Find Academic Supervisors

Aleksandr ZinovievView profile

Research Fellow

• Additive manufacturing
• Metal 3D printing
• Materials science
• +6 more

Aleksandr Zinoviev is a Senior Research Associate at the School of Engineering and Information Technology (SEIT) at UNSW Canberra, where he has been working since 2022. His research spans multiple institutions across the globe, including previous positions at Siemens Digital Industries Software in Belgium, University of Bremen and AMSIS GmbH in Germany, and Institute of Strength Physics and Materials Science of the Russian Academy of Sciences and Tomsk Polytechnic University in Russia. He has also conducted research stays at the University of Bremen (Germany) and São Paulo State University (Brazil). Dr. Zinoviev's research interests are highly interdisciplinary, focusing on metal additive manufacturing, thermodynamics of materials, computational materials science, solid mechanics, software engineering, and machine learning. He specializes in developing and applying novel knowledge-based approaches to address engineering challenges, particularly in improving materials and parts produced by advanced manufacturing, optimizing production processes, and enhancing data processing. His work bridges the gap between fundamental materials science and practical engineering applications, with a strong emphasis on computational modeling and simulation. Analysis of his recent publications (2021-2025) reveals a consistent focus on additive manufacturing process modeling, microstructure-property relationships in additively manufactured metals, and computational approaches to materials science. His research particularly emphasizes cellular automata modeling, multiscale simulation techniques, and the application of machine learning to materials processing. The publications demonstrate expertise in both experimental characterization and advanced computational methods for predicting mechanical behavior of additively manufactured components. Dr. Zinoviev actively mentors prospective PhD and Research Master's candidates, offering guidance on topics related to thermal modeling of additive manufacturing and process optimization. He has indicated that scholarships of up to $35,000 (AUD) are available for qualified candidates who achieved High Distinction in their undergraduate program and/or have completed a Masters by Research.

• Biomaterials Engineering
• Biomedical Engineering
• Biomineralization
• +6 more

Dr. Liza-Anastasia DiCecco is an Assistant Professor in the Department of Systems Design Engineering at the University of Waterloo, where she leads the Regenerative Biomaterials Innovation Group. Her research focuses on biomimetic implant development for hard tissues, biomineralization processes, and advanced materials characterization using liquid phase electron microscopy. She holds a PhD in Materials Engineering from McMaster University and completed postdoctoral training at Penn State University supported by the NSERC Banting Fellowship. Education: PhD, Materials Engineering, McMaster University (2023) MASc, Materials Engineering, University of Windsor (2019) BASc, Mechanical Engineering, University of Windsor (2017) Research Interests: Biomaterials design for musculoskeletal applications Biomineralization mechanisms at organic-inorganic interfaces In situ liquid transmission electron microscopy (TEM) for dynamic material analysis 3D printing of functionalized medical implants Computational modeling of biomaterial behavior Awards & Recognition: 2023 NSERC Banting Postdoctoral Fellowship 2019-2022 NSERC Vanier Canada Graduate Scholarship 2024 M&M Microanalysis Society Creative Canvas Award 2023 McMaster University Fall Valedictorian Professional Affiliations: Councillor-At-Large, Microscopy Society of Canada Core Member, Waterloo Institute for Nanotechnology Member, Canadian Biomaterials Society Lab Focus: The DiCecco Team develops novel biomaterial characterization workflows linking atomic-to-macro scale structures, with emphasis on hydrated environments. Current projects explore titanium-based implants with genistein coatings and collagen mineralization mechanisms.

• Additive Manufacturing
• Welding Science
• Materials Engineering
• +3 more

Professor Stewart Williams is a leading academic at Cranfield University's Welding and Additive Manufacturing Centre, specializing in advanced manufacturing technologies. His research focuses on additive manufacturing, particularly wire arc additive manufacturing (WAAM), laser processing, and materials science. He previously worked at BAE Systems, contributing to aerospace manufacturing innovation. Williams' work bridges academia and industry, addressing challenges in large-scale engineering structures, residual stress mitigation, and material optimization. Education: PhD in Laser Physics (Royal Holloway College, University of London). Research Interests: His studies emphasize WAAM for titanium and aluminum alloys, hybrid laser-arc processes, and microstructure refinement through techniques like ultrasonic peening. He also investigates in-process monitoring and non-destructive evaluation for AM components. Grants & Partnerships: Leads the WAAMMat multi-client program and collaborates with industry leaders such as Airbus, Rolls-Royce, and Lockheed Martin. His projects address automation, mechanical properties, and industrial scalability of additive technologies. Labs/Teams: Heads Cranfield's Welding and Additive Manufacturing Centre, fostering interdisciplinary research in advanced manufacturing and materials engineering.

• Quality Inspection and Control
• Predictive Modeling
• Smart Manufacturing Systems
• +3 more

Dr. Yu (Chelsea) Jin is an Assistant Professor in the Department of Industrial Engineering at the University at Buffalo, specializing in quality inspection, predictive modeling, and data analytics for advanced manufacturing systems. She holds a PhD in Industrial Engineering from the University of Arkansas, an ME from the University of Michigan, and dual BS degrees in Network Engineering and Finance from Jinan University. Her research focuses on integrating machine learning and physics-based models to optimize manufacturing processes, such as additive manufacturing, PCB assembly, and pharmaceutical distribution systems. She has developed frameworks like ReflowNet for reflow oven optimization and physics-informed neural networks for thermal profile prediction. Her work emphasizes both theoretical advancements and practical applications in smart manufacturing and healthcare logistics. Dr. Jin's recent publications highlight contributions to generative AI for knowledge retrieval, AGV system optimization, and multi-source transfer learning for pandemic modeling. She actively collaborates with industry partners to bridge academic research and real-world manufacturing challenges.

Michael SandbergView profile

Assistant Professor

• Additive Manufacturing
• Composite Materials
• Digital Twins
• +3 more

Michael Sandberg is a Tenure Track Assistant Professor at the Department of Mechanical and Production Engineering Design and Manufacturing, Aarhus University (AU Engineering). His research bridges mechanical engineering and sustainable manufacturing technologies. Primary Affiliation: Aarhus University Department: Mechanical and Production Engineering Design and Manufacturing His work focuses on: Additive Manufacturing: Optimizing fiber orientation and process-induced stresses in 3D printing. Composite Materials: Studying compaction in pultrusion processes. Digital Twins: Advancing modeling techniques for industrial applications. Sustainable Design: Developing life-cycle engineering simulations for circular economy practices. Key trends in his publications include: Integration of digital twin platforms with industrial processes. Advancements in thermoset composite manufacturing. Innovations in large-scale additive manufacturing. Contact: ms@mpe.au.dk

Joe AlexandersenView profile

Associate Professor

• Computational Mechanics
• Topology Optimization
• Fluid Dynamics
• +5 more

Joe Alexandersen is an Associate Professor in the Department of Mechanical Engineering at the University of Southern Denmark (SDU), affiliated with the Institute of Mechanical and Electrical Engineering. His research spans structural optimization, heat transfer, fluid dynamics, and high-performance computing, with applications in heat sink design, microfluidic devices, and additive manufacturing. Research Interests Topology and shape optimization Conjugate heat transfer Navier-Stokes flow modeling Finite element methods High-performance computing Scientific Awards 2022 Fluids 2020 Best Paper Award 2017 DTU Young Researcher Award 2015 ISSMO/Springer Prize for Young Scientist Key Projects HiHeaT: Topology optimization for high heat flux components (2024–2027) Structural Analysis of Large Modular Vessels (2025–2027)

Sabine C. LangerView profile

Professor

• Acoustics
• Modeling and Simulation
• Numerical Acoustics
• +7 more

Prof. Dr.-Ing. Sabine C. Langer is a Full Professor of Acoustics and Director of the Institute of Acoustics at Technische Universität Braunschweig. She holds a PhD in Engineering and has extensive experience in academia, including leadership roles such as President of the Deutsche Gesellschaft für Akustik (DEGA) and Deputy Speaker of the DFG Collaborative Research Center 880 (SFB 880). Her research focuses on acoustics, numerical modeling, aircraft noise reduction, and innovative materials for sound absorption. She has pioneered studies on acoustic black holes, metamaterials, and AI-driven design optimization. Langer’s work also includes contributions to educational platforms, such as developing MATLAB-based sound quality analysis tools and online learning resources for engineering students. Education: Civil Engineering degree (1991–1996, TU Braunschweig), PhD in Engineering (2001, TU Braunschweig). Key positions include W2 Professor for Vibroacoustics (2013–2018) and Junior Professor for Wave Propagation and Building Acoustics (2003–2013). She led the Graduate School at SFB 880 and advised numerous research initiatives in structural acoustics and noise mitigation. Research interests span numerical acoustics, sound quality assessment, and sustainable acoustic design. Her recent work emphasizes AI integration in engineering design, stochastic modeling, and additive manufacturing of acoustic materials. She has published extensively on aircraft cabin noise prediction, vibration isolation, and metamaterial applications. Professional roles include membership in the DIN/VDI Normenausschuss Akustik and the Advisory Board of the Excellence Cluster Hearing4All. She has organized major acoustics conferences, including DAGA 2020 in Hannover, and contributed to standard-setting in noise reduction and vibration technology.

• Scientific Computing
• Computational Fluid Dynamics
• Finite Element Methods
• +3 more

Johan Jansson is an Associate Professor in Scientific Computing at KTH Royal Institute of Technology and BCAM (Basque Center for Applied Mathematics). He leads research in predictive Direct FEM Simulation (DFS) for aerodynamics and multiphase flows, and co-founded Icarus Digital Math as CEO. His work includes the FEniCS open-source finite element software project and MOOC-HPFEM educational initiatives. He holds roles as Director of the Center for Digital Math and collaborates internationally in computational science. Research focuses on high-performance computing (HPC), fluid-structure interaction (FSI), biomedical modeling, and renewable energy systems. Notable contributions include adaptive FEM frameworks for turbulent flow, vocal fold simulations, and wave energy converter modeling. His work bridges academic research with industrial applications, leveraging FEniCS-HPC and Unicorn solvers. Key achievements include election to the IVA Royal Swedish Academy of Sciences 100-list and securing the Severo Ochoa Center of Excellence Award. He has pioneered open-source tools like SimTek and contributed to major projects like the Salter Sink and vocal production modeling. Teaching responsibilities include courses on database technology, computational fluid mechanics, and research methodology. He actively engages in large-scale simulation projects involving marine energy, cardiac ablation protocols, and aerodynamic optimization.

• Structural Engineering
• Architecture
• Computational Design
• +4 more

Dr. Zhi Albert Li is a Postdoctoral Researcher at RMIT University's School of Engineering, affiliated with the Centre for Innovative Structures and Materials (CISM) under Emeritus Professor Mike Xie. His research focuses on integrating topology optimization with subjective preferences, extended reality, and advanced manufacturing. He holds a PhD from RMIT (2024) and a BFA in Environmental Design from Tianjin University (2018). Education: Bachelor of Fine Arts in Environmental Design, Tianjin University, China (2018) Ph.D. in Structural Topology Optimization, RMIT University, Australia (2024) Research Interests: Subjective preference-driven topology optimization Extended reality integration in design Complex architectural surface construction Articles Trends: His recent work emphasizes interactive design tools (e.g., iBESO), VR applications in structural optimization, and kinetic structures. Key themes include user-centric design systems and advanced manufacturing techniques. Awards: Postgraduate Research Excellence Award 2024 DNA Paris Design Award 2024 International 3D Printing Competition Third Prize 2020 Teaching and Advising: Albert has supervised undergraduate architecture projects at Tianjin University and lectured globally on computational design. He collaborates on the ARC Laureate Fellowship project and leads software development initiatives. Labs/Teams: Active in CISM at RMIT, focusing on innovative structural solutions and material applications.

Dong Jun (DJ) KimView profile

Senior Lecturer

• Materials Science
• Energy Storage
• Supramolecular Chemistry
• +5 more

Dr Dong Jun (DJ) Kim is a Senior Lecturer in the School of Chemistry at UNSW Sydney since 2023, focusing on the design and synthesis of supramolecular compounds for energy storage applications. Previously, he served as a Lecturer at the same institution from 2018 to 2023. Ph.D. in Materials Science and Engineering, KAIST (2015) B.Sc. in Materials Science and Engineering, Yonsei University (2010) His research bridges supramolecular chemistry and energy storage materials, particularly in developing organic rechargeable batteries, solid-state electrolytes, and graphene-based composites. He explores molecular pump systems, redox-active macrocycles, and sustainable synthesis methods. Recent publications highlight trends in solid-state battery technology, molecular self-assembly, and chiral material engineering. His work spans from fundamental molecular design to scalable manufacturing processes for practical energy applications. Scientific recognition includes the prestigious ARC Discovery Early Career Researcher Award (DECRA) 2021–2024. He has secured research grants from Australia's Economic Accelerator and UNSW Faculty of Science – Industry Network Seed Funding. Collaborations with global institutions and co-publications with researchers like Prof. J. Fraser Stoddart (Nobel Laureate) underscore his contributions to advancing battery technologies via supramolecular and nanoscale innovations.

David CollinsView profile

Associate Professor

• Materials Science
• Metallurgy
• Superalloys
• +4 more

Dr David Collins serves as the Mike Ashby Associate Professor in Materials Science at the Department of Materials Science and Metallurgy, University of Cambridge, and is a core member of the Rolls-Royce University Technology Centre (UTC) focused on advanced aerospace materials. His research spans superalloys , titanium alloys , and high-entropy alloys , with expertise in phase transformations , high-temperature deformation , and microstructural evolution . He pioneers advanced characterization techniques including in-situ synchrotron X-ray diffraction , electron backscatter diffraction (EBSD) , and three-dimensional X-ray diffraction (3DXRD) to investigate grain-scale stress interactions and failure mechanisms under extreme conditions. Analysis of his 2023-2025 publications reveals dominant trends in additive manufacturing validation , oxidation/corrosion resistance of superalloys , and grain-resolved mechanical behavior using coupled experimental-computational approaches. His work frequently addresses Rolls-Royce-relevant challenges in jet engine materials, particularly nickel-based superalloy performance under cyclic thermal-mechanical loading. No specific scientific awards for Dr Collins are mentioned in available departmental communications, though the Rolls-Royce UTC recently celebrated prizes for other researchers. Details regarding student supervision and grant funding are not publicly specified, but his position within the EPSRC- and Rolls-Royce-funded UTC indicates active involvement in large-scale collaborative research projects. As part of the Rolls-Royce UTC infrastructure, Dr Collins utilizes specialized facilities including electro-thermal mechanical testing rigs, cyclic oxidation test systems, and synchrotron beamline partnerships for real-time microstructural analysis during deformation and phase transformations.

Lawrence SassView profile

Professor

• Digital Fabrication
• Low-Cost Housing
• Construction Automation
• +3 more

Lawrence Sass is a Professor and Chair of the Computation Group in the Department of Architecture at MIT's School of Architecture + Planning. His research focuses on design innovation using digital fabrication, particularly in low-cost housing and construction automation. He pioneered methods to reduce home construction steps through computational tools, including the concept of Snap Assembly building systems showcased at MoMA in 2008. His work has inspired startups in digitally fabricated housing. B.Arch from Pratt Institute (1990) Master’s (1994) and PhD (2000) from MIT Research interests include sustainable construction techniques, 3D printing in architecture, and material optimization. He co-founded LuBan3D, a software system enabling large-scale 3D modeling with affordable tools. Current projects explore AI and robotic systems for home production. Awards include the prestigious MacVicar Faculty Fellow recognition. His teaching includes courses like Design Computation (4.500) and Tiny Fab (4.501), emphasizing computational methods in architectural design. Collaborations include work with Singapore-based researcher Prof. Lujie Chen on large-scale fabrication software. His lab focuses on integrating digital tools into physical production workflows, aiming to democratize construction through accessible fabrication technologies.

Santiago BadiaView profile

Professor

• Computational Science and Engineering
• Numerical Analysis
• Finite Element Methods
• +3 more

Santiago Badia is a Full Professor of Computational Science and Engineering at Universitat Politècnica de Catalunya (UPC), holding an adjoint researcher position at the International Center for Numerical Methods in Engineering (CIMNE). He leads the Large Scale Scientific Computing (LSSC) group at CIMNE, focusing on finite element methods, numerical analysis, and high-performance computing. His research emphasizes fluid dynamics, multiphysics problems, and scalable solvers for large-scale systems. Previously, he worked at Politecnico di Milano and Sandia National Labs. He developed the FEMPAR software framework, a parallel finite element tool for PDE simulations, achieving landmark scalability (e.g., 60 billion unknowns on 458,672 cores). FEMPAR is recognized in the High-Q Club of European codes. His expertise includes discontinuous Galerkin methods, XFEM, and domain decomposition preconditioners. Research interests span metal additive manufacturing, superconductor devices, and nuclear engineering applications. Awards include FEMPAR's High-Q Club inclusion. He advises PhD and MSc students (e.g., Jesus Bonilla, Eric Neiva, Marc Olm) and has open positions in postdoc/PhD levels. His team includes researchers like Javier Principe and Alberto Martín. Ongoing projects involve advancing parallel algorithms, multiphysics simulations, and software scalability for exascale computing.

Carmel MajidiView profile

Professor

• Soft Robotics
• Wearable Robotics
• Soft Electronics
• +12 more

Carmel Majidi is a Professor in the Department of Mechanical Engineering at Carnegie Mellon University's College of Engineering. He leads the Soft Machines Lab, where his research focuses on soft robotics, wearable computing, and advanced materials that mimic biological systems. His work enables robots and machines to safely interact with humans through soft, deformable technologies. Education: Ph.D. in EECS, University of California, Berkeley (2007) B.S. in Civil and Environmental Engineering, Cornell University (2001) His research interests span soft robotics, stretchable electronics, liquid metal materials, and bio-inspired engineering. He develops soft electromechanical materials for applications in haptics, medical devices, and human-machine interfaces. His group pioneers fabrication methods for soft composites and microfluidic systems that function as artificial skin, nervous tissue, and muscle. The recent trend in his publications highlights a strong focus on soft actuators, self-healing materials, liquid metal composites, and haptic interfaces for virtual and augmented reality. His work integrates materials science, robotics, and advanced manufacturing to enable scalable, robust, and practical soft systems. Scientific Awards: 2023 Inno Fire Award for Trailblazing Innovators, Pittsburgh Business Times Majidi leads a major research thrust in a new NSF Engineering Research Center (ERC) dedicated to improving robot dexterity, funded up to $52 million. He has been instrumental in developing soft robotic systems inspired by prehistoric organisms, such as the pleurocystitid, and in creating healthcare devices powered by body heat using liquid metal technologies. His research has been featured in Popular Science , Communications of the ACM , and Ars Technica . He is actively involved in advancing scalable manufacturing of soft electronics and enabling robust integration between soft materials and conventional microelectronics. His lab collaborates across disciplines to push the boundaries of physical AI and wearable robotics.

Ignacio Rios UribeView profile

Assistant Professor

• Behavioral Operations Management
• Mechanism Design
• Matching Markets
• +7 more

Ignacio Rios Uribe is an Assistant Professor at the Naveen Jindal School of Management (University of Texas at Dallas) specializing in Operations Management . He holds a PhD in Operations, Information and Technology (2020) from Stanford University, with additional MA in Economics from Stanford and MS/BS in Operations Research and Industrial Engineering from Universidad de Chile. PhD in Operations, Information and Technology (2020) - Stanford University MA in Economics (2020) - Stanford University MS in Operations Management (2014) - Universidad de Chile BS in Industrial Engineering (2014) - Universidad de Chile His research focuses on Behavioral Operations Management , particularly in matching markets , college admissions systems, and online platform optimization . Current projects examine mechanism design for dating apps, strategic behavior in college applications, team-building incentives, and charity donation systems. He employs mathematical modeling, field experiments, and structural estimation techniques. Recent publications analyze platform design for curated dating markets (M&SOM, 2023), stable matching with contingent priorities (Management Science, 2023), and capacity planning in school choice (Operations Research, 2022). His work combines theoretical analysis with empirical validation using real-world data from Chilean education systems and industry partners. Awards include First Place in Doing Good with Good OR (2018) and BOM Best Working Paper Competition (2023) Published in top journals like Management Science, M&SOM, Operations Research Professional affiliations with INFORMS and Manufacturing & Service Operations Management Society