Find Academic Supervisors

• Combustion Modeling
• Fluid Power
• Internal Combustion Engines
• +3 more

Roberto Finesso is an Associate Professor at the Department of Energy (DENERG) at Politecnico di Torino, Italy. He is a member of the College of Mechanical, Aerospace and Automotive Engineering and contributes to the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His research focuses on combustion modeling and control in diesel engines, fluid power systems, and optimization of hybrid electric vehicle layouts and control strategies. Scientific Disciplinary Sector: IIND-06/A - Fluid Machinery ERC Sectors: PE8_5 - Fluid Mechanics, Hydraulic-, Turbo-, and Piston-Engines SDG Goals: 4 (Quality Education), 9 (Industry, Innovation, and Infrastructure), 12 (Responsible Consumption and Production) His work spans combustion diagnostics , NOx and PM emission control , hybrid powertrain optimization , and machine learning for engine calibration . He employs 3D-CFD (Fluent) and 0D (Amesim) techniques for hydraulic component modeling and develops real-time control algorithms for diesel engines. His research also includes model-based calibration , pressure-based combustion control , and predictive tools for emission analysis . Recent research trends focus on integrating physics-based , semi-empirical , and neural network models for combustion control. He has pioneered techniques for offline and real-time EGR optimization , MFB50 control , and IMEP management in diesel engines. His studies address both light-duty and heavy-duty applications, emphasizing CO2 minimization and cost efficiency in hybrid vehicles. Scientific Awards: SAE Excellence in Oral Presentation Award (2013) Teaching Contributions: Course Instructor for Fundamentals of Fluid Machinery and Fundamentals of Thermal and Hydraulic Machines and Fluid Power (Mechanical Engineering, 2019–2025) Course Collaborator for Automotive Fluid Power Systems (Automotive Engineering, 2019–2025) Research Groups: FPRL Research Group (DENERG)

• Hydrodynamics
• Mooring systems
• System identification
• +6 more

Bruno Paduano serves as a Fixed-term Assistant Professor at the Department of Mechanical and Aerospace Engineering (DIMEAS) at Polytechnic University of Turin. He is an active member of the College of Mechanical, Aerospace and Automotive Engineering and an invited member of the College of Electrical and Energy Engineering. His academic position operates under Italian Law 240/10 art.24-a with research and teaching responsibilities spanning multiple degree programs. Dr. Paduano's research focuses on hydrodynamics, mooring systems, system identification, and wave energy conversion. His scientific work falls under the disciplinary sector IIND-02/A - Mechanics applied to machines within Area 0009 - Industrial and information engineering. His research aligns with ERC sectors PE7_1 (Control engineering), PE6_12 (Scientific computing), PE7_7 (Signal processing), and PE7_3 (Simulation engineering and modelling). His work directly contributes to UN Sustainable Development Goals 7 (Affordable and clean energy), 11 (Sustainable cities), 13 (Climate action), and 14 (Life below water). His recent publications demonstrate a strong focus on experimental validation of numerical models for floating offshore wind and wave energy systems. The research trends show particular emphasis on high-fidelity modeling of mooring systems, system identification techniques for marine renewable energy converters, and control strategies for maximizing energy capture from ocean resources. His work bridges theoretical modeling with practical experimental validation through scaled model testing. Dr. Paduano actively supervises PhD students Anna Ceni (40th cycle, Mechanical Engineering) and Lorenzo Dutto (39th cycle, Mechanical Engineering). He participates in the FLOWAM HI-FI Project for numerical modeling of floating wind farms (2024) as a research group member. His teaching portfolio spans PhD, Master's, and Bachelor's programs, with courses focused on numerical modeling and experimental validation of wave and floating wind energy converters. He is affiliated with the Mechatronics and Servo Systems research group within DIMEAS. His current teaching assignments include Numerical Modeling and Experimental Validation of Wave and Offshore Wind Energy Converters (2025/26 PhD program), Wind and Ocean Energy Plants (Master's level), and specialized courses on The Sea and the Green Transition across multiple engineering disciplines.

Philip MarmetView profile

Researcher

• Multiphysics Simulation
• Multiscale Modeling
• Microstructure Characterization
• +5 more

Dr. Philip Marmet is a Researcher and Lecturer at the Institute of Computational Physics (ICP) within the School of Engineering at Zurich University of Applied Sciences (ZHAW). His work focuses on Multiphysics and Multiscale simulations, characterization and stochastic modeling of microstructures, with particular expertise in solid oxide fuel cell electrode design. His educational background includes a PhD in Physics/Modeling and Simulation from the University of Fribourg (2019-2023), an MSc in Physics/Soft Matter Theory from the same institution (2013-2016), and an MSc in Engineering from Bern University of Applied Sciences (2011-2013). PhD in Physics / Modeling and Simulation, Solid Oxide Fuel Cells, University of Fribourg (2019-2023) MSc in Physics / Soft Matter Theory, University of Fribourg (2013-2016) MSc in Engineering BFH / Industrial Technologies, Bern University of Applied Sciences (2011-2013) BSc in Mechanical Engineering / Mechatronics, Bern University of Applied Sciences (2003-2007) Dr. Marmet's research spans Multiphysics Simulation, Multiscale Modeling, Microstructure Characterization, and Digital Materials Design. His work bridges theoretical modeling with experimental validation to optimize materials for energy applications. He has developed specialized methodologies for virtual microstructure variation and optimization of porous materials, particularly for solid oxide fuel cells and aerosol filters. His publication record shows a clear progression toward increasingly sophisticated multiscale modeling approaches, with recent work focusing on stochastic microstructure modeling using pluri-Gaussian methods. His research demonstrates strong integration of computational techniques (including GeoDict, Comsol Multiphysics, ANSYS, OpenFOAM, and Matlab/Simulink) with experimental validation. Best graduation results of 2013 "Gold", Master of Science in Engineering Dr. Marmet supervises student projects and lectures Analysis 1 and 2 for bachelor courses. His research has received funding from the Swiss Federal Office of Energy (SFOE) and Eurostars program. He has developed practical software tools including the Python app for stochastic microstructure modeling of SOC electrodes and the Characterization-app for standardized microstructure analysis, demonstrating his commitment to translating research into practical engineering solutions. His work is organized around the Digital Materials Design workflow, connecting virtual microstructure generation, automated characterization, and multiphysics simulation to enable data-driven optimization of energy materials without extensive experimental iteration.

• Heavy Ion Collision
• Nuclear Physics at High Density
• Nuclear Symmetry Energy
• +3 more

Dr. Yongsun Kim is a Professor at the Department of Physics and Astronomy , Sejong University. Holding a Ph.D. from MIT (2013) and a B.S. from the University of Illinois Urbana-Champaign (2007), he conducted postdoctoral research at Korea University (2013-2017) and UIUC (2017-2018). His work bridges high-energy physics and nuclear structure , focusing on heavy-ion collisions , quark-gluon plasma , and Higgs boson phenomenology . Research Interests Heavy Ion Collisions at LHC/RHIC Nuclear Symmetry Energy in Rare Isotopes High-Density Nuclear Physics Detector Development for sPHENIX and ECCE Scientific Contributions With over 1073 research outputs , his recent publications include measurements of W+W- production, studies of top quark entanglement , and searches for exotic Higgs decays . His work spans CMS detector upgrades, charm hadronization, and QCD investigations . Scientific Awards No specific awards mentioned in the provided data.

Makarov Sergey LvovichView profile

Associate Professor

• Software Engineering
• Artificial Intelligence
• Mobile Development
• +6 more

Sergey Lvovich Makarov serves as an Associate Professor in the Department of Software Engineering within the Faculty of Computer Science at the National Research University Higher School of Economics (HSE), where he has been employed since 2012. With 21 years of scientific and teaching experience, he holds formal academic credentials including a Candidate of Technical Sciences degree (awarded in 2009) from the Moscow State Institute of Electronics and Mathematics, specializing in Automated Design Systems. His research interests span software engineering, artificial intelligence, mobile development, Internet of Things technologies, automatic text processing, and an unusual interdisciplinary focus on fashion informatics where he applies computational methods to analyze symbolic systems in costume design. This dual expertise is reflected in his publications that bridge technical computer science with applications in fashion industry analysis. Makarov's scholarly output demonstrates a consistent trajectory from foundational work in intelligent information processing systems toward increasingly sophisticated applications in mobile development, IoT ecosystems, and fashion data analysis. His recent publications (2018-2023) focus heavily on practical hardware-software integration through Arduino and Raspberry Pi platforms, while maintaining his distinctive research thread analyzing symbolic systems in fashion design through computational methods. Gratitude from HSE University (May 2024) Gratitude from the Department of Software Engineering, HSE (November 2023) Medal 'Recognition - 10 years of successful work' (December 2022) Gratitude from the Faculty of Computer Science, HSE (September 2019) Academic Work Allowance (2014-2018) As an educator, Makarov supervises student research including Potapenko Vladimir Andreevich's 2013 qualification work on CRM system development. He has received multiple Academic Work Allowances recognizing his teaching excellence. His research includes significant grant-funded projects, notably serving as responsible executor for the R&D project 'Intelligent system for searching the Internet for information analogues of text documents' (2010-2011) and participating in research on decision support systems (2012). His scholarly contributions include numerous publications, research grants, and participation in conferences focusing on AI applications and intelligent systems. Makarov maintains active involvement in curriculum development, particularly in mobile application development and IoT technologies, as evidenced by his current teaching assignments for the 2025/2026 academic year which include specialized courses in Android development using both Kotlin and Java, Manufacturing Data Collection and Analytics, and IoT Ecosystems.

• Control engineering
• Robotics
• Machine learning
• +6 more

Felix Kong is a Lecturer at the University of Technology Sydney, Faculty of Engineering and Information Technology. He specializes in control engineering, robotics, and mechatronic systems with a focus on maritime navigation and bio-inspired locomotion. Current affiliation : University of Technology Sydney (Lecturer since 2022) Previous role : Postdoctoral Research Fellow at University of Technology Sydney (2019-2022) Education : PhD from University of Sydney His research spans multiple domains: Maritime robotics : Stochastic ship routing, ocean current estimation, visibility graph optimization Dynamic locomotion : Gait analysis in parrots, bio-inspired vertical climbing robots Control theory : Iterative learning control, contraction analysis, SLAM optimality prediction Recent publications demonstrate a strong trend toward autonomous navigation systems that integrate: Stochastic weather modeling for ship routing 3D ocean flow estimation for underwater gliders Neural network-based SLAM analysis Multi-agent planning frameworks He has received funding from: Australia's Economic Accelerator Innovate Grant (2025-2027) UTS ECR Research Capabilities Initiative (2021-2022) Teaching contributions include course development and instruction for 41099 Fundamentals of Mechatronic Engineering . Peer-review activities extend to major robotics conferences and journals.

Stefan FelderView profile

Associate Professor

• Hydraulic Engineering
• Environmental Fluid Mechanics
• Water Resources Engineering
• +6 more

Associate Professor Stefan Felder is a leading expert in hydraulic engineering and applied fluid mechanics at the School of Civil and Environmental Engineering, University of New South Wales (UNSW) . With a Dipl.-Ing. from RWTH Aachen University and a PhD from the University of Queensland, he established the hydraulic engineering research group at the UNSW Water Research Laboratory in 2014. Internationally recognized for innovations in air-water flow measurement, fish passage solutions, and remote sensing technologies, his work bridges laboratory-scale modeling with field-scale applications. Education: Dipl.-Ing. (2008) RWTH Aachen, PhD (2013) University of Queensland Leadership Roles: Chair of Research Management Group at WRL, Vice-Chair of IAHR Hydraulic Structures Committee Research Focus: Experimental hydraulics, fishway design, climate change impacts on estuarine systems, and advanced instrumentation development. His work pioneers LIDAR applications for flow analysis and air-water probe technologies. Grants & Projects: Chief Investigator on $6.2M+ in grants including NSW fishway installations, Swiss hydrodynamic safety studies, and international collaborations on sustainable hydraulic systems. Scientific Awards: Karl Emil Hilgard Hydraulics Prize (ASCE) 2023 JD Lawson Scholarship (Engineers Australia) 2017 University of Queensland Dean’s Award for PhD Excellence 2013 DTK Travel Grant for Dipl.-Ing. Thesis 2008

Ryan RuvaldView profile

Research Fellow

• Product Development
• Data-Driven Design
• Autonomous Systems
• +6 more

Ryan Ruvald is a Postdoctoral Fellow at Blekinge Institute of Technology (BTH) in the Department of Mechanical Engineering, Karlskrona, Sweden. His academic journey began with a Bachelor of Science in Mechanical Engineering from the California Maritime Academy, where he gained extensive hands-on training on ships and power plants. Prior to academia, he worked in the solar industry building utility-scale solar power plants for First Solar in Phoenix, Arizona, and served in commercial shipping on container ships, tankers, and deep-sea drillships. Bachelor of Science in Mechanical Engineering, California Maritime Academy Master of Science in Mechanical Engineering with emphasis on Sustainable Product Service System Innovation (MSPI program), Blekinge Institute of Technology Ruvald's research centers on product development, with particular focus on developing methods to generate data for data-driven design in scenarios where knowledge about both machine and environment is sparse or non-existent. His current research focuses on addressing the human element in autonomous system design through experiential prototyping platforms developed in partnership with Volvo CE. These platforms simulate user scenarios to guide empathic design of systems and human-machine interactions. His work spans across Knowledge Management, Design Decision Rationale, Artificial Intelligence, Augmented Reality, and Internet of Things, with strong emphasis on Product-Service Systems (PSS) innovation. His publication record reveals a consistent trajectory in PSS design methodologies, with increasing integration of AI and autonomous systems in recent years. Early work focused on prototyping techniques and PSS implementation in construction equipment, while his most recent publications explore AI-driven approaches to predictive maintenance, autonomous equipment behavior comprehension, and data mining through experience prototyping. This evolution demonstrates a clear progression from traditional product-service system design toward intelligent, data-driven approaches that incorporate human factors in autonomous systems. Ruvald collaborates extensively with industry partners, most notably Volvo CE, to develop experiential prototyping platforms that bridge theoretical research with practical applications. His work has significant implications for the construction equipment industry and autonomous vehicle development, focusing on how humans interact with increasingly autonomous systems in real-world environments.

Momen AbayazidView profile

Assistant Professor

• Robotic Image-Guided Needle Insertion
• Motion Compensation Using Machine Learning
• Soft Robotics
• +3 more

Momen Abayazid is an Assistant Professor in the Robotics and Mechatronics group (RaM) at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente. He holds a PhD in Surgical Robotics from the University of Twente and an M.Sc. in Biomedical Engineering from Delft University of Technology. His research focuses on robotic image-guided interventions, soft robotics, and machine learning applications in medical systems. Education: M.Sc. in Biomedical Engineering (Delft University of Technology), PhD in Surgical Robotics (University of Twente) His expertise includes haptic feedback, needle insertion control, and organ motion compensation. Recent projects involve AI-driven medical imaging, soft robotics for rehabilitation, and sensorized medical devices. Collaborations span institutions like Harvard Medical School and Brigham and Women’s Hospital. ResearchGate and Google Scholar profiles highlight his contributions to medical robotics. Scientific Awards: No explicit awards mentioned in the provided text.

• Ambient intelligence
• Human-computer interaction
• Internet of Things
• +5 more

Fulvio Horn is a Full Professor in the Department of Control and Computer Science at the Polytechnic University of Turin, where he serves as Vice-Rector for Education. He holds multiple leadership positions including Coordinator of the Student Contribution and Planning Commission, Coordinator of the Investigative Committee for Teaching Coordination, and member of both the Board of Directors and Academic Senate. He also contributes to the Interdepartmental Center for Service Robotics and the Master's and Continuing Education School. His research spans Ambient Intelligence, Human-Computer Interaction, and Internet of Things, with specific focus on end-user development for smart environments, IoT security, and accessible technology design. He leads the e-Lite research group that develops innovative technologies at the intersection of Human-Computer Interaction, Ubiquitous Computing, and Artificial Intelligence. His ERC sectors include artificial intelligence systems, computer systems, human-computer interaction, and web information systems. Recent publications reveal a strong emphasis on IoT security challenges, end-user programming tools, and visualization techniques. His work addresses critical gaps in smart home security, novice developer experiences, and accessibility. Key contributions include TextCode for programming support, security frameworks for IoT gateways, and conversational interfaces for rule creation. Much of this research involves close collaboration with Luigi De Russis and other colleagues. Professor Horn has served as Editor-in-Chief of the Journal of Reliable Intelligent Environments (2015-2021) and as Director of IT Professional magazine since 2012. He has secured significant funding through EU programs, regional initiatives, and commercial contracts for projects including RESCHIP4EU, AccessCoVE, and EMPATHY. He actively mentors PhD students including Tommaso Calo' (working on AI realization algorithms) and Luca Mannella (focusing on IoT security). His teaching portfolio includes Web Applications, Human-Computer Interaction, and Programming Techniques across multiple engineering programs. He coordinates doctoral colleges in Computer and Systems Engineering at both Turin and Palermo universities. As leader of the ELITE research group (Intelligent and Interactive Systems) in LAB 10, Professor Horn's team develops practical solutions that bridge human needs and technology through intelligent software components. Current projects address sustainability, accessibility, and educational technology, with strong emphasis on open-source development and real-world implementation.

• Geotechnical Engineering
• Discrete Element Method (DEM) modeling
• Granular Material Behavior
• +2 more

Michelle Lee Barry is an Associate Professor in the Department of Civil Engineering at the University of Arkansas College of Engineering. Her research focuses on multi-scale granular material behavior, experimentally validated discrete element method (DEM) models, and applications of geotechnical engineering in historic preservation. Ph.D., Texas A&M University (2013) M.S., Texas A&M University (2009) B.S., Texas A&M University (2008) Barry's research spans geotechnical laboratory testing, numerical modeling, and soil dynamics. She has applied these methodologies to infrastructure assessment (bridge scour, levees, dams) and additive manufacturing processes. Her work integrates experimental validation with computational modeling to address engineering challenges. Recent publications highlight her contributions to geophysical survey techniques, soil resistivity analysis, and DEM calibration for metallic powder simulations. Applications include transportation infrastructure, flood protection, and advanced materials fabrication. Barry teaches undergraduate Soil Mechanics and graduate courses in Numerical Modeling and Soil Dynamics. Her research has been published in journals such as Transportation Geotechnics , Geotechnical Testing Journal , and Granular Matter .

• Optical Physics
• Biophotonics
• Biomedical Engineering
• +7 more

David McGloin is an Adjunct Professor at the University of Technology Sydney, School of Electrical and Data Engineering, where he also serves as Director of Research Programs. He joined UTS in January 2018 after previously holding positions at the University of Dundee, where he was Head of Physics and Associate Dean for Research. His educational background includes an undergraduate degree in Laser Physics and Optoelectronics and a PhD in Laser and Atomic Physics, both from the University of St Andrews. After his PhD, he worked at the UK Defence Science and Technology Laboratory before returning to St. Andrews for postdoctoral work. Professor McGloin's research spans several interconnected areas in optical physics and biophotonics. His work focuses on: Optical manipulation of microscopic particles, especially aerosols Biophotonics and biomedical imaging applications Cell mechanics and microfluidic analysis of cellular properties Advanced imaging techniques including super resolution microscopy and optical coherence tomography Applications in cancer diagnosis, particularly for prostate and bladder cancer His recent publications demonstrate a strong trend toward developing novel optical techniques with practical applications in biomedical engineering and aerosol science. Many of his recent papers focus on computational imaging approaches, 3D printed optical components, and the application of optical manipulation techniques to biological systems. Professor McGloin has received significant research funding from organizations including the Royal Society, Engineering and Physical Sciences Research Council, Medical Research Council, and Natural Environment Research Council. His most notable early career achievement was being awarded a Royal Society University Research Fellowship. He supervises HDR students and teaches graduate courses including Technology Research Preparation and Technology Research Methods at UTS. His laboratory work involves optical manipulation, biophotonics, and microfluidics research.

• Socio-economic geography
• Spatial management
• Smart cities
• +3 more

Agnieszka Szczepańska is a full Professor at the University of Warmia and Mazury , affiliated with the Faculty of Geoengineering and the Department of Socio-Economic Geography . Her research focuses on spatial planning, 3D visualization technologies, and socio-economic impacts on urban environments.

• Intelligent systems
• Robotics
• Controls
• +3 more

Dr. Ajay Mahajan is a Professor of Mechanical and Biomedical Engineering at the University of Akron’s College of Engineering and Polymer Science, where he also serves as Associate Dean for Research and Industrial Engagement. Since joining UA in 2009, he has held leadership roles including Special Assistant to the President for Innovation and Associate Vice President for Innovation before returning to full-time faculty duties. Education: Ph.D. in Mechanical Engineering, Tulane University (1994) M.S. in Mechanical Engineering, Tulane University (1992) B.Eng. in Mechanical Engineering, University of Roorkee (1990) Research Interests: Dr. Mahajan’s research integrates intelligent systems, robotics, and biomedical engineering. His work spans the development of smart biomedical devices—such as 3D-printed cochlear models for ENT training and kidney-stone retrieval tools with force feedback—to autonomous robotic platforms for space applications. He also explores data analytics for healthcare decision-making and battery management systems for electric aircraft, reflecting a multidisciplinary approach that bridges mechanical design, control theory, and clinical translation. Scientific Awards: 2008 Honorary Award in Intelligent Systems, Model Identification and Intelligent Systems Technical Committee (MIIS-TC), ASME First Prize, medical category, NASA’s 2007 Create the Future Design Contest for a neuro-navigation system for brain surgery Grants & Collaborations: While specific grant details are not enumerated, Dr. Mahajan’s extensive publication record and leadership roles indicate sustained funding and industrial partnerships, particularly in aerospace, healthcare, and energy storage sectors. Laboratories & Teams: Dr. Mahajan is affiliated with the 3D Printing Lab and contributes to interdisciplinary teams across mechanical and biomedical engineering, fostering innovation in medical simulation, robotics, and data-driven healthcare solutions.

• Automation Systems
• Control Engineering
• Cybersecurity
• +5 more

Tomasz Makowski is a Lecturer at the Department of Infotronics and Cybersecurity within the Faculty of Electrical and Computer Engineering at Cracow University of Technology. His work focuses on automation systems, control engineering, and cybersecurity, with active collaborations in robotics and IoT projects. Current affiliation: Cracow University of Technology Academic rank: Lecturer Research interests include: Automation systems and PLC programming 3D printing and Fusion 360 modeling Robotics and sensor networks Human-machine interfaces (HMI) and RFID technology Recent publications highlight applications in: Electromagnetic launcher control 3D printing integrations Smart greenhouse automation Experimental PID algorithm testing Mobile delivery robotics