Find Academic Supervisors

Nathir RawashdehView profile

Assistant Professor

• Image Processing
• Autonomous Vehicles Perception
• Mobile Robot Applications
• +7 more

Nathir Rawashdeh is an Assistant Professor in the Department of Applied Computing at Michigan Technological University , with an affiliated appointment in Electrical and Computer Engineering . He is a Senior Member of the IEEE and a member of the Institute of Computing and Cybersystems (ICC) and Great Lakes Research Center . Education: Ph.D., Electrical Engineering, University of Kentucky, 2007 MS, Electrical and Computer Engineering, University of Massachusetts, Amherst, 2003 BS, Electrical Engineering, University of Kentucky, 2000 Dr. Rawashdeh's research focuses on unmanned vehicle perception , image analysis , control systems , and mechatronics , with applications in autonomous driving, winter weather adaptation, and industrial automation. His work includes sensor fusion, deep learning, and AI-enhanced manufacturing solutions. Recent publications highlight advancements in winter weather autonomous driving , UV disinfection robotics , and AI-driven industrial inspection systems . His research spans mechatronics curriculum development, industry 4.0 integration, and cross-cultural educational initiatives. Scientific Awards: Senior Member of the IEEE Dr. Rawashdeh has secured over $2 million in funding from organizations including the NSF , Ford Motor Co. , NIST , and the European Commission . His grants support projects like GPU clusters for research, winter weather autonomous driving standards, and UV sterilization robotics. He leads the Mobile Robotics Lab at Michigan Tech, focusing on collaboration and innovation in autonomous systems and mechatronics research.

Furat Al-ObaidyView profile

Lecturer

• Machine Learning
• Intelligent Systems
• VLSI Circuits
• +7 more

Furat Al-Obaidy is a Lecturer in the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn's College of Engineering and Computer Science. His expertise spans machine learning, intelligent systems, VLSI circuits, multi-core systems, FPGA architecture, and deep learning applications. PhD in Electrical & Computer Engineering from Ryerson University (2021) MSc in Electrical & Computer Engineering from Ryerson University (2016) MSc in Control & Instrumentation Engineering from University of Technology, Baghdad (1999) BSc in Control & Systems Engineering from University of Technology, Baghdad (1996) His research focuses on power-aware computing systems, thermal imaging for IC testing, hybrid cache architectures, and AI-driven network optimization. He has published extensively on topics including GPGPU power management, 3D NoC routing, and wireless sensor networks. His recent publications highlight applications of neural networks in cache optimization, FPGA architecture, and thermal imaging for hardware diagnostics. Earlier work includes control system simulations for wind turbines and power factor analysis in electrical circuits. Ryerson Graduate Development Award (2021) Ontario Graduate Scholarship Award (OGS) (2020) Ryerson Graduate Fellowship (2018) Graduate Research Excellence Award (2017) Queen Elizabeth II Graduate Scholarship in Science and Technology (2017)

Raif BAYIRView profile

Professor

• Robotics
• Hybrid and Electric Vehicles
• Artificial Intelligence
• +3 more

Prof. Dr. Raif Bayır is a Turkish academic at Karabük University's College of Engineering, Department of Mechatronics Engineering. With a career spanning 2000-2024, he has held continuous full-time faculty positions from Assistant Professor to Professor. His research focuses on Robotics, Hybrid/Electric Vehicles, and Artificial Intelligence. Doctorate: Gazi University (2005) - Electronics & Computer Education Postgraduate: Gazi University (1998) - Electronics & Computer Education Undergraduate: Gazi University (1995) - Electronics & Computer Education His work integrates Artificial Intelligence techniques into Electric Vehicle systems, Robotics, and Agricultural Engineering applications. Recent publications emphasize Deep Learning for Mask Detection, Real-Time Battery Monitoring, and Autonomous Navigation Systems. Scientific awards include: 2017 METU Line-Following Robot 1st Prize 2016 TÜBİTAK Domestic Product Award 2015 TÜBİTAK Electromobil Best Design Prize He has advised over 20 graduate theses on topics spanning Electric Vehicle Components, Beehive Monitoring Systems, and Intelligent Control Applications. His research teams have developed multiple TÜBİTAK-supported projects including Automotive Test Stands and Battery Management Systems.

Janine ReichenbachView profile

Professor

• Somatic Gene Therapy
• Primary Immunodeficiencies
• Hematopoietic Stem Cell Research
• +4 more

Prof. Dr. med. Janine Reichenbach is a full professor and head of the Somatic Gene Therapy department at the University of Zurich, affiliated with the University Children's Hospital Zurich. She holds dual board certifications in Pediatrics and Adolescent Medicine (Germany/Switzerland) and Allergology & Clinical Immunology (Switzerland). Her career spans over two decades of translational research bridging basic science and clinical implementation of gene therapies. Education: MD from Goethe University Frankfurt (1995-1997), medical training in Germany (1997-2000), and specialist certifications in Switzerland (2005-2009). Research Focus: Translational development of hematopoietic stem cell-based gene therapies for primary immunodeficiencies, particularly chronic granulomatous disease (CGD) and ataxia telangiectasia (A-T). Key projects include lentiviral vector design, genome editing at ATM locus, and myeloid-targeted therapies with brain-crossing potential. Awards: Recipient of the 2010 Walther und Gertrud Siegenthaler Stiftung prize. Grants: Leads Swiss National Science Foundation projects, University Research Priority Programs (URPP Itinerare), Clinical Research Priority Programs (CRPP ImmuGene), and Wyss Centre collaborations. Leadership: Principal investigator in EU-FP7 projects CELL-PID and NET4CGD, steering committee member for SCID newborn screening, and co-founder of international research networks.

Rabah AoufiView profile

Senior Lecturer

• Digital Signal Processing
• Microcontroller Systems
• Control Systems
• +3 more

Rabah Aoufi is a Senior Lecturer in the Department of Engineering Technology & Industrial Distribution at the College of Engineering, Texas A&M University. His primary affiliation includes the Electronic Systems Engineering Technology program. He can be reached at raoufi@tamu.edu and is located in FERM 304AA. His work focuses on digital signal processing, microcontroller systems, control systems, and engineering entrepreneurship. Research interests span embedded systems design, real-time data processing, and innovative educational projects. His publications reflect expertise in both foundational engineering principles (e.g., signal processing fundamentals) and applied technologies (e.g., microcontroller programming and big data frameworks). His articles demonstrate a career-long engagement with evolving technologies—from foundational 1980s multiprocessor architectures to modern big data systems. No scientific awards or grants are explicitly mentioned in the provided materials.

Palanichamy NaveenView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Deep Learning
• +7 more

Dr. Palanichamy Naveen is an Assistant Professor in the Department of Electronics and Communication Engineering at Dr. N.G.P. Institute of Technology, India. His research lies at the intersection of computer vision, machine learning, and signal processing, with applications in healthcare, control systems, and academic policy. He actively collaborates with researchers globally, including institutions in the Czech Republic, and has contributed over 60 publications to academic literature. His research interests span Computer Vision , Deep Learning , Image and Video Processing , Signal Processing , and Optimization Algorithms . He also explores interdisciplinary topics such as academic performance appraisal and sports analytics. His work reflects a strong commitment to both technical innovation and institutional improvement in engineering education. The recent trend in his publications demonstrates a dual focus: applying AI to solve real-world problems in medical imaging and industrial control, while also contributing to academic governance through models for faculty evaluation and research incentivization. This blend of technical and administrative research highlights his broad impact in engineering academia. Scientific Contributions: Developed lightweight transformer models for retinal disease detection from OCT scans Proposed novel bio-inspired optimization algorithms for PID controller tuning Designed frameworks for faculty performance appraisal and research contribution assessment Created a relative grading system for ODI cricket player rankings Dr. Naveen is actively involved in academic discourse and knowledge dissemination through preprint platforms and peer-reviewed journals. While no formal advising or grant information is available in the text, his extensive publication record and international collaborations suggest active mentorship and research leadership. He is also engaged with academic networks like SciProfiles and Multidisciplinary Digital Publishing Institute, contributing to the broader scholarly ecosystem.

• Electrical Machines and Energy Conversion
• Control Theory and Applications
• Artificial Intelligence
• +3 more

Hilmi AYGÜN is an Assistant Professor in the Department of Mechatronics Engineering at Karabük University's Faculty of Engineering and Natural Sciences, where he has been serving since 2019. His academic career began as a Research Assistant in the Electrical and Electronics Engineering Department from 2009-2019 before transitioning to his current position in Mechatronics Engineering. He also serves as the Erasmus Coordinator for both the Mechatronics Engineering Department and the university since 2021. Education: PhD in Electrical and Electronics Engineering (2011-2019), Karabük University, Institute of Science MSc in Electrical and Electronics Engineering (2010-2011), Karabük University, Institute of Science BSc in Electrical and Electronics Engineering (2003-2007), Kırıkkale University, Faculty of Engineering Hilmi AYGÜN's research primarily focuses on electrical machines and energy conversion systems, with particular emphasis on motor control algorithms for electric vehicle applications. His work integrates control theory with artificial intelligence techniques, especially optimization algorithms like Particle Swarm Optimization (PSO) and the Yusufcuk Algorithm. He has made significant contributions to field-oriented control of induction motors, DC motor control systems, and wind energy applications. His publication record shows a clear trajectory toward increasingly sophisticated control systems for electromechanical applications, with recent work focusing on metaheuristic methods for motor control, optimization of wind energy systems, and advanced DC motor control techniques. His research bridges theoretical control concepts with practical engineering applications, particularly in transportation and renewable energy sectors. Hilmi AYGÜN has successfully advised at least one Master's student, Hersh Hasan Taha Al Dawoodı, whose thesis focused on field-oriented control of induction motors using metaheuristic methods. He has participated in two major research projects: one on optimal flux reference direct torque control for asynchronous motors used in electric vehicles (2015-2019), and another on controlling bed temperature in fluidized bed boilers using PSO-PID controllers (2011-2013). As an educator, he has taught numerous courses including Electric Machine Dynamics, Modeling and Control of Biomedical Systems, Control of Electric Machines, Electric and Hybrid Vehicles, Industrial Automation, and various electronics courses. His teaching spans both undergraduate and graduate levels, demonstrating his versatility across multiple engineering disciplines within the mechatronics field.

• Robotics
• Autonomous System Design
• Control Theory and Applications
• +3 more

Abdurrahman Yılmaz is an Assistant Professor at Istanbul Technical University's Department of Control and Automation Engineering within the College of Electrical-Electronics. His career spans academic and industrial roles, including a Research Assistant position at Istanbul Technical University (2018-2022) and Test Rig Design Engineer at ASELSAN INC. (2014). Education: PhD in Control and Automation Engineering (Istanbul Technical University, 2014-2022) MSc in Mechatronics Engineering (Yildiz Technical University, 2014-2017) BSc in Electronics Engineering (Istanbul Technical University, 2009-2014) Double Major in Control and Automation Engineering (Istanbul Technical University, 2011-2014) Research Interests focus on Robotics, Autonomous System Design, and Control Theory. His work includes localization frameworks for autonomous mobile robots, adaptive control algorithms for quadcopters, and soft haptic sensing technologies. Recent research explores digital twin simulators and quadruped robot dynamics. Scientific Output trends highlight advancements in mobile robot navigation, industrial automation, and autonomous systems. Publications span journals like Journal of Field Robotics and conferences including TAROS and RoboSoft. Awards: The Most Successful Doctoral Thesis Award of 2022 (University, 2023) 1st Water Management Awards (Ministry of Forestry and Water Affairs, 2019) Collaborations extend to international researchers in robotics and control systems. He serves as PI for the project "Development of a Design-Aiding Analysis Tool for Four-Legged Robots" (2023-2024).

Mike WagnerView profile

Professor

• Renewable Energy Systems
• Energy Storage Optimization
• Thermal Systems Modeling
• +3 more

Mike Wagner is a Professor of Mechanical Engineering at the University of Wisconsin-Madison. He leads the Energy Systems Operations Lab and is affiliated with the Solar Energy Lab and Wisconsin Electric Machines and Power Electronics Consortium. His research focuses on thermal systems modeling, energy storage optimization, and high-temperature power generation technologies. Dr. Wagner holds a B.S. and M.S. from the University of Wisconsin-Madison (2007, 2008) and a Ph.D. from Colorado School of Mines (2017). Prior to UW-Madison, he spent 11 years as a senior researcher and PI at NREL’s Thermal Systems group. His research spans renewable energy systems, battery testing, and hybrid generation technologies. Recent work includes nuclear-solar integration, molten salt thermal storage, and AI-driven control systems for power plants. Awards: PECASE (2019), NREL President’s Award (2019), and multiple NREL recognition awards. He teaches courses in heat transfer (ME 364), graduate research (ME 790/890), and nuclear engineering (NE 790). His lab develops tools like SRLIFE, SolarPILOT, and SAM for energy system modeling and optimization.

Timothy DrysdaleView profile

Professor

• Remote Laboratories
• Engineering Education
• Electromagnetics
• +2 more

Timothy Drysdale is Professor and Chair in Technology Enhanced Science Education at the University of Edinburgh, where he directs the Remote Laboratories group and serves as Director of Strategic Digital Education. His practable.io platform revolutionizes laboratory education through aesthetically-designed remote experiments installed in campus foyers, saving physical space while enhancing accessibility. Research develops novel remote labs based on experiments likened to "science museum exhibits," integrating real-time equipment access via web interfaces. Additional work explores orbital angular momentum in radio communications. His £3M openEngineering Laboratory project received multiple honors including the Queen's Anniversary Prize and THE Digital Innovation Award. Global Online Laboratories Consortium Award (2024, 2018) Queen's Anniversary Prize (2024) Jisc Digital Transformation Award (2023) Guardian Teaching Excellence Award (2018) Teaches across undergraduate engineering programs and supervises doctoral projects in digital education innovation. Advocates for assessment transformation and generative AI integration in education.

Niko NevarantaView profile

Associate Professor

• Electrical and Electronic Engineering
• Control and Systems Engineering
• Modelling and Simulation
• +6 more

Niko Nevaranta serves as an Associate Professor (Tenure Track) in the Department of Electrical Engineering at Lappeenranta-Lahti University of Technology (LUT), specifically within the School of Energy Systems. His academic journey began at LUT where he earned his B.Sc. (2010), M.Sc. (2011), and D.Sc. (2016) degrees in electrical engineering. His career path includes a visiting researcher position at KTH Royal Institute of Technology in Stockholm (2018) and a post-doctoral researcher role funded by the Academy of Finland (2019-2022). Nevaranta's research focuses on data-driven modeling and control systems for electromechanical and energy applications. His primary expertise lies in Industrial Informatics for Energy System Disruption, with specific interests in high-speed rotating machinery, system identification, parameter estimation, and intelligent control systems. His work bridges theoretical control engineering with practical industrial applications, particularly in the energy transition sector. Analysis of his recent publications reveals a strong emphasis on active magnetic bearing technology, rotor dynamics, and high-speed machinery applications. His research increasingly incorporates data-driven approaches and machine learning techniques to address complex control challenges in energy systems. The publications demonstrate a clear progression from fundamental control theory toward practical implementation in real-world energy conversion systems. As an educator, Nevaranta has developed innovative teaching materials for control engineering, including MATLAB-based tools and virtual learning environments. His educational contributions focus on making complex control concepts accessible to undergraduate students through interactive and visual learning approaches. Nevaranta works within the laboratory of Control Engineering and Digital Systems at LUT, where he leads research on advanced control methodologies for energy systems. His current projects involve high-speed machine technology, particularly in applications related to biomass and waste heat recovery, as well as emerging technologies in direct air capture systems.

Pouria SarhadiView profile

Senior Lecturer

• Control Theory
• Autonomous Vehicles
• Adaptive Control
• +3 more

Pouria Sarhadi is a Senior Lecturer at the University of Hertfordshire's School of Physics, Engineering & Computer Science. He has held roles as a Research Fellow at Queen's University Belfast (2021-2022) and the University of Surrey (2019-2021), and served as an Adjunct Professor at Babol Noshirvani University of Technology (2016-2018). He is a Chartered Engineer (CEng), Member of the IET, and recognized as UK 'Global Talent' by UKRI. His research focuses on control theory applications, adaptive control, autonomous vehicles, and systems engineering. He has contributed to over 50 peer-reviewed publications and led projects such as HertsLynx CAM On-Demand (UKRI-funded). He is actively involved in editorial roles for Applied Ocean Research and advises on IFAC Technical Committees. Research interests include: Autonomous systems (ground, marine, aerial) Machine learning in control systems Adaptive control and system identification Autonomous vehicle safety and navigation Key awards include CEng, MIET, and UK Global Talent recognition. He has advised on UKRI and Horizon Europe projects and consults for industries. Current projects include hybrid navigation safety simulators and cooperative control of multi-AUV systems.

Amin HajizadehView profile

Associate Professor

• Renewable Energy Systems
• DC Microgrids
• Offshore Renewable Energy
• +6 more

Amin Hajizadeh is an Associate Professor at Aalborg University (AAU), affiliated with the Esbjerg Energy Section in the Faculty of Engineering and Science . His research focuses on renewable energy systems, DC microgrids, offshore renewable energy integration, and AI-driven energy solutions. He holds a PhD in Electrical Power Engineering (2010). Research Highlights: Developing control strategies for modular multiport DC-DC converters and offshore wind-hydrogen systems Advancing energy management in net-zero buildings and smart city frameworks Pioneering work in AI-based wake steering for wind farm optimization Projects & Awards: Lead investigator in BlueBARGE (€5M EU project on renewable bunkering for anchored ships) Recipient of the 2024 Best Paper Award for work on neural network-based wake steering Key Contributions: Published 140+ papers in journals like IEEE Transactions and Renewable Energy Supervised 6 PhD students and contributed to 19 funded research projects Active in editorial roles (e.g., IET Renewable Power Generation)

• AI and Robotics
• Human-Robot Interaction (HRI)
• Autonomous Agents
• +7 more

Dr. Abolfazl Zaraki is a Senior Lecturer in AI and Robotics at the University of Hertfordshire's Department of Computer Science, part of the School of Physics, Engineering & Computer Science. He leads the Robotics Research Group and previously held roles at Cardiff University's School of Engineering and the IROHMS Research Centre. His academic journey includes a Master's in Mechatronics from University Technology Malaysia (2010) and a PhD in Automatic Robotic and Bioengineering from the University of Pisa (2014). He has held Research Fellow positions in Italy and the UK until 2019. Dr. Zaraki's research focuses on AI-driven autonomous systems, social robotics, and assistive technologies. Key projects include the EASEL, BabyRobot, and JAMES EU initiatives, alongside the Innovate UK-funded InSight project. His work emphasizes Human-Robot Interaction (HRI), trusted autonomy, and applications in healthcare and industrial contexts. Notable contributions include the development of the Kaspar humanoid robot for autism therapy and advancements in reinforcement learning for robotic control. His recent publications (2021–2025) explore agentic AI, memory-driven systems, and personalized LLMs for HRI, alongside technical advancements in robotic control, communication systems, and bio-inspired robotics. His research bridges theoretical AI innovation with practical applications in healthcare, education, and industrial automation. Zaraki has collaborated internationally across institutions and industry partners, contributing to 35+ research outputs. His work aligns with global trends in ethical AI, explainable systems, and human-centric robotics design.

Josep Ribes BertomeuView profile

Associate Professor

• Wastewater Treatment
• Anaerobic Membrane Bioreactors (AnMBR)
• Mathematical Modeling of Bioprocesses
• +7 more

Josep Ribes Bertomeu is an Associate Professor in the Department of Chemical Engineering at the University of Valencia, Spain, within the School of Engineering. He is a key member of the CALAGUA-UV Research Group on Environmental Technologies, where he has conducted extensive research since 1999. His research focuses on wastewater treatment , particularly using anaerobic membrane bioreactors (AnMBR) , mathematical modeling , process control , and optimization through artificial intelligence. He has made significant contributions to the development of simulation tools such as DESASS and LoDif-BioControl, and has worked on parameter calibration and control algorithms for wastewater treatment plants (WWTPs). His recent publications demonstrate a strong trend in energy recovery , resource valorization , and sustainable water management , aligning with circular economy principles. He has also been active in chemical engineering education , innovating laboratory teaching and virtual learning strategies. Principal Researcher, LIFE MEMORY Project (University of Valencia) Supervised 3 PhD theses Published over 35 international journal papers Co-author of 3 registered software programs and 5 invention patents He has contributed to numerous applied research and technology transfer projects with public and private entities, emphasizing real-world impact.