Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.
Dr. Christopher M. Wolverton is a Professor of Materials Science and Engineering at Northwestern University , where he leads the Wolverton Research Group . His work focuses on computational materials science with applications in energy sustainability , particularly in batteries , hydrogen storage , and thermoelectrics . PhD in Physics from University of California, Berkeley BS in Physics (summa cum laude) from University of Texas, Austin His research leverages first-principles quantum mechanical simulations and machine learning to enable virtual materials synthesis before laboratory testing. The group specializes in hybrid computational methods integrating Density Functional Theory (DFT) , Monte Carlo simulations , and phase-field microstructural models . The article portfolio shows leadership in energy storage materials , with recent work on data-driven nanoparticle facet control , mixed-anion semiconductors , and machine learning-accelerated discovery . Publications span top journals including Nature Energy , Nature Materials , and Science . 2006 Ford Motor Company Technical Achievement Award 2005 Ford Patent & Publication Awards 2003 Ford Environmental/Physical Sciences Recognition As advisor to PhD candidates Zhenpeng Yao , Shiqiang Hao , and Shane Patel , he fosters interdisciplinary research connecting materials informatics with experimental validation . The group maintains active collaborations with Argonne National Lab and MIT/Harvard teams.
Dane Morgan is a Professor in the Department of Materials Science & Engineering at the University of Wisconsin-Madison, College of Engineering. His research focuses on computational materials science for materials design, including ab initio electronic structure modeling, multiscale methods, and machine learning applications in materials discovery. His work spans nuclear materials, battery and fuel cell electrodes, and electronic materials. Education : PhD, 1998, University of California, Berkeley MS, 1994, University of California, Berkeley BA, 1992, Swarthmore College Research Interests : Computational materials science, ab initio methods for electronic structure and thermokinetics, machine learning for materials discovery, electrochemical systems modeling, and applications in nuclear materials, batteries, and electronic materials. His work integrates advanced computational techniques with experimental validation. Scientific Awards : 2024 APL Materials, Editors Pick 2023 Microscopy and Microanalysis Best Paper Award (Instrumentation and Software category) 2023 IEEE Transactions on Plasma Science Best Paper Award 2023 Kellet Mid-Career Award 2015 TMS Materials Genome Initiative Ambassador 2006 3M Technical Nontenured Faculty Grant
Jack Beuth is a Professor of Mechanical Engineering at Carnegie Mellon University (CMU), affiliated with the College of Engineering. He has been on the faculty since 1992 and leads the NextManufacturing Center, focusing on additive manufacturing (AM) research. His work emphasizes process mapping for AM, material science, and machine learning integration in manufacturing processes. Key affiliations include the Engineering Research Accelerator and the Manufacturing Futures Institute. Education: Ph.D. in Engineering Sciences, Harvard University (1992) M.S. in Engineering Sciences, Harvard University (1989) M.S. in Engineering Science and Mechanics, Virginia Tech (1987) B.S. in Engineering Science and Mechanics, Virginia Tech (1984) Research Interests: Additive Manufacturing (process modeling, material characterization, and defect analysis) Melt pool dynamics and thermal modeling Machine learning for process optimization and quality control Advanced materials for AM (e.g., Ti-6Al-4V, Inconel 718) His research has led to innovations like 'process map' approaches for AM, enabling better control over variables such as melt pool geometry and microstructure. Awards and Recognition: Ralph R. Teetor Educational Award (1998) George Tallman and Florence Barrett Ladd Development Professorship (2000) ASME Curriculum Innovation Award (2005) Benjamin Richard Teare Teaching Award (2009) Grants and Collaborations: $3.5M cooperative agreement with the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory (ARL) for AI-driven AM process optimization. Collaborations with Westinghouse Electric Company on 3D-printed nuclear components, such as spacer grids for pressurized water reactors. Labs and Teams: NextManufacturing Center: A research hub for AM innovation, emphasizing industrial partnerships and applied research. Beuth’s Additive Lab: Specializes in melt pool analysis, process mapping, and material behavior under AM conditions.
Dr. Lukas Frey is a Researcher at ETH Zurich, affiliated with the Chair of Physical Chemistry and the Institute of Molecular Physical Sciences (IMPS). His work focuses on biophysical studies of membrane proteins, lipid dynamics, and protein aggregation mechanisms. Key research areas include structural biology of ion channels, NMR spectroscopy of membrane proteins in nanodiscs, and the role of lipid environments in modulating protein dynamics. Frey employs advanced techniques like mass photometry and solid-state NMR to investigate molecular mechanisms in biological systems. His recent studies address amyloid fibril formation, pH-dependent α-synuclein polymorphism, and cholesterol-mediated modulation of membrane protein behavior. Based at the HCI F 228 facility in Zurich, Frey collaborates on projects involving lipid bilayer environments, ion channel function, and the structural basis of protein aggregation. His email is lukas.frey@phys.chem.ethz.ch, and he holds an ORCID identifier 0000-0002-1052-1104. Research contributions span from fundamental biophysical insights to methodological advancements in membrane protein analysis.
Gunnar Kusch is a Senior Research Associate at the Department of Materials Science & Metallurgy, University of Cambridge. His research focuses on defects in semiconductors, porous AlGaN materials, and advanced characterization techniques like cathodoluminescence (CL) and atom probe tomography (APT). He holds a PhD from the University of Strathclyde and leads projects on UV-B LED optimization, nanoscale defect behavior analysis, and semiconductor device design. His work bridges materials synthesis, characterization, and device performance, with applications in energy-efficient lighting and solar cell technology. Key research areas include: Defect engineering in III-nitride semiconductors Porous AlGaN templates for high-efficiency UV emitters Correlative microscopy techniques (CL, EBSD, APT) Composition-structure-property relationships in photovoltaic materials Notable contributions include developing CL-based methods for nanoscale defect analysis and demonstrating improved Cu(In,Ga)S₂ solar cell efficiencies through compositional engineering. His laboratory focuses on translating microscopic insights into macroscopic device improvements.
Chao Wang is an Associate Professor at the Department of Chemical and Biomolecular Engineering within the Whiting School of Engineering at Johns Hopkins University. He also serves as the Director of the Nano Energy Laboratory and the department’s Master’s Admissions Director. His research focuses on sustainable energy systems and nanomaterials for CO2 capture and conversion, electrocatalysis, thermocatalysis, and green chemical engineering. Education: Bachelor’s degree, University of Science and Technology of China (2004) Doctorate, Brown University (2009) Wang’s research targets efficient energy conversion and storage via nanomaterials with tailored atomic structures, emphasizing catalytic activity, selectivity, and stability. His group explores electrochemical and thermochemical processes for reduced carbon footprints, including CO2 and methane conversion, ammonia recovery, and phosphorus/nitrogen nutrient recycling using zeolite-based systems. Recent publications (2021–2024) highlight his work in high-entropy alloys, solid-state battery materials, CO2 electroreduction, and biomedical nanotechnologies. Collaborative efforts span catalysis, nanoparticle dynamics, and environmental applications. Grants include a $1M DOE award for multi-university research, a $625K DOE grant for electrified transportation systems, and $3M in startup funding for carbon-removal technology commercialization. Alumni under his mentorship include Ph.D. graduates like Michael J. Manto (2018) and Master’s students like Mitchell Keller (2018), with notable achievements in catalyst development for ammonia/phosphorus recovery and industry placements at Grace & Co. and GEA Engineering.
Thomas R Powers is a Professor of Engineering and Professor of Physics at Brown University. He joined Brown in 2000 as the first holder of the James R. Rice Term Chair in Solid Mechanics and has been an influential figure in soft matter physics, biomechanics, and microorganism locomotion. PhD in Physics, University of Pennsylvania (1995) BS in Physics and Mathematics, MIT (1989) His research focuses on soft matter systems, including colloidal and lipid bilayer membranes, liquid crystals, and active matter, with an emphasis on low-Reynolds-number hydrodynamics and geometric mechanics. His work has been supported by NSF grants, including collaborations with Brandeis University's bioinspired materials center. Recent publications explore microbial flagellar dynamics (e.g., Giardia lamblia ), chiral membrane behavior, and active gel responses to shear. Key keywords include soft matter, active matter, fluid mechanics, and microscale locomotion. Scientific honors include: Fellow, American Physical Society NSF CAREER Award (2001-2006) T. Francis Ogilvie Young Investigator Lectureship, MIT Ocean Engineering He has advised numerous students through courses like ENGN 2912F (Soft Matter) and ENGN 1210 (Biomechanics), while leading funded research on colloidal membranes and viscoelastic fluid interactions.
Dr. Robert O’Connor is an Assistant Professor at the School of Physical Sciences, Dublin City University (DCU) , specializing in interface chemistry and thin film characterization. His work bridges semiconductor physics and energy harvesting technologies , with a focus on materials like high-κ dielectrics and III-V substrates. BSc in Applied Physics (2001), DCU PhD in Semiconductor Physics (2005), DCU His research employs X-ray photoelectron spectroscopy (XPS) and atomic layer deposition (ALD) to study material interfaces in devices such as MOSFETs and photoelectrochemical systems . He leads a 4-year SFI-funded project on solar water splitting for hydrogen fuel and collaborates with Trinity College Dublin (SPOKE project) and IMEC, Belgium on area-selective deposition techniques. His lab utilizes a state-of-the-art integrated ALD-XPS tool . His scientific awards include the Marie Curie Intra-European Fellowship , Irish Research Council EMBARK Fellowship , and SFI TIDA Award . Publications span high-κ dielectrics , self-assembled monolayers , and block copolymer lithography , with recent work on graphene oxide heterostructures and recyclability in additive manufacturing . He supervises 5 postgraduate students and teaches modules like Final Year Project (PS451) and Solid State Physics I (PS204) . Collaborations include institutions such as IMEC and Trinity College Dublin , with tools like the integrated ALD-XPS system at DCU.
Dr. Zheng Yuan is an Associate Professor (Senior Lecturer) in the School of Computer Science at the University of Sheffield. Previously, they held roles as an Assistant Professor at King's College London and a Research Associate at the University of Cambridge's Department of Computer Science and Technology. Their primary research focuses on machine learning and deep learning applications in natural language processing (NLP), particularly in educational technology, healthcare, creativity, and multilingual contexts. Key projects include computer-assisted language learning (CALL), human-centered NLP in education, computational code-switching, and creative AI. Education includes a PhD and MPhil in Natural Language Processing from the University of Cambridge, and a BSc(Eng) from Queen Mary University of London. They hold affiliated positions at the University of Cambridge, King's College London, and are a Fellow of Trinity College, Cambridge. They contribute to The Alan Turing Institute's Data-Centric Engineering Programme and hold FHEA status (2024-). Research interests span educational NLP, multilingual systems, transfer learning, and explainable AI. They actively organize workshops and serve on editorial boards (e.g., PeerJ Computer Science) and conference committees (ACL/EMNLP). Recent activities include co-organizing NLP workshops at ACL 2025 and NAACL 2024, alongside roles in professional societies like the ACL Professional Conduct Committee. Awards include Fellowship of the Higher Education Academy (2024-) and ASEFClassNet18 Faculty Collaboration (2025-). They welcome PhD applications in NLP and machine learning, emphasizing interdisciplinary applications.
Nuri Yazdani is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich, Switzerland. Based at the Institute for Electronics (Institut für Elektronik) in Zurich, Dr. Yazdani contributes to both teaching and research in advanced materials and nanotechnology. His work spans multiple interdisciplinary areas connecting physics, chemistry, and electrical engineering, with particular emphasis on nanocrystal-based materials and their applications in electronics and optoelectronics. Dr. Yazdani's research focuses on the synthesis, characterization, and application of nanomaterials, particularly semiconductor nanocrystals and quantum dots. His work explores the fundamental physical properties of these materials, including exciton-phonon interactions, structural ordering in multicomponent systems, and charge transport mechanisms in nanocrystal assemblies. He investigates how nanoscale phenomena affect macroscopic material properties, with applications ranging from catalysis to optoelectronic devices. His approach combines experimental techniques like small-angle X-ray scattering with theoretical modeling to understand structure-property relationships in nanomaterials. Analysis of Dr. Yazdani's recent publications reveals a strong emphasis on perovskite and chalcogenide nanocrystals, with particular interest in how structural features like cation distribution, octahedral tilting, and surface chemistry affect optical and electronic properties. His work bridges fundamental physics with practical applications, spanning from quantum optics to energy conversion technologies. A recurring theme is the investigation of size-dependent phenomena and the role of phonons in determining material behavior at the nanoscale. Dr. Yazdani collaborates extensively with researchers across multiple institutions and disciplines, as evidenced by his authorship on numerous multi-investigator publications. His work appears in high-impact journals including Nature Communications, Journal of the American Chemical Society, and Nature Physics, reflecting the significance and interdisciplinary nature of his contributions to nanoscience and nanotechnology.
Turan Birol is an Associate Professor in the Department of Chemical Engineering and Materials Science at the University of Minnesota, with a secondary appointment in the School of Physics. He leads the Theoretical Materials Physics Group , focusing on computational materials design to discover exotic condensed matter phenomena. Education: PhD in Physics (Cornell University), Postdoc (Rutgers University) Research Areas: Ferroelectricity, Charge Density Waves, Multiferroics, Strongly Correlated Systems, Kagome Metals His work combines Density Functional Theory with Dynamical Mean Field Theory to study materials like perovskites, layered antiperovskites, and 2D/3D compounds. Recent projects include Office of Naval Research -funded ferroelectric design and NSF Discovery File -featured transparent conductors. Scientific contributions include 15+ recent articles on topics spanning structural chirality in superconductors, strain-tuned magnetism, and catalytic resonance theory. Former advisees include PhD graduates in Physics and Materials Science.
Justin Wan is a Professor in the Department of Computer Science at the University of Waterloo. His research focuses on scientific computing, medical image processing, computational finance, and machine learning. He holds a Ph.D. from UCLA (1998), an M.A. from UCLA (1995), and a B.Sc. from the Chinese University of Hong Kong (1992). Wan’s work bridges numerical methods, optimization, and deep learning, with applications in financial modeling, medical imaging, and fluid dynamics. His research interests include advanced techniques in scientific computing (e.g., multigrid methods), computer graphics simulation, and medical image enhancement (e.g., CT scan artifact reduction). He has pioneered applications of machine learning to computational finance, including option pricing and hedging using deep neural networks and GANs. His recent work explores denoising diffusion models and multi-agent systems for optimal execution in finance. Publications span topics like volatility surface computation, optimal mass transport for image registration, and parallel solvers for fluid dynamics. His methods address challenges in high-dimensional problems, robust numerical valuation, and scalable algorithms for large datasets. Wan collaborates across disciplines, integrating mathematical rigor with practical engineering solutions.
Cheuk Wai Tai is a Senior Staff Researcher at Stockholm University's Department of Environmental and Materials Chemistry since 2009. He manages the transmission electron microscopes and sample preparation equipment at the Electron Microscopy Center and serves as Section Editor for the Journal of Electronic Materials. His work focuses on quantitative structure characterization in functional materials research, particularly within nanoscience and nanotechnology contexts. Education: Ph.D. in Applied Physics, The Hong Kong Polytechnic University, 2004 M.Phil. in Applied Physics, The Hong Kong Polytechnic University, 2001 M.Sc. in Physics, The Chinese University of Hong Kong, 1998 B.Sc. (Hons) in Engineering Physics, The Hong Kong Polytechnic University, 1997 Dip. in Mechanical Engineering (Computer Aided Engineering), Institute of Vocational Education (formerly Haking Wong Technical Institute), Hong Kong, 1992 His research centers on structure-property relationships in functional materials through advanced electron microscopy techniques. Current specializations include Pair Distribution Function (ePDF) & Diffuse Scattering, Energy Materials characterization, and EM sample preparation methodology development. The group maintains strong focus on translating structural data into functional performance metrics for nanomaterials. Recent publications (2013-2019) demonstrate consistent emphasis on electron microscopy applications for energy storage materials (batteries, photocatalysts) and functional ceramics. Key trends include structural disorder analysis in piezoelectrics, development of quantitative TEM methods like SUePDF, and nanoscale characterization of electrocatalyst surface phases. His work bridges materials chemistry with advanced imaging techniques. Scientific recognition includes: Fellow of The Royal Microscopical Society (U.K.) Senior Member of IEEE Marie Curie Fellowship (2007-2009) from European Commission Sir Edward Youde Memorial Fellowship (2003/2004) from Hong Kong S.A.R. Government He teaches Solid State Chemistry (KZ7003) and leads Introduction to Analytical Electron Microscopy (KZ8009), having previously taught Advanced Transmission Electron Microscopy (KZ8010) before 2011. Major grants supporting his work include: "Quantitative structural characterisation using 3D electron-based pair distribution function" (Swedish Research Council) "A Multidimensional Toolkit for Modern Electron Microscopy" (Swedish Foundation for Strategic Research) "Mitigating Ni-rich Li-ion cathode side-reactions" (Swedish Energy Agency, Co-applicant) He leads the Cheuk-Wai Tai group within Stockholm University's chemistry department and oversees operations at the Electron Microscopy Center, where his team develops and applies advanced characterization techniques for functional materials research.
Dr Dongbin Wei is an Associate Professor at the School of Mechanical and Mechatronic Engineering , University of Technology Sydney (UTS), with a career spanning academia and industry. He holds a PhD in Materials Processing Engineering from the University of Science and Technology Beijing (2001) and academic appointments from 2005–2012 at the University of Wollongong (Research Fellow to Lecturer) and 2013–2017 at UTS (Senior Lecturer) before his promotion to Associate Professor in 2018. His research lies at the intersection of Mechanical Engineering , Manufacturing Engineering , and Materials Processing , focusing on: Ultrasonic Additive Manufacturing (UAM) Micro Metal Forming and Size Effects Tribology and Lubrication Numerical Simulations of Material Processing Composite Material Fabrication Key contributions include: Development of the Springback Path–Displacement Adjustment (SP-DA) method for stamping accuracy Advancements in femtosecond laser texturing for silicon wettability control Studies on nanolubrication in hot rolling Optimization of micro-deep drawing parameters He has secured competitive grants from the Australian Research Council (ARC) and industry partners like Weir Minerals Australia Ltd , including projects on: Revolutionizing mineral separation via additive manufacturing Super high-speed grinding technologies Mechanics of micro composite drill fabrication As a lead supervisor, he guided the 2022 thesis 'Creation and Validation of 3D Printable Mineral Separation Spiral' . His work bridges theoretical analysis, computational modeling (FEM/FEA), and practical validation in advanced manufacturing systems.
