Find Academic Supervisors

Christopher LeonardiView profile

Associate Professor

• Computational Mechanics
• Fluid-Solid Interactions
• Multiphase Flows
• +3 more

Dr. Christopher Leonardi is an Associate Professor and Director of Teaching and Learning at the School of Mechanical and Mining Engineering, The University of Queensland (UQ). He is affiliated with the Centre for Multiscale Energy Systems and has extensive industry experience as an engineering consultant with Rockfield Technologies Australia. PhD in Computational Mechanics, University of Wales, Swansea BE(Hons) in Mechanical Engineering, James Cook University (First Class Honours, University Medal) Research Interests focus on computational models for fluid-solid interactions, including: Suspension Transport Porous Media Flow Multiphase Flows Poromechanics Applications in Coal Seam Gas (CSG) and Hydrogen Production His work spans unconventional reservoirs, mineral extraction, and hydrogen formation via methane pyrolysis, utilizing methods like Lattice Boltzmann, Discrete Element, and Finite Element Analysis. Collaborations include Pawsey Supercomputing Centre. Scientific Awards include: Australian Awards for University Teaching (AAUT) Citation, 2019 UQ Citation for Outstanding Contributions to Student Learning, 2018 Advance Queensland Industry Research Fellowship (Mid-Career) Teaching involves coordinating MECH3780 Computational Mechanics and lecturing ENGG1001 Programming for Engineers . His team includes postdoctoral and postgraduate researchers, with significant industry partnerships.

• Metallurgy
• Extractive Metallurgy
• Metal Processing
• +4 more

Tomasz Kargul serves as a Lecturer at the Department of Plastic Metal Processing and Extractive Metallurgy within the Faculty of Metals Engineering and Industrial Computer Science at AGH University of Science and Technology in Kraków, Poland. His academic position falls under the assistant professors group, with office location in Building B-5, Room 309 at Czarnowiejska Street 66, and primary contact email tkargul@agh.edu.pl. Dr. Kargul's research centers on metallurgical engineering with emphasis on superalloy systems (particularly Ni-based MAR-M247 and Co-based X-40), nanocomposite development for repair applications, phase transformation mechanisms in peritectic steels, and steelmaking process optimization. His experimental work integrates microstructure characterization, thermal analysis, and fluid dynamics modeling to address industrial challenges in aerospace component repair, directional solidification, and ladle refining processes. Key methodologies include suction casting, differential scanning calorimetry, and numerical simulation of casting phenomena. Analysis of his 15 most recent publications (2025-2014) reveals three dominant research thrusts: (1) Nanocomposite-enhanced superalloy repair technologies focusing on TiB 2 /TiC-reinforced Alloy 625 systems; (2) Fundamental studies of phase transformations in peritectic steels using advanced thermal characterization; and (3) Optimization of ladle stirring hydrodynamics and continuous casting processes. The work consistently bridges experimental metallurgy with industrial process modeling, demonstrating strong specialization in high-temperature material behavior and solidification phenomena. Scientific awards: No awards or honors were documented in the available sources. Advising and grants: Publicly accessible information does not specify graduate student supervision, research funding sources, or grant awards. His departmental role suggests involvement in undergraduate and graduate instruction within metallurgical engineering programs, but specific advising records remain undisclosed.

Baafour Nyantekyi-KwakyeView profile

Assistant Professor

• Thermo-fluids
• Turbulent Flows
• River Ice Engineering
• +3 more

Baafour Nyantekyi-Kwakye is an Assistant Professor in the Mechanical Engineering department at Memorial University of Newfoundland since August 2018. He holds a PhD (2016), MSc (2011), and BSc (2005) in Mechanical Engineering from the University of Manitoba, Canada and Kwame Nkrumah University of Science and Technology (KNUST), Ghana. His expertise spans thermo-fluids, turbulent structures in separated/reattached flows, atomization in gas turbines, river ice processes, and ice jam stability. Educations: PhD in Mechanical Engineering, University of Manitoba (2016) MSc in Mechanical Engineering, University of Manitoba (2011) BSc in Mechanical Engineering (Thermo-fluids & Energy Systems), KNUST, Ghana (2005) Research Interests: Dr. Nyantekyi-Kwakye focuses on experimental fluid mechanics, particularly in turbulent flow structures within offset jets, river ice dynamics, and hydraulic engineering applications. His work combines advanced measurement techniques like PIV and acoustic Doppler velocimetry to study flow behaviors in complex environments, such as ice jams and rough surfaces. Key themes include mitigating riverbed scouring at hydropower stations and understanding border ice formation through turbulent transport mechanisms. Publishing Trends: His recent articles emphasize river ice engineering (e.g., ice jam stability) and 3D turbulent offset jet dynamics. He has contributed to journals like Journal of Hydraulic Research and Journal of Turbulence , with a focus on experimental methodologies and numerical model validation. Awards & Honors: University of Manitoba Graduate Fellowship (2013-2015) International Graduate Student Scholarship (2012-2013) Best Poster Presentation (Thermo-fluids Division, 2011) Advising & Grants: Supervised graduate students at the University of Manitoba's Hydraulic Research and Testing Facility (HRTF). Active reviewer for the Journal of Applications of Computational Fluid Mechanics and member of ASME and CSME. No explicit grant details provided in text. Labs & Teams: Associated with the Energy and Combustion Laboratory (University of Manitoba) and Hydraulic Research and Testing Facility (HRTF). Collaborates with multidisciplinary teams on fluid dynamics and environmental engineering challenges.

Weidong ZhuView profile

Professor

• Vibration Analysis
• Mechanical Engineering
• Acoustics
• +3 more

Professor Weidong Zhu is a mechanical engineering professor at the University of Maryland, Baltimore County (UMBC), specializing in vibration analysis, acoustics, and nonlinear dynamics. His research focuses on applications such as high-speed elevator cable dynamics, wind turbine optimization, and automotive systems. He has developed innovative methodologies for vibration measurement using advanced laser Doppler vibrometry techniques. Zhu's work has been recognized with prestigious awards, including the Rayleigh Lecture from the American Society of Mechanical Engineers (2023) and the 2020 Board of Regents’ Faculty Award for Excellence in Scholarship. His research bridges theoretical analysis and practical engineering solutions, addressing challenges in structural health monitoring, energy harvesting, and dynamic system control. Key contributions include studies on rotating machinery dynamics, nonlinear energy sinks, and the integration of machine learning for control systems. His methodologies enhance the understanding and mitigation of vibrations in critical infrastructure, such as wind turbines and tidal energy converters.

• Computational Intelligence
• Evolutionary Multi-objective Optimization
• Evolutionary Machine Learning
• +5 more

Professor Hisao Ishibuchi is Chair Professor of Computer Science and Engineering at Southern University of Science and Technology (SUSTech) in Shenzhen, China, a role he has held since April 2017. Previously, he spent nearly three decades at Osaka Prefecture University, progressing from Research Associate (1987-1993) to Assistant Professor (1993), Associate Professor (1994-1999), and full Professor (1999-2017). He is an IEEE Fellow , served as Vice-President of the IEEE Computational Intelligence Society (2010-2013) , and is currently President of the Japan Society for Evolutionary Computation (2016-2018) . He is Editor-in-Chief of IEEE Computational Intelligence Magazine (2014-2019) and the Journal of the Japan EC Society (2014-2018). Education: Ph.D. in Engineering, Osaka Prefecture University, 1992 M.S. in Engineering, Kyoto University, 1987 B.S. in Engineering, Kyoto University, 1985 Research Focus: Professor Ishibuchi is internationally recognised as a pioneer of computational intelligence , with seminal contributions to evolutionary multi-objective optimisation , evolutionary machine learning , fuzzy systems , neural networks , and hybrid intelligent systems . He introduced the first multi-objective memetic algorithm and early methods for multi-objective fuzzy rule-based classifier design that balance accuracy and interpretability. Publications & Impact: With over 100 journal papers in top-tier venues such as IEEE Transactions on Evolutionary Computation and nearly 500 conference papers, his work has attracted more than 24 000 Google-Scholar citations and an h-index of 68. His recent articles concentrate on many-objective optimisation, fuzzy machine learning, and transfer learning techniques. Honours & Awards: IEEE Computational Intelligence Society Fuzzy Systems Pioneer Award 2019 IEEE Fellow 2014 JSPS Prize 2007 (Japan’s most prestigious mid-career award) Multiple Best Paper Awards from GECCO, FUZZ-IEEE, SCIS & ISIS, WAC, ACIIDS, HIS-NCEI, and others Teaching & Mentoring: At SUSTech he teaches Advanced Algorithms and Advanced Optimization Algorithms , covering greedy algorithms, hyper-heuristics, memetic algorithms, multi-objective optimisation, and performance assessment. His research group actively recruits post-doctoral fellows and research assistants in evolutionary computation, fuzzy systems, and neural networks. Labs & Teams: He leads the Computational Intelligence Research Group at SUSTech, maintaining active collaboration networks across Asia, Europe, and North America, and supervising several post-doctoral researchers and graduate students working on next-generation intelligent systems.

• Stochastic Modeling
• Statistical Physics
• Non-Equilibrium Statistical Physics
• +4 more

Cristian Spitoni is an Assistant Professor in the Mathematical Modeling group at the Mathematical Institute within the Faculty of Science at Utrecht University. His office is located in the Hans Freudenthal Building at Budapestlaan 6, Room 510, 3584 CD Utrecht. He maintains an active research profile spanning mathematical physics, statistics, and interdisciplinary applications in medical informatics and neuromorphic computing. His primary research interests include Stochastic Modeling, Statistical Physics, Non-Equilibrium Statistical Physics, and Survival Analysis. Dr. Spitoni's work demonstrates a remarkable interdisciplinary range, bridging theoretical mathematics with practical applications in healthcare and computing. His research trajectory shows a fascinating evolution from fundamental statistical physics problems to medical applications and more recently to neuromorphic computing. Analysis of his recent publications (2023-2025) reveals three major research thrusts: 1) Theoretical work on probabilistic cellular automata and metastability in statistical physics; 2) Medical statistics applications focusing on ICU infections, sepsis, and survival analysis; and 3) Cutting-edge research in neuromorphic computing, particularly on memristors, fluidic circuits, and brain-inspired computing architectures. His work increasingly shows interdisciplinary convergence, with mathematical techniques from statistical physics being applied to both medical informatics and neuromorphic engineering problems. Dr. Spitoni has established productive collaborations with researchers across multiple disciplines, including medical researchers at Utrecht University Medical Center and physicists working on novel computing architectures. His research has been published in high-impact journals spanning physics, mathematics, medical informatics, and computer science, demonstrating the breadth and significance of his contributions. His teaching responsibilities include courses such as Interacting Particle Systems in the Lattice and Continuum, Introduction to Complex Systems, and Mathematical Statistics, reflecting his expertise in both theoretical and applied mathematical modeling.