Find Academic Supervisors

Eric CoataneaView profile

Professor

• Manufacturing Systems
• Additive Manufacturing
• Causal Graphs
• +5 more

Eric Coatanea is a Professor at Tampere University, affiliated with the Automation Technology and Mechanical Engineering department within the Faculty of Engineering and Natural Sciences. His research focuses on manufacturing systems, causal graph networks, multi-disciplinary optimization, and AI integration in engineering design. He holds a BSc from University of West Brittany (1990), MSc from INSA Toulouse (1993), and teaching certification from Ecole Normale Supérieure (1994). Research interests include modeling manufacturing systems, additive manufacturing (e.g., Directed Energy Deposition), causal graphs for decision-making, and systems engineering. Notable awards include the Chevalier des Palmes Académiques (2018) and Marie-Curie Fellowship (2006–2008). Recent publications emphasize optimization algorithms combining AI (e.g., L-ANN-GWO), viscosity effects in 3D printing, and causal graph applications in MDO. His work bridges theoretical frameworks with practical engineering challenges, focusing on early design synthesis and sustainable manufacturing. Commitments include editorial roles (Journal of Integrated Design & Process Science), NSERC Canada advisory, and board memberships (Dynavio Cooperative Oy, Selko Oy). Current projects include LILIAM, ÄVE, and DIGITBrain initiatives.

Joon ChungView profile

Professor

• Multidisciplinary Design Optimization
• Flight Simulation
• Human Machine Interface
• +4 more

Dr. Joon Chung is a Professor in the Department of Aerospace Engineering at Toronto Metropolitan University, specializing in aircraft design optimization and immersive simulation technologies. His educational background includes: PhD from the University of Toronto (1997) MASc from the University of Toronto (1993) BSc from Iowa State University (1990) Chung's research integrates Multidisciplinary Design Optimization (MDO) with cutting-edge VR/AR applications to solve holistic aircraft design challenges. His work spans flight simulation, Human Machine Interfaces (HMI), and aircraft interior customization, focusing on how immersive technologies can optimize aerodynamics, control systems, and user experience across pilot training, maintenance, and customer configuration processes. He actively supervises graduate students and leads the MIMS (Mixed-Reality Immersive Motion Simulation) Lab, one of Canada's pioneering research groups developing VR/AR solutions for aerospace engineering applications.

• Aircraft Electrification
• Conceptual Aircraft Design
• Multidisciplinary Design Optimization (MDO)
• +2 more

Michael Kruger is a postdoctoral researcher at the University of Southern California's Viterbi School of Engineering, affiliated with the Dryden Wind Tunnel. His work focuses on aerodynamics and electric aircraft design. Bachelor's and Master's in Mechanical Engineering from University of Pretoria PhD in Aerospace and Mechanical Engineering (ADRL) at USC His research integrates traditional aircraft design with advanced computational modeling and optimization, particularly in electric propulsion systems for commuter and trans-continental aircraft. He contributed to the development of the SUAVE MDO framework and the LUCAS conceptual design library. Currently, he characterizes flow fields in the Dryden Wind Tunnel's upgraded test section and collaborates with undergraduate and graduate students on fundamental aerodynamics experiments.

Mehdi TarkianView profile

Associate Professor

• Design Automation
• Machine Learning
• Optimization
• +5 more

Mehdi Tarkian is a Senior Associate Professor at Linköping University within the Department of Management and Engineering (IEI) , focusing on the Product Realisation division. His research and teaching emphasize Design Automation, leveraging methods like Knowledge-Based Engineering (KBE), Machine Learning, and Optimization. He co-founded the spin-off company XperDi in 2012, based on his research, and returned to LiU full-time in 2017. Current research projects include AutoPack (ML-driven CAD automation), ADAPT (design automation for production preparation), and DeProtion (construction sector design automation). He teaches courses such as Collaborative Multidisciplinary Design Optimization (TMKT79) and Product Modeling (TMKT57) , both highly rated by students. Publications highlight advancements in optical character recognition (OCR) for engineering drawings, reinforcement learning in unstructured production environments, and automated fixture design. His work bridges academic research with industrial applications, aiming to reduce repetitive tasks and enhance engineering intuition. He is part of the Automation Lab and the Unit of Machine Design and Industrial Production (PRODKOP) , collaborating with industry partners to translate research into practical solutions.

• Renewable Energy
• Fluid-Structure Interaction (FSI)
• Aeroacoustics
• +5 more

Huadong Yao is an Assistant Professor at the Department of Marine Engineering, Chalmers University of Technology. His research spans renewable energy , fluid-structure interaction (FSI) , and transportation systems , with a focus on offshore wind farms, wave energy, and aero/hydroacoustics. Multi-University Collaboration : Guest professorships at international institutions Leadership Roles : Coordinator of Horizon 2020 projects (e.g., IVANHOE) and guest editor for journals Key Organizations : Member of AIAA, SAE International, RINA, ICNMT, and ICES Working Group on Offshore Renewable Energy His research integrates CFD and FSI coding (OpenFOAM, in-house codes) with turbulence modeling (LES, SNGR) to address problems in marine hydrodynamics (e.g., rim-driven thrusters, wind-powered ship propulsion) and terrestrial transportation (high-speed train aerodynamics, urban air mobility). Recent work explores biomechanics (whiplash injury hydrodynamics) and battery cooling systems for electric vehicles. Current projects focus on: Optimization of wave energy converter farms (hexagon layouts, mooring fatigue) Hubless rim-driven thruster design (gap geometry, concave cavities) Hydrographic impacts of offshore wind turbines on marine environments Urban air mobility (UAM) aerodynamics Multidisciplinary Design Optimization (MDO) using machine learning He collaborates with institutions like AIAA, SAE, and ICES, and has received funding from Horizon 2020 and Swedish national agencies.

Sicheng HeView profile

Assistant Professor

• Multidisciplinary Design Optimization (MDO)
• Computational Fluid Dynamics (CFD)
• Computational Aeroelasticity
• +8 more

Sicheng He is an Assistant Professor in the Department of Mechanical, Aerospace and Biomedical Engineering at the University of Tennessee, Knoxville since August 2023. He previously held postdoctoral research positions at MIT (2022-2023) and the University of Michigan, Ann Arbor (2020-2021), where he focused on computational aeroelasticity and multidisciplinary design optimization (MDO). Education: PhD in Aerospace Engineering (2020), University of Michigan, Ann Arbor MS in Applied Math (2015), University of Michigan, Ann Arbor MSE in Aerospace Engineering (2015), University of Michigan, Ann Arbor BSE in Aerospace Engineering (2013) and Mechanical Engineering (2013), Joint Institute, Shanghai Jiao Tong University Research Interests: Sicheng He specializes in optimization techniques for large-scale dynamical systems, with emphasis on PDE-constrained optimization, mixed integer programming, and machine learning-based surrogate models. His work includes applications in wind energy systems, aircraft design (particularly transonic buffet analysis), and stability-constrained optimization frameworks. Publication Trends: His research output focuses on computational physics and optimization, with recurring themes in aerospace engineering, wind energy, and multidisciplinary design. Key methodologies include algorithmic differentiation, time-spectral solvers, and gradient-enhanced neural networks for aerodynamic shape optimization. Awards: Best student paper in MDO, 2nd place, AIAA Aviation Conference 2019 Professional Involvement: Active in AIAA and ICAO CAEP Working Group 3. Developed educational workshops on figure visualization and Git version control at MIT. Serves as reviewer for journals including AIAA Journal, Structural and Multidisciplinary Optimization, and International Journal for Numerical Methods in Fluids.

Darshan SarojiniView profile

Assistant Professor

• Multidisciplinary Design, Analysis, and Optimization (MDAO)
• Aircraft Design
• Systems Engineering
• +5 more

Darshan Sarojini is an Assistant Professor in the Aerospace and Ocean Engineering Department at Virginia Tech (College of Engineering). His research focuses on Multidisciplinary Design, Analysis, and Optimization (MDAO) , Certification-Driven Aircraft Design , and Systems Engineering , with applications in Urban Air Mobility (UAM) and electric vertical takeoff and landing (eVTOL) systems. He leads the Intelligent Design Optimization (IDOpt) Lab , which develops advanced methods for complex engineering systems design. Education: Ph.D. & M.S. in Aerospace Engineering, Georgia Institute of Technology M.S. in Computational Science and Engineering, Georgia Tech B.E. in Mechanical Engineering, B.M.S. College of Engineering, India Research expertise includes integrating Model-Based Systems Engineering (MBSE) with MDAO, high-performance computing (HPC) workflows, and structural optimization under dynamic loads. He has served as Technical Discipline Chair for the AIAA Modeling and Simulation Technologies committee and contributed to NASA ULI projects. Recent work emphasizes large-scale MDO of eVTOL concepts, certification-constrained design, and computational frameworks for aircraft systems. He has mentored students from the ENLACE program and collaborated with industry partners like Archer Aviation and Aurora Flight Sciences. Honors include Best Application Paper Awards at IFToMM 2015 and the 2015 National Conference on Machines and Mechanisms. His lab actively engages in student competitions (e.g., IndySCC) and promotes broader participation in HPC through workshops.

• Multidisciplinary Design Optimization (MDO)
• Aerospace Engineering
• Surrogate Models
• +6 more

Nathalie Bartoli is a Senior Research Scientist (DR2) at ONERA and a Professor at ISAE-SUPAERO. She holds a Habilitation degree (HDR) in Applied Mathematics and specializes in Multidisciplinary Design Optimization (MDO), surrogate modeling, and Bayesian optimization. Her work focuses on aerospace applications, particularly aircraft design and optimization algorithms. She leads the Multidisciplinary Methods and Integrated Concepts Unit (DTIS/M2CI) at ONERA and teaches courses on optimization and MDO at ISAE-SUPAERO. Her research interests include surrogate models (Kriging/Gaussian Processes, mixture of experts), Bayesian optimization, and data fusion techniques. She is a member of the AIAA MDO Technical Committee and has organized workshops such as the MDO PhD Day (2019) and European MDO Workshops (2019, 2020). She has supervised over 25 PhD students and co-authored the SMT Python toolbox for surrogate modeling. Recent achievements include keynote speaking at NATO conferences, winning AIAA MDO Best Paper Awards (2022, 2020), and contributions to the AGILE H2020 project. Her work integrates manufacturing, supply chain, and aircraft design through MDO frameworks, addressing challenges in green aviation and hybrid propulsion systems. She collaborates internationally with universities like McGill and TU Delft, and industries like Airbus and DLR. Awards include the 2018 ICAS Award for AGILE project contributions and multiple best paper recognitions. Her research bridges theoretical optimization methods with practical aerospace engineering, emphasizing scalable algorithms for high-dimensional problems and industrial applications.

• Aircraft Design
• Aeronautical Systems
• Model-Based Systems Engineering (MBSE)
• +4 more

Atif Riaz is a Senior Lecturer in Aircraft Engineering and Design at Cranfield University's School of Engineering (Department of Aerospace Engineering). He holds a BEng in Aeronautics/Astronautics (University of Southampton), BSc in Computer Sciences, and a PhD in Aerospace Engineering (Cranfield University). His research focuses on complex systems design methodologies, including MDO, MBSE, and set-based design, with applications in aircraft design and aerospace systems. He teaches courses on Systems Modelling Language (SysML), Multidisciplinary Design Optimization, and Integrated Product Development. Key collaborations include Airbus and Rolls-Royce through projects like COLIBRI, where he develops cloud-based collaborative design tools (e.g., AirCADia software deployed at Airbus). He has supervised multiple PhD students and contributed to EU/UK research initiatives such as CRESCENDO and DAVINCI. His work spans technical domains like aeroacoustics, safety assessment, and environmental impact analysis of supersonic aircraft. Publications emphasize computational frameworks for uncertainty management, margin allocation, and interactive systems architecting.

Achille MessacView profile

Professor

• Multidisciplinary Design Optimization
• Structural Optimization
• Wind Energy Systems
• +3 more

Achille Messac is a Professor and Dean of the College of Engineering and Architecture at Howard University. He holds a Ph.D. from MIT's Department of Aeronautical and Astronautical Engineering. His research focuses on multidisciplinary design optimization (MDO), structural optimization, wind energy systems, and surrogate modeling techniques. He has authored over 240 publications and a textbook on optimization with MATLAB. Dr. Messac is a Fellow of AIAA and ASME, and has received prestigious awards including the AIAA MDO Award and NSF CAREER Award. He has held leadership roles such as Department Chair at Syracuse University and Dean at Rensselaer Polytechnic Institute. His technical contributions include pioneering work in control structure integrated design and wind farm optimization. He currently serves on editorial boards of Optimization and Engineering Journal, and chairs AIAA committees. His research emphasizes practical applications of optimization in engineering systems and renewable energy.

Brian J. GermanView profile

Associate Professor

• Aerospace Engineering
• Electric Propulsion
• Urban Air Mobility (UAM)
• +6 more

Brian J. German is the National Institute of Aerospace Langley Associate Professor in the Daniel Guggenheim School of Aerospace Engineering at the Georgia Institute of Technology. His research focuses on electric propulsion, urban air mobility (UAM), and the transformation of aviation through autonomy and distributed electric propulsion technologies. Education: Ph.D. in Aerospace Engineering, Georgia Tech (2007) M.S. in Aerospace Engineering, Georgia Tech (2000) B.S. in Aerospace Engineering, Georgia Tech (1999) German specializes in aircraft design optimization, battery modeling for electric aircraft, and operations research for emerging aviation markets. His work spans technical domains like aerodynamics, propulsion systems, and airspace utilization, with applications in UAM, thin-haul regional aviation, and cargo delivery via eVTOL aircraft. Recent research trends emphasize multidisciplinary optimization frameworks, propeller-wing interaction modeling, and economic feasibility studies for electric aircraft. He has led NASA-sponsored projects on vertiport placement, battery recharge economics, and blown wing performance analysis. Scientific Awards: NSF CAREER Award (2012) AIAA Associate Fellow (2017) Fulbright Scholarship (2002) Lockheed Martin Dean’s Excellence in Teaching Award (2012) National Defense Science and Engineering Graduate Fellowship (1999) German has advised students on eVTOL cargo delivery, blown wing wind tunnel studies, and optimization of reconfigurable aircraft. He teaches undergraduate and graduate courses on aerospace performance, design methods, and optimization. His lab conducts wind tunnel and flight tests of subscale CTOL/STOL/VTOL aircraft to validate aerodynamic and performance models.

• Aerospace Structures
• Multidisciplinary Design Optimization
• Aircraft Wing Design
• +1 more

Odeh Dababneh is a Senior Lecturer in Aerospace Structures at Kingston University's School of Engineering. His research focuses on Multidisciplinary Design Optimization (MDO) for aircraft wingbox structures using gradient-based methods. Professional experience includes: Lecturer in Aeronautical Engineering at University of South Wales Research Associate at Queen's University Belfast (£8.9M Powerplant Integration project) Engineering consultant for MD Defence & Aerospace Corporation Head of engineering at Royal Jordanian Aero Club Industry training includes programs with Jordan Aerospace Industries and Turkish Aerospace Industries covering aircraft manufacturing, F-16 modernization, and systems integration.

Wrik MallikView profile

Lecturer

• Aeroacoustics
• Aeroelasticity
• Fluid-Structure Interaction
• +10 more

Dr. Wrik Mallik is a Lecturer in Aerospace Engineering at the School of Engineering, University of Glasgow, joining in September 2022. His research focuses on computational modeling of fluid dynamics, fluid-structure interaction, and acoustics for sustainable applications in aeronautics, wind engineering, and marine sectors. Education: BTech in Civil Engineering from Jadavpur University, PhD in Aerospace Engineering from Virginia Tech, Postdoctoral Fellow at University of British Columbia Collaborations: Marine Directorate Scotland, National Manufacturing Institute of Scotland, University of Strathclyde, University of Salford, University of British Columbia, Indian Institute of Technology Delhi Key research areas include: Aeroacoustic modeling of bio-inspired fliers Transonic aeroelasticity of transport vehicles Energy harvesting from urban aerodynamics Underwater noise in offshore wind farms Data-driven additive manufacturing Recent publications (2025-2017) span fluid-structure interaction, shape optimization, and sustainable energy systems. Grants include EPSRC ILN+ funding and international partnership awards.

Hamdi AdelView profile

Senior Lecturer

• Inverse Problems
• Optimization with Partial Differential Equations (PDEs)
• Controllability of PDEs
• +3 more

Hamdi Adel is a Senior Lecturer (Maître de conférences HDR) at INSA Rouen Normandie, France, since September 2008. He is a permanent member of the Laboratory of Mathematics (LMI) and has collaborated with institutions in Germany (Humboldt University Berlin) and Tunisia. His research focuses on inverse problems in partial differential equations (PDEs), optimization with PDE constraints, and controllability of transport equations, particularly applied to groundwater and surface water pollution monitoring. His work includes developing non-iterative methods for source identification, dispersion-current adjoint functions for pollution tracking, and optimization techniques like the SAND (Simultaneous Analysis and Design) approach. He has supervised PhD students Boris Gnamah and Imed Mahfoudhi and contributed to projects such as M2NUM (Normandy Region & FEDER) and ECOS NORD M15M01. Hamdi's publications span journals like Inverse Problems , Journal of Engineering Mathematics , and Computational Optimization and Applications , addressing topics from 1D/2D/3D transport equations to aerodynamic optimization. He has also held administrative roles in academic committees (CoS INSA Rouen, CNU 26) and organized international workshops on automatic differentiation and optimization.

• Systems Engineering
• Sustainable Manufacturing
• Cyber-Physical Systems
• +5 more

Dr. Ali Asghar Bataleblu is a Senior Research Fellow at the Sustainable Manufacturing Laboratory within the Faculty of Engineering at the Free University of Bozen-Bolzano . His work focuses on transdisciplinary systems engineering for resilience, sustainability, and circular economy , with over a decade of experience in uncertainty-based Multidisciplinary Design Optimization (MDO) . He was previously the director of an MDO research center for nearly ten years. Academic Rank: Research Fellow Key Research Areas: Systems Engineering, Cyber-Physical Systems, Resilience Engineering, Sustainable Manufacturing Dr. Bataleblu’s research bridges model-based systems engineering (MBSE) , digital twins , and surrogate-assisted optimization to address sustainability challenges in manufacturing and mobility. He employs multi-agent systems and system-of-systems frameworks to analyze complex interactions in industrial and environmental contexts. His work includes requirements management and axiomatic design for holistic system decomposition. The 15 most recent articles highlight his focus on resilient cyber-physical production systems , sustainable mobility , AI-integrated MBSE , and multi-agent optimization for wildfire management. These works span disciplines like industrial engineering , computational intelligence , and urban planning , with subfields covering digital twins , dynamic system modeling , and automated routing . Scientific Awards: TOWARDS South Tyrol International Postdoctoral Fellowship (2023) Young Scientist Award at ICQIS-2024 (2024) He leads the Sustainable Factory Design Decomposition (SFDD) project funded by the Autonomous Province of Bolzano , collaborating with Purdue University Fort Wayne . His research integrates graph database visualization for supply chain resilience and life cycle assessment (LCA) automation in fast-moving consumer goods. He also explores reinforcement learning for aerial vehicle design and robust control systems for drones.