جست‌وجوی استاد و پژوهشگر

• Thermal Systems
• Battery and Vehicle Energy Management
• Model Predictive Control
• +۶ مورد دیگر

Professor Peter Fussey holds a dual role at the University of Sussex as a Professor in the School of Engineering and Informatics and Associate Dean for Global and Civic Engagement at the Faculty of Science, Engineering and Medicine. He leads the Energy and Materials Engineering Research Centre, focusing on Thermal Systems , Battery and Vehicle Energy Management , Model Predictive Control , and Data Analytics . Previously, he spent over 25 years at Ricardo UK, leading the Control Department and developing advanced control systems for hybrid/electric vehicles and thermal management. His career also includes rail acoustics research at British Rail Research and SNCF. Education: DPhil in Engineering from the University of Oxford MA in Engineering from the University of Cambridge Research Interests: Professor Fussey’s work spans automotive and mechanical engineering , with a focus on low-emission powertrains , energy management systems , and advanced control algorithms . His recent projects include optimizing EV cabin climate control for extended range, geofencing for smart mobility, and neuro-fuzzy modeling for thermal systems. He has also pioneered applications of model predictive control (MPC) in selective catalytic reduction (SCR) systems and engine combustion optimization. Teaching: Courses include Low Emission Vehicle Propulsion , Vehicle Dynamics , and supervising Formula Student projects. His teaching emphasizes practical applications of control theory and sustainability. Labs/Teams: Leads the Energy and Materials Engineering Research Centre , fostering interdisciplinary research in sustainable energy and advanced propulsion systems.

Frank P.T. Willemsمشاهده پروفایل

استاد

• Control Systems
• Internal Combustion Engines
• After-treatment Systems
• +۵ مورد دیگر

Frank P.T. Willems is Full Professor of Systems and Control Technology and Chair of Integrated Powertrain Control at Eindhoven University of Technology (TU/e). His research focuses on control-oriented modeling of internal combustion engines and after-treatment systems, cylinder pressure-based combustion control, and integrated energy and emission management. He develops optimal and robust control methods for automotive powertrain systems to achieve ultra-efficient and clean combustion concepts. His work enables auto-calibration that optimizes total powertrain efficiency using smart sensors and self-learning control concepts. He is active in the IFAC Technical Committee Automotive Control and serves as Associate Editor for Control Engineering Practice. He has organized symposia on future heavy-duty powertrain control and contributes to the Topsector HTSM roadmap Automotive.

Richard Paigeمشاهده پروفایل

استاد

• Software Engineering
• Model-Driven Engineering
• Safety-Critical Systems
• +۱۰ مورد دیگر

Richard Paige is a Joseph Ip Distinguished Engineering Professor at McMaster University's Department of Computing and Software, Faculty of Engineering. He also holds a part-time position as Professor of Enterprise Systems at the University of York, UK. His primary research focuses on software engineering, particularly model-driven engineering, safety-critical systems, and low-code development. He leads the McMaster Centre for Software Certification (McSCert) and has extensive industry collaborations, including with Rolls-Royce, Leonardo, and NASA. Paige holds a PhD in Computer Science from the University of Toronto (1997), an MSc from the same institution (1994), and a BSc from McMaster University (1992). He has supervised over 22 PhD and 72 Master’s students, many of whom pursue careers in academia and industry. His funding exceeds $24M CAD from NSERC, Ontario Research Fund, and industry grants. His research emphasizes model management, assurance cases, and safety-critical systems. Key contributions include the Epsilon framework and advancements in model-driven tools. Paige chairs the STAF conferences and serves on editorial boards for journals like Software and Systems Modeling . He actively promotes open-source tooling and has won multiple best paper awards, including ACM Distinguished Paper at MoDELS (2010, 2017) and the Ten-Year Most Influential Paper Award (2016). Paige’s teaching focuses on problem-based learning and flipped classrooms, with awards for pedagogical innovation. He also leads interdisciplinary projects, such as SECT-AIR (reducing aerospace software costs) and CROSSMINER (developer-centric knowledge mining). His work bridges academia and industry, addressing challenges in automotive, healthcare, and aerospace sectors. Current projects include safety assurance for autonomous vehicles and model-driven sustainability evaluation.

Mark Lawfordمشاهده پروفایل

استاد

• Software engineering
• Safety critical systems
• Digital & Smart Systems
• +۳ مورد دیگر

Mark Lawford is a Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. His expertise spans software engineering, safety critical systems, and model-based development, with a focus on digital & smart systems and transportation research clusters. Contact: Email: lawford@mcmaster.ca Website: www.cas.mcmaster.ca/~lawford His research explores automotive systems , formal verification , and model-driven engineering , particularly addressing challenges in automotive electrification , centralized E/E architectures , and safety assurance cases . Recent publications emphasize test case generation , change impact analysis , and model transformation tools for Simulink, SysML, and AUTOSAR. Key trends in his work include autonomous vehicle safety , real-time control systems , and integration of formal methods with industrial practices across automotive, biomedical, and nuclear domains.

Chris Braceمشاهده پروفایل

استاد

• Automotive Engineering
• Powertrain Systems
• Internal Combustion Engines
• +۵ مورد دیگر

Chris Brace is a Professor of Automotive Propulsion and Deputy Director of the Powertrain Vehicle Research Centre at the University of Bath. His work focuses on advanced measurement, analysis, and control of multi-cylinder engine systems under dynamic conditions, with extensive collaboration with industry leaders like Ford Motor Company and Jaguar LandRover. He contributes to the United Nations Sustainable Development Goals (SDGs), particularly in sustainable mobility and low-emission propulsion systems. Education : Sandwich degree at University of Bath (1990), PhD (1996). Research interests encompass powertrain systems , internal combustion engines , hybrid electric vehicles , battery technology , and low-emission propulsion . His projects integrate nonlinear control systems, fault-tolerant designs, and data-driven validation architectures. Recent publications highlight advancements in emission control algorithms, adaptive critic networks for rotary engines, fault-tolerant motor control, and battery parameter modeling. These works reflect trends in automotive electrification , hybrid systems , and environmental sustainability . Supervision : Supervised PhD research on hybrid electric vehicle control strategies (Christopher Vagg, 2015). Grants & Projects include Innovate UK-funded initiatives like Battery Integrated Wing (2025–2028) and EPSRC-supported JLR Prosperity Partnership (2021–2026). He also leads the IAAPS Institute for Advanced Automotive Propulsion Systems. Key Collaborations : Ford Motor Company, Jaguar LandRover, West of England Combined Authority.

Thijs van Keulenمشاهده پروفایل

استادیار

• Optimal Control Theory
• Control of Constrained Systems
• Extremum Seeking Control
• +۶ مورد دیگر

Thijs van Keulen is a Part-time Assistant Professor at the Mechanical Engineering Department of Eindhoven University of Technology (TU/e), affiliated with the Control Systems Technology Group under the supervision of Professor W.P.M.H. Heemels. He also holds an ancillary position as Mechatronics Engineer at ASML since 2018. MSc in Mechanical Engineering (Delft University of Technology, 2007) PhD in Mechanical Engineering (TU/e, 2011) Research Interests : Thijs specializes in optimal control theory , focusing on constrained systems and extremum seeking control . His work bridges theoretical development with industrial applications in hybrid vehicles , heavy-duty powertrains , and high-performance mechatronic systems . Key contributions include modeling solutions for emissions reduction, fuel efficiency improvements, and adaptive feedforward parameter learning frameworks for industrial machinery. Article Trends : His research spans control systems engineering with a focus on hybrid transportation technologies and industrial automation . Recent publications highlight applications of Pontryagin's Minimum Principle to eco-driving challenges, recursive learning in high-tech motion systems, and robust control frameworks for varying reference trajectories, demonstrating interdisciplinary impact across automotive, industrial, and applied mathematics domains. Grants & Collaborations : His work has been supported by the Dutch Research Council (NWO) and Project NEON (17628). Collaborations with DAF Trucks N.V. (2011-2018) and ASML emphasize industry-academia partnerships.

• Electric Vehicle Engineering
• Battery System Design
• Autonomous Vehicle Optimization
• +۵ مورد دیگر

Jelena Andric is an Associate Professor in the Vehicle Engineering and Autonomous Systems department at Chalmers University of Technology, working within the Mechanics and Maritime Sciences school. Her research spans multiple aspects of vehicle engineering with a particular focus on electric and autonomous vehicle technologies. Her research interests primarily center around electric vehicle engineering, battery system design, autonomous vehicle optimization, thermal management systems, computational fluid dynamics, reinforcement learning applications, and hardware-in-the-loop simulation. She has developed expertise in applying advanced computational methods to solve complex vehicle engineering problems, particularly in the areas of battery management and energy optimization. Analysis of her recent publications reveals a strong trend toward optimizing electric vehicle performance, particularly focusing on battery degradation mitigation, thermal management, and energy efficiency. Her work increasingly incorporates artificial intelligence techniques, especially reinforcement learning, to develop sophisticated optimization approaches for electric trucks and autonomous vehicles. The research spans from fundamental fluid dynamics studies to applied engineering solutions for real-world transportation challenges. Dr. Andric has been actively involved in numerous research projects funded by organizations including VINNOVA, the Swedish Energy Agency, CHAIR, and ÅForsk. These projects cover diverse areas such as battery aging prediction, vehicle management strategies for electrified vehicles, electric public transit systems, and virtual engine calibration. Her current research portfolio includes leadership in projects related to simulation-based evaluation of connected vehicles, battery aging prediction for electric autonomous vehicles, AI-cloud-based vehicle management strategies, and transition to electric public transit systems. These projects demonstrate her commitment to addressing critical challenges in sustainable transportation through advanced engineering solutions.

Imran Qureshiمشاهده پروفایل

دانشیار

• Gas Turbine Engines
• Experimental Fluid Dynamics
• Computational Fluid Dynamics
• +۱۰ مورد دیگر

Dr. Imran Qureshi is an Associate Professor in the Department of Mechanical Engineering at the University of Birmingham Dubai Campus, part of the School of Engineering. He previously served as an Assistant Professor at the American University of Sharjah, UAE, before joining the University of Birmingham. His academic and industrial expertise lies in mechanical and aerospace engineering, particularly in gas turbine systems and sustainable energy technologies. BEng (Hons) in Aerospace Engineering, NUST, Pakistan MSc in Mechanical Engineering, University of Leeds, UK DPhil in Engineering Science, University of Oxford, UK Chartered Engineer (CEng), IMechE UK Dr. Qureshi's research focuses on experimental and computational fluid dynamics , gas turbine engines , heat transfer , and sustainable energy systems . His work bridges industrial applications and academic inquiry, particularly in improving turbine performance and advancing renewable energy technologies. He has investigated aggressive inlet swirl effects, combustor temperature nonuniformity, and dynamic engine modeling using artificial intelligence. His recent publications reflect a growing emphasis on sustainability, with studies on net-zero energy buildings , photovoltaic and concentrated solar technologies , and hydrogen propulsion . The integration of AI in turbine diagnostics and performance monitoring marks a significant trend in his scholarly output. His work spans both fundamental aerothermal investigations and applied sustainability solutions. Dr. Qureshi has no listed scientific awards in the provided text. He teaches undergraduate modules including Thermodynamics and Fluid Mechanics , Sustainable Energy and Environment , Engineering Mathematics , Powertrain and Vehicle Engineering , and supervises final-year individual engineering projects. There is no mention of students he has advised or research grants he has led. No specific lab or research team is referenced in the text.

• Mechanical Engineering
• Machine Design
• Robotics
• +۵ مورد دیگر

Pedro Ortiz Morón is a faculty member at the Barcelona East School of Engineering (EEBE), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Mechanical Engineering. He teaches MACHINE DESIGN and supervises numerous Final Degree Projects, demonstrating active engagement in engineering education and applied research. Research Interests: His work centers on mechanical design, with emphasis on robotics, vehicle dynamics, automation, and educational tools. Projects under his supervision span from robotic prostheses to Formula Student vehicles, indicating a strong focus on practical, hands-on engineering solutions. His interest in Arduino-based systems highlights integration of electronics and mechanics in teaching and prototyping. Publication Trends: The recent articles reflect a consistent focus on mechanical systems design, optimization, and innovation in both industrial and assistive applications. There is a clear emphasis on student-driven projects in automotive, robotics, and educational contexts, often involving prototyping and real-world implementation. Scientific Awards: No awards or honors are mentioned in the provided text. Advising and Grants: Ortiz Morón has supervised at least 20 Final Degree Projects between 2017 and 2024, serving as primary advisor. His students have worked on diverse topics including hydraulic lifts, robotic prostheses, and vehicle dynamics. There is no mention of research grants or funding in the text. Labs and Teams: While no specific lab or research team is named, his involvement in Formula Student and Arduino-based educational tools suggests collaboration with student engineering teams and possibly laboratory development for teaching purposes.

• Combustion
• Energy Management Systems
• Hybrid Electric Vehicles
• +۷ مورد دیگر

Luciano Rolando is an Associate Professor at the Department of Energy (DENERG) in Politecnico di Torino. He is a member of the CARS@PoliTO Interdepartmental Center for Automotive Research and Sustainable Mobility. His academic roles include teaching Hybrid Propulsion Systems at the PhD level and various undergraduate/graduate courses such as Thermal Machines and Structural Mechanics and Fluid Machines across Chemical, Mechanical, and Energy Engineering programs. As Scientific Director and Manager of competitive and commercial research projects like OpThermEV (2021-2022) and Alternative Fuels: Large Bore Ammonia Combustion (2024-2025), he focuses on optimizing thermal management systems, hydrogen combustion, and emission reduction technologies. His research group E3 (DENERG) explores synergies between hybrid propulsion, renewable fuels, and predictive control algorithms. His recent publications highlight advancements in deep reinforcement learning for energy management, hydrogen-fueled powertrains, and dual-diluted combustion systems. Collaborations include industry partnerships and supervision of seven ongoing PhD students. He holds a national patent for predictive thermal control systems in electric vehicles, aligning with SDG goals 7, 12, and 13.

Christopher Sittlمشاهده پروفایل

پژوهشگر

• Computational Acoustics
• Vehicle Acoustics
• Boundary Element Method
• +۶ مورد دیگر

Christopher Sittl is a Researcher at the Chair of Vibroacoustics of Vehicles and Machines within the Department of Engineering Physics and Computation at the TUM School of Engineering and Design, Technical University of Munich. Pursuing an External PhD, his work focuses on developing efficient computational methods for acoustic optimization in automotive applications. His research interests span computational acoustics, vehicle noise control, and advanced numerical methods: Computational Acoustics Vehicle Acoustics and Noise Optimization Boundary Element Method applications Finite Element Method for vibroacoustic problems Matrix-Padé-via-Lanczos Method implementation Sound quality engineering for automotive powertrains Sittl's research addresses the computational challenge of solving large linear systems in acoustic scattering tasks, moving beyond traditional frequency-by-frequency approaches to develop more efficient Padé-approximation methods applicable across frequency ranges. His work bridges theoretical numerical methods with practical automotive engineering needs, particularly in creating customer-pleasant noise profiles rather than merely minimizing sound pressure levels. His primary publication demonstrates application of Krylov subspace methods for efficient acoustic transfer function solutions. Collaborating with Ostbayerische Technische Hochschule Regensburg, Otto von Guericke University of Magdeburg, and CHP Messtechnik GmbH, his research contributes to the department's focus on computational vibroacoustics and automotive noise control.

Imen Bahriمشاهده پروفایل

پژوهشگر

• Control Systems
• Electrical Engineering
• Power Electronics
• +۳ مورد دیگر

Imen Bahri is a researcher at the Laboratory of Electrical and Electronic Engineering of Paris (GeePs) , specializing in control systems for electromagnetic and power electronic devices. Her work focuses on vibration reduction, efficiency optimization, and sensorless control strategies for electric machines like switched reluctance machines (SRMs) and permanent magnet synchronous machines (PMSMs). Research Interests include: Robust control methods (H-infinity, RST controllers) Intermittent control for automotive applications Sensorless performance enhancement DC microgrid voltage regulation Recent publications address vibration suppression via HW/SW partitioning, torque pulsation in electric vehicles, and FPGA-based fault-tolerant systems. She collaborates with institutions like Université de Lorraine and IEEE on modeling, simulation, and industrial electronics.

Nick Morrisمشاهده پروفایل

دانشیار

• Tribology
• Lubrication Engineering
• Mechanical Engineering
• +۳ مورد دیگر

Dr. Nick Morris is a Reader in Surface and Lubrication Engineering with over 12 years of experience in powertrain dynamics and tribology. He specializes in tribo-dynamic simulations and experiments to address efficiency, wear, and NVH issues in automotive systems. His work focuses on bearing hydrodynamics, experimental tribology, clutch dynamics, and lubricant additives. He has published 66 papers, including 36 journal articles, and supervised 10 doctoral researchers in industry-funded projects. Education: BEng, PhD Research Interests: Morris’s research spans tribology, lubrication engineering, and automotive systems. Key areas include: Bearing and clutch tribodynamics Surface texturing for reduced friction Electrical discharge phenomena in e-motor bearings Lubricant additives and their interactions Publications: Recent work highlights include studies on electric vehicle powertrains, diamond-like carbon coatings, and hydrogen-fueled Wankel engines. His articles often integrate experimental and numerical methods to explore frictional interactions and material performance. Grants/Advising: Supervised 10 doctoral researchers and industry-funded projects. Active in editorial roles for Journal Lubricants and the Institution of Engineering and Technology’s Tribology Executive Committee. Labs/Teams: Member of the Dynamics and Tribology Research Group, focusing on advanced tribological systems.

Jeremy Laliberteمشاهده پروفایل

استاد

• Composite Materials
• Fibre Metal Laminates (FMLs)
• Uninhabited Aerial Vehicles (UAVs)
• +۷ مورد دیگر

Professor Jeremy Laliberte is a faculty member in the Department of Mechanical and Aerospace Engineering at Carleton University. He focuses on novel aircraft structures, composite materials, and next-generation UAV/MAV design. Previously a Research Officer at the National Research Council Institute for Aerospace Research (2001-2008), he now leads the Advanced Aircraft Design Lab and co-leads the NSERC CREATE UTILI initiative with multiple Canadian universities. Research areas include: Composite and hybrid material manufacturing Biomimetic aerospace structures Hydrogen fuel cell aircraft power systems Finite element analysis of impact damage Urban air mobility safety protocols Recent publications emphasize: High-fidelity composite modeling Low-velocity impact analysis Hybrid delivery logistics Battery lifecycle optimization Scientific recognition includes: Best Poster at ICAF 2023 Best Student Paper/Presentation awards (2022 AEAC) He supervises a research group working on projects with industry partners like Bell Helicopter, Bombardier, and NRC.

Stephan Rinderknechtمشاهده پروفایل

استاد

• Mechatronic Systems
• Vehicle Systems
• Energy Systems
• +۱۰ مورد دیگر

Stephan Rinderknecht is a Professor for Mechatronic Systems in Mechanical Engineering at Technische Universität Darmstadt since 2009. His research focuses on Vehicle Systems Energy Systems Vibration Systems Robotics Finite Element Method (FEM) Multi-body Simulation (MBS) Hybrid and Electric Drives Rotor Dynamics Active Magnetic Bearings .