E. (Texas) and Professional Certification in Logistics (Georgia Tech). Research focuses on sustainability integration in engineering curricula, supply chain optimization, healthcare systems, and accreditation standards. She has secured over $3.6M in research funding and authored/co-authored over 140 peer-reviewed publications. Her teaching excellence is recognized through awards like the UTA Academy of Distinguished Teachers (2011) and UT System Regents’ Outstanding Teacher (2012). Key contributions include leading the 'Engineering Sustainable Engineers' NSF-funded project (2009–2012) and advancing ABET’s global accreditation efforts. She advises over 40 Ph.D. students and has been a mentor in systemic change initiatives for engineering education. Her service spans roles in the UT System Healthcare Steering Committee, Texas Higher Education Coordinating Board, and editorial boards for journals like Engineering Education Letters.

Adnan Salihbegovicمشاهده پروفایل

مدرس

• Automation Engineering
• Instrumentation
• Embedded Systems
• +۳ مورد دیگر

Adnan Salihbegovic is affiliated with the Department for Automation and Electronics, where he teaches advanced courses such as Special Measurements Techniques for undergraduate students. His curriculum emphasizes modern instrumentation methodologies, including LabVIEW programming, virtual instrumentation, and data acquisition system integration using DAQ modules and GPIB communication protocols. He oversees laboratory works involving HP and National Instruments equipment for signal analysis, logic analyzers, spectral analyzers, and oscilloscopes. His research interests focus on automation systems, embedded systems design, IoT applications, and control engineering. He has contributed to projects involving web-based SCADA systems, industrial automation workflows, and optimization of order-picking processes in logistics. His work also explores educational tools such as decompilable code editors and tiny OS kernels for teaching purposes. Salihbegovic’s publications span topics like enterprise GIS in power distribution, domain-specific modeling languages for IoT, and vibration control using fuzzy logic. He actively participates in international conferences related to automation and information technologies, demonstrating expertise in both theoretical and applied engineering solutions. His teaching integrates practical lab exercises with theoretical concepts, ensuring students gain hands-on experience with industry-standard tools like LabVIEW and DAQ systems. He also advocates for remote laboratory access and internet-based control systems to enhance educational accessibility and industrial efficiency.

Noorbakhsh Amiri Golilarzمشاهده پروفایل

استاد پژوهشی

• Artificial Intelligence
• Image Processing
• Deep Neural Networks
• +۲ مورد دیگر

Noorbakhsh Amiri Golilarz is Assistant Research Professor in Computer Science and Engineering at Mississippi State University. His research focuses on artificial intelligence applications in image processing, computer vision, and medical diagnostics. Key research areas include deep neural networks for image denoising, medical image analysis, and cybersecurity for AI systems. Recent work explores adversarial robustness, medical knowledge graphs, and generative model evaluation. Publications demonstrate strong methodological innovations in optimization algorithms and deep learning architectures applied across domains including healthcare, renewable energy, and industrial quality control.

Wilkistar Otienoمشاهده پروفایل

دانشیار

• Predictive Data Analytics for Manufacturing Systems
• Sustainable Manufacturing (Remanufacturing)
• Energy Sustainability
• +۳ مورد دیگر

Wilkistar Otieno is an Associate Professor in the Department of Industrial & Manufacturing Engineering at the University of Wisconsin-Milwaukee (UWM). He serves as Co-Director of the UWM Industrial Assessment Center (IAC) and Director of the NSF/S-STEM program aimed at preparing engineers and computer scientists. His research focuses on predictive data analytics for manufacturing systems, sustainable manufacturing (remanufacturing), energy sustainability, reliability analysis, and engineering education. He holds a PhD in Industrial Engineering from the University of South Florida (2010), alongside MS degrees in Statistics (2007) and Industrial Engineering (2006) from the same institution, and a BS in Production and Mechanical Engineering from Moi University, Kenya (2002). Education: PhD, Industrial Engineering, University of South Florida, 2010 MS, Statistics, University of South Florida, 2007 MS, Industrial Engineering, University of South Florida, 2006 BS, Production and Mechanical Engineering, Moi University, Kenya, 2002 His research emphasizes sustainable manufacturing practices, including remanufacturing strategies and energy efficiency. He has received notable awards such as the 2023 Engineer of the Year Award and the 2022 BizTimes Outstanding Women of Color in Education Award. His work bridges academia and industry through collaborative projects like the NSF/S-STEM program and the Industrial Assessment Center, which assists companies in optimizing energy use and manufacturing processes. Key trends in his publications include leveraging data analytics for defect prediction in electronics manufacturing, optimizing remanufacturing policies, and applying fuzzy logic systems to evaluate technical and economic feasibility of sustainable practices. His contributions to engineering education focus on integrating industry-relevant concepts like connected enterprise frameworks into curricula. Awards: Engineer of the Year Award (2023) Notable Woman in Engineering (2022) BizTimes Outstanding Women of Color in Education Award (2022) UW-System As a mentor, he leads the NSF/LSAMP Wisconsin Alliance for Minority Participation. He is currently on sabbatical for the Fall 2024 and Spring 2025 semesters.

• Electrical Engineering Education
• Fuzzy Logic Systems
• Power Systems Analysis
• +۳ مورد دیگر

Cristina Vatavu is a Lecturer in the Department of Electrical Engineering at Gheorghe Asachi Technical University of Iași's Faculty of Electrical Engineering. Her research spans electrical engineering education innovations, fuzzy logic systems, power analysis, and signal processing. She actively participates in student scientific communications sessions and coordinates competitions in theoretical electrical engineering applications. Research interests focus on pedagogical improvements through simulation tools (OrCAD), nonlinear device analysis, and practical training methodologies. Publications demonstrate strong emphasis on optimizing educational approaches and control systems through fuzzy logic algorithms. Articles reveal consistent focus on engineering education enhancement (2018-2019), alongside deeper technical work in fuzzy logic applications (2002-2005) and signal/power analysis (2005-2016).

Yuchu Qinمشاهده پروفایل

مدرس ارشد

• Design for Additive Manufacturing
• Intelligent Manufacturing
• Knowledge Representation and Reasoning
• +۷ مورد دیگر

Dr. Yuchu Qin serves as a Senior Lecturer (Equivalent) in the School of Computing and Engineering and Senior Research Fellow with the EPSRC Future Advanced Metrology Hub for Sustainable Manufacturing at the University of Huddersfield. With dual PhD qualifications in Instrument Science and Technology and Mechanical Engineering, Dr. Qin bridges mechanical engineering and computer science disciplines to advance research in additive manufacturing and intelligent systems. Dr. Qin's research spans design for additive manufacturing, intelligent manufacturing systems, knowledge representation, and decision analysis, with particular expertise in fuzzy sets, optimization techniques, and category theory applications. Recent work demonstrates strong integration of AI methodologies with traditional manufacturing processes, creating innovative solutions for quality control and process optimization in additive manufacturing. Publications over the past three years reveal a clear trajectory toward AI-enhanced manufacturing solutions, with emphasis on surface characterization, process parameter optimization, and knowledge representation. The research combines deep theoretical foundations with practical manufacturing applications, addressing critical challenges in additive manufacturing quality and efficiency. Research Degree Scholarship in Engineering (2017) National Scholarship for Doctoral Students (2015) National Scholarship for Master's Students (2012) National Scholarship for Undergraduate Students (2008) As Principal Investigator for a Royal Society International Exchanges Grant and core researcher for major EPSRC funding totaling over £23 million, Dr. Qin actively supervises three PhD students while serving as reviewer for over 70 journals and holding editorial positions with multiple publications. Dr. Qin's teaching includes professional development courses and data mining instruction for both undergraduate and postgraduate students. Research activities center around the EPSRC Future Advanced Metrology Hub, where Dr. Qin contributes to developing next-generation metrology solutions for sustainable manufacturing through both theoretical advancements and practical implementations that address real-world manufacturing challenges.

Chin-Tser Huangمشاهده پروفایل

استاد

• Network Security
• Wireless Network Security
• Network Protocol Design
• +۲ مورد دیگر

Chin-Tser Huang is a Professor in the Department of Computer Science and Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing. He holds a PhD and MS from the University of Texas at Austin and a BS from National Taiwan University. His research focuses on network security, wireless network security, intrusion detection systems, and distributed network protocols. Current projects investigate adaptive channel switching for vehicular networks under harsh weather conditions using machine learning and fuzzy logic systems, as well as blockchain applications for secure authentication and e-voting. Recent publications demonstrate cross-disciplinary approaches to telecommunications security, integrating weather modeling, reinforcement learning, and cryptographic systems for next-generation networks.

John Groegerمشاهده پروفایل

استاد

• Sleep Science
• Cognitive Psychology
• Human Factors
• +۴ مورد دیگر

John Groeger is a Professor of Psychology in the School of Social Sciences at Nottingham Trent University (NTU), appointed in June 2017. His roles encompass research leadership, management of Human Tissue work in Psychology, and direction of NTU's SleepWellScience sleep assessment service for trauma recovery. He actively teaches the final-year Psychology of Sleep module (PSY31010) and supervises undergraduate/postgraduate research. A Chartered Psychologist and Fellow of the British Psychological Society, Groeger's academic journey includes professorial appointments at University of Surrey (1995-2008), University College Cork (2008-12, also Head of School), and University of Hull (2012-2017). His educational background features a PhD from Queen's University Belfast (1984) and prior work at the MRC Applied Psychology Unit in Cambridge. His research centers on sleep-cognition interactions, investigating protective factors (sleep, aptitude, pharmaceuticals) and performance challenges (sleep loss, circadian disruption, brain injury) with real-world applications in driving, work, and daily activities. Recent work emphasizes disease-sleep bidirectional relationships, shift-work safety, and the neurological underpinnings of cognitive performance. His 80+ peer-reviewed publications and two books span sleep measurement, transport psychology, and neuropsychological assessment. Current research trends show strong interdisciplinary focus on sleep-health connections across populations—from sexual minorities to children—with growing emphasis on environmental impacts (air pollution, socioeconomic factors) and biological mechanisms. Recent publications integrate microbiome studies, circadian genetics, and large-scale epidemiological analyses from UK Biobank. Fellow of the British Psychological Society Former honorary General Secretary of the British Psychological Society President of Traffic & Transport Division, International Association of Applied Psychology Groeger provides expert consultation for Amazon, Continental AG, Manchester United FC, and others on sleep-performance relationships, while serving as an expert witness in transport accident cases involving fatigue and distraction. His SleepWellScience service bridges research and clinical applications for trauma recovery. He leads multidisciplinary teams exploring the biological bases of cognitive performance, with current projects examining gut-brain axis effects on sleep, circadian mechanisms in neurodevelopmental disorders, and socioeconomic determinants of sleep health across the lifespan.

Timothy C. Havensمشاهده پروفایل

استاد

• Machine Learning
• Signal Processing
• Sensor Fusion
• +۷ مورد دیگر

Timothy C. Havens is the William and Gloria Jackson Professor in Electrical and Computer Engineering and Computer Science at Michigan Tech University. He serves as Director of the Great Lakes Research Center and Institute of Computing and Cybersystems, overseeing multidisciplinary research in autonomous systems, environmental monitoring, and AI. He also directs the PRIME Lab, focusing on pattern recognition and machine learning. Havens holds a Ph.D. in Electrical and Computer Engineering from the University of Missouri (2010), advised by Jim Keller. His postdoctoral training included an NSF/CRA Computing Innovation Fellowship at Michigan State University under Anil Jain. He has taught extensively at Michigan Tech, including courses like Machine Learning (EE/CS5841), Data Mining (CS4821), and Signals and Systems (ECE3830). His research spans sensor fusion, underwater imaging, autonomous robotics, and explainable AI. Notable projects include reconstructing Great Lakes temperature data via deep learning, developing robust ROS-based autonomous systems, and advancing fuzzy integral techniques for interpretable machine learning. He emphasizes practical applications in environmental science, transportation safety, and defense technology. Havens' work has produced over 150 refereed publications and numerous patents. He prioritizes student training in LaTeX, programming, and publication practices, requiring all advisees to master these tools. His lab collaborates with industry and government agencies on projects involving sensor networks, underwater robotics, and AI security.