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Johnson Goh Kuan EngView profile

Adjunct Professor

• Additive Manufacturing
• Atomic Precision Manufacturing
• Nanofabrication
• +6 more

Johnson Goh Kuan Eng is an Adjunct Professor affiliated with the National University of Singapore and based at the Institute of Materials Research and Engineering (IMRE), A*STAR . His research spans quantum physics, materials science, and nanotechnology, with a focus on 2D materials and quantum computing. Department: Quantum Technologies for Engineering (IMRE, A*STAR) Email: phygkej@nus.edu.sg , gohj@imre.a-star.edu.sg Research Interests: Dr. Goh's work investigates quantum confinement in 2D systems, dielectric properties for quantum devices, and nanofabrication techniques like scanning probe microscopy and molecular beam epitaxy. His studies also explore defect engineering, carrier injection, and spin-valley coupling for quantum computing applications. Publication Trends: His recent articles (2020–2021) emphasize 2D transition metal dichalcogenides (WS2, MoS2), leveraging quantum effects for next-generation electronics and computing. Topics include vacancy-induced conductivity tuning, contact optimization, and machine learning applications in material breakdown prediction. Advising & Collaborations: The text does not provide explicit details about advisees or grants, but his publications highlight collaborations with institutions like the University of New South Wales, A*STAR, and NUS.

• Microbiology
• Antimicrobial Resistance (AMR)
• Bacteriophage Therapy
• +3 more

Dr. Carola Venturini is a Lecturer at the Sydney School of Veterinary Science, University of Sydney. Her research focuses on microbiology, antimicrobial resistance (AMR), and bacteriophage therapy with a One Health perspective. She holds a BSc (Hons) from the University of Trieste and a PhD in Molecular Biology from the University of Wollongong. Her work investigates mobile genetic elements in bacterial pathogens and explores bacteriophage applications in animal and human health. Education: BSc (Hons) in Natural Sciences, University of Trieste PhD in Molecular Biology, University of Wollongong Research interests include: Evolution of drug-resistant pathogens Horizontal gene transfer mechanisms Bacteriophage-based interventions Microbiome ecology and antibiotic impacts Recent work highlights bacteriophage translocation in human colonoids, Vibrio harveyi pathogenesis in fish, and MDR Klebsiella pneumoniae clonal spread. Her studies bridge animal, human, and environmental health sectors. Grants include projects on phage formulations for animal infections, AMR surveillance in India, and collaborations with institutions in Germany, UK, USA, and Italy. Labs/Teams: Collaborates with the Westmead Institute for Medical Research and maintains international partnerships through the Sydney Southeast Asia Centre and Charles Perkins Centre.

Arthur F WitulskiView profile

Research Professor

• Radiation Effects on Electronic Devices
• Power Semiconductor Reliability
• Space System Radiation Hardening
• +3 more

Arthur F Witulski is a Research Professor of Electrical Engineering at Vanderbilt University's School of Engineering. He specializes in radiation effects on electronic power semiconductor devices and systems, focusing on radiation reliability in aerospace and nuclear environments. His research addresses challenges in satellites, robotics, and high-reliability power electronics. Education: PhD, MS, and BS in Electrical Engineering from the University of Colorado. Research Interests include radiation hardening of power electronics, semiconductor reliability under ionizing environments, and system-level modeling of radiation effects. His work spans energy systems, nano-materials, and risk mitigation strategies for complex engineering projects. Key contributions include developing models for SiC power device failures, Bayesian assurance frameworks for space systems, and methodologies linking component-level testing to system reliability. His recent articles emphasize single-event effects in advanced semiconductors and radiation tolerance in commercial-off-the-shelf (COTS) components. Witulski has pioneered radiation assurance tools for small satellites and robotic systems, emphasizing probabilistic modeling and fault-tolerant designs. His work integrates theoretical physics with practical engineering solutions for harsh radiation environments.

Thao NguyenView profile

Professor

• Biomechanics
• Polymer Engineering
• Materials Science
• +3 more

Thao (Vicky) Nguyen is a Professor of Mechanical Engineering at Johns Hopkins University, with a secondary appointment in the Department of Materials Science and Engineering. She is co-Deputy Director of the Hopkins Extreme Materials Institute (HEMI). Her research focuses on biomechanics of soft engineering and biological materials, including adaptive polymers, fracture mechanics, and ocular biomechanics related to glaucoma. Key collaborators include the National Eye Institute and National Science Foundation. Nguyen holds a B.S. from MIT (1998), and M.S. and Ph.D. from Stanford (2000, 2004). She previously worked at Sandia National Laboratories. Awards include the James R. Rice Medal (2025), NSF CAREER Award, and multiple ASME honors. Her lab integrates experimental and computational approaches, with notable work on shape-memory polymers and scleral biomechanics. Research interests include collagen growth, liquid crystal elastomers, and architected materials. She leads studies on optic nerve head mechanics, funded by DOD, NEI, and BrightFocus. Nguyen serves on editorial boards for ASME journals and professional societies.

Andrea WaltherView profile

Professor

• Nonlinear Optimization
• Algorithmic Differentiation
• Mathematical Optimization
• +3 more

Andrea Walther is a Professor of Mathematical Optimization at the Humboldt University of Berlin, holding a position within the Faculty of Mathematics and Natural Sciences. She leads the Mathematical Optimization research group at the Institute of Mathematics, focusing on algorithmic differentiation, nonlinear optimization, and applied mathematics. Her academic journey includes a Diploma in Business Mathematics (1996, University of Bayreuth), a PhD (1999, TU Dresden), and habilitation (2008, TU Dresden). She has held roles such as Junior Professor at TU Dresden (2007–2008) and Professor at the University of Paderborn (2009–2019) before joining Humboldt in 2019 as a MATH+ Professor. Education : 1991–1996: Studies in Business Mathematics, University of Bayreuth 1996: Diploma in Business Mathematics, University of Bayreuth 1999: PhD in Mathematics, TU Dresden 2008: Habilitation, TU Dresden Her research interests center on optimization methods, particularly algorithmic differentiation (e.g., ADOL-C software), nonsmooth optimization, and applications in engineering and machine learning. She leads initiatives like the Cluster of Excellence MATH+ and contributes to projects such as the Transregio 154. Key Projects: Co-PI of DFG Project 'Mixed-integer non-smooth optimization for gas market problems' (2020–2022) Principal Investigator in MATH+ Projects (EF3-7, AA2-7) Co-developer of ADOL-C, a widely used tool for algorithmic differentiation Notable awards include being a SIAM Fellow. Her work bridges theoretical advancements and practical applications, with contributions to energy sector optimization, inverse problems, and computational frameworks for solving complex systems.

Stephen E. GentView profile

Professor

• Conflict Processes
• International Relations
• Formal Theory
• +3 more

Stephen E. Gent is a Professor of Political Science at the University of North Carolina at Chapel Hill. He holds a B.A. from the University of Mississippi (1999), and M.A. and Ph.D. from the University of Rochester (2003, 2005). His research focuses on conflict processes, particularly the role of third parties in international and civil conflicts, and how economic competition drives territorial disputes. His influential 2021 book Market Power Politics examines how states pursue market dominance through conflict and mediation. Gent has also published widely in journals like the Journal of Politics and Journal of Conflict Resolution . Education : B.A., University of Mississippi, 1999 M.A., University of Rochester, 2003 Ph.D., University of Rochester, 2005 His research interests include mediation effectiveness, rebel group behavior, civilian victimization in war, and the strategic use of military intervention. He has received the 2022 Hedley Bull Prize in International Relations for his theoretical contributions. His work bridges formal theory, quantitative methods, and real-world case studies, with a focus on how power dynamics shape international conflict outcomes. Gent’s articles analyze topics like peace agreement durability, NGO accountability dilemmas, and the political economy of arbitration. His recent work addresses contemporary issues such as China’s South China Sea strategy and partisan polarization’s impact on U.S. foreign policy credibility. Awards : 2022 Hedley Bull Prize (European Consortium for Political Research) Grants/Advising : While specific grants are not detailed, his extensive publication record indicates sustained research funding. He has advised multiple students in political methodology and conflict studies, though explicit student names are not listed in available texts.

• Computational Materials Science
• Electronic Structure Theory
• High-Entropy Alloys
• +5 more

Stephan Schönecker is a Researcher and Associate Professor (Docent) at KTH Royal Institute of Technology, specializing in computational materials science and electronic structure theory. He holds key administrative roles including Studierektor (since January 2025) and Lokalt skyddsombud (2021–2024). His research focuses on multicomponent alloys, superconductivity, magnetism, and energy materials, with applications in nanotechnology and materials design. His academic background includes a strong foundation in theoretical physics and materials science. Research interests span bulk/interfacial properties of alloys, strain engineering in thin films, and ab initio treatments of magnetism and lattice vibrations. Notable contributions involve predicting novel materials through computational methods and exploring high-entropy alloys for magnetic refrigeration and structural applications. Recent publications highlight advancements in data-driven alloy design, magnetocaloric materials, and the mechanical behavior of refractory alloys. Collaborations with institutions like the Technical University of Denmark and Chinese universities reflect his international research network. His work bridges theoretical predictions with experimental validation, emphasizing both fundamental physics and practical engineering applications. Professional service includes roles in academic governance and union representation (Saco-S styrelseledamot, 2022–2025). His lab focuses on computational modeling and materials informatics, though specific lab names are not explicitly mentioned in the text.

• Nuclear Materials
• Radiation Damage Physics
• Computational Materials Science
• +4 more

Pär Olsson is a Professor in the Department of Nuclear Science & Engineering at KTH Royal Institute of Technology. His research focuses on computational and experimental studies of radiation damage in nuclear materials, with particular emphasis on understanding defect dynamics, microstructural evolution under irradiation, and the behavior of advanced nuclear fuels. He leads courses such as Multiscale Modeling of Nuclear Materials and Radiation Damage Physics, emphasizing both theoretical and practical aspects of materials science in nuclear contexts. His research interests include the development of advanced accident-tolerant fuels (e.g., UN-UO2 composites), the computational modeling of radiation effects in metals like Fe and W, and the interplay between solute atoms and defects in irradiated materials. His work combines first-principles calculations, kinetic Monte Carlo simulations, and experimental validation to address challenges in nuclear energy systems. Notable contributions include studies on fission product solubility in nuclear fuels, oxygen’s role in tungsten defect evolution, and the thermal performance of UN-based composites. His team’s projects, such as the M4F initiative (Multiscale Modelling for Fusion and Fission Materials), aim to bridge atomistic and continuum-scale models for material design. Pär Olsson collaborates extensively with international institutions and contributes to nuclear materials education through course coordination and supervision of graduate studies in physics and materials science.

Marcus KitchenView profile

Associate Professor

• Phase Contrast X-ray Imaging
• Compton Scatter Imaging
• Biomedical Imaging
• +4 more

Associate Professor Marcus Kitchen is affiliated with Monash University's School of Physics and Astronomy and the Victorian Heart Institute. He specializes in developing advanced X-ray imaging techniques, including Phase Contrast Imaging, Compton Scatter Imaging, and Ultra-Low Radiation Dose methods. His research focuses on enhancing diagnostic capabilities in lung and brain imaging while minimizing radiation exposure. Collaborations with institutions like the Hudson Institute aim to improve neonatal care, particularly for preterm infants with underdeveloped lungs. Key projects include translating synchrotron-based methodologies for clinical and industrial applications. Research interests span biomedical imaging, material discrimination, and radiation dose reduction. He leads or co-leads over 30 projects, including 'X-ray Scatter Imaging: Vast Information with Minimal Radiation' (2025–2028) and 'IMPACT: IMplementation of x-ray PhAse-Contrast Tomography to transform cancer diagnosis' (2022–2026). His work aligns with UN Sustainable Development Goals focused on health and innovation. Publications emphasize novel imaging modalities and their applications in respiratory and neurological disorders. Despite no explicit awards listed, his contributions to reducing radiation exposure and advancing lung mechanics research are significant. He supervises graduate students and actively seeks PhD candidates. His lab integrates theoretical, computational, and experimental approaches to bridge gaps between fundamental physics and clinical medicine.

John ToobyView profile

Professor

• Evolutionary Psychology
• Evolutionary Biology
• Cognitive Psychology
• +5 more

John Tooby is a Distinguished Professor of Anthropology at the University of California, Santa Barbara (UCSB), affiliated with the College of Letters and Science. He co-directs UCSB's Center for Evolutionary Psychology (CEP), where his research integrates evolutionary biology, cognitive science, and anthropology to study human nature. His work focuses on psychological adaptations for cooperation, coalitions, and social reasoning, with fieldwork in the Ecuadorian Amazon to study cross-cultural behavioral adaptations. Education: PhD from Harvard University. Research interests include evolutionary psychology's foundational theories, the evolution of sexual reproduction, and the design of cognitive mechanisms for social exchange. He has authored seminal works like Conceptual Foundations of Evolutionary Psychology and Universal Minds . Research highlights include mapping cognitive specializations for detecting cheaters, understanding shame and pride as adaptive emotions, and analyzing the evolutionary roots of political behavior. His publications emphasize evolutionary principles in explaining cultural phenomena and social institutions. Grants and labs: Maintains the CEP field station in the Amazon for cross-cultural studies. Collaborates on projects like the evolutionary basis of morality and the cognitive architecture of anger.

Kevin MylesView profile

Professor

• Arbovirus Transmission
• RNA Interference
• CRISPR Gene Drives
• +2 more

Kevin Myles is a Professor in the Department of Entomology at Texas A&M University's College of Agriculture & Life Sciences. His research investigates mosquito antiviral immunity and genetic control strategies for arbovirus vectors. With a Ph.D. in Microbiology from Colorado State University, his work integrates molecular virology, genomics, and bioinformatics to develop novel vector control methods. Research focuses on RNA interference pathways in mosquito defense, CRISPR-based gene drives for population control, and temperature effects on vector competence. Current projects engineer self-eliminating transgenes and characterize tissue-specific antiviral responses. Analysis of 15 publications reveals emphasis on genetic control technologies (53% of articles), mosquito immunity (27%), and climate-vector interactions (13%). Recent work increasingly addresses safety mechanisms for field applications. Leads development of computational tools like MGDrivE for simulating gene drive efficacy. Research has produced multiple genetic systems for precise modification of mosquito populations, with applications in dengue, Zika, and chikungunya control.

Ricardo Grau-CrespoView profile

Associate Professor

• Materials Science
• Computational Chemistry
• Energy Materials
• +3 more

Dr. Ricardo Grau-Crespo is an Associate Professor of Materials Theory and Lead of the Chemical Sciences Research Division at the University of Reading. He is affiliated with the School of Chemistry, Food, and Pharmacy within the Department of Chemistry, focusing on computational materials science for clean energy applications. His research explores molecular-level simulations to investigate materials for energy storage and environmental technologies. Key projects include studies on spinel ferrites, thermal conductivity in pyrochlores, and nanofluids for thermal energy systems. He leads the GCMT Group (https://gcmt-group.github.io/) and is active in advancing computational methods for materials discovery, including machine learning applications. His work bridges theory and experiment, with notable contributions to photocatalysis, thermoelectrics, and interfacial phenomena in nanomaterials. Research Themes: Environment, Energy Materials, and Computational Materials Science. Collaborations include experimental partners for validation of computational models. Active in high-throughput screening and AI-driven material design, emphasizing sustainability and energy efficiency.

Robert MacKayView profile

Professor

• Dynamical Systems
• Mathematical Physics
• Complexity Science
• +3 more

Robert MacKay is a Professor of Mathematics and Director of Mathematical Interdisciplinary Research at the University of Warwick. His work bridges pure and applied mathematics, focusing on dynamical systems, mathematical physics, and complexity science with applications to economics, engineering, and fusion energy. He leads the Warwick team in the Simons collaboration on Hidden Symmetry and Fusion Energy, addressing challenges in stellarator design. He teaches advanced courses like MA4H0 Applied Dynamical Systems and TCC Thermal Economics, the latter pioneering a thermodynamic approach to macroeconomics. His research interests include nonlinear dynamics, bifurcation theory, and applications to physics (e.g., plasma confinement), biology, and finance. Collaborations include work on magnetohydrodynamic equilibria and single-particle motion in non-axisymmetric magnetic fields. He has secured grants from EPSRC, Royal Society, and the Simons Foundation, supporting interdisciplinary projects such as the Mathematics of Complexity Science and Systems Biology (2009–2011). MacKay holds prestigious awards including Fellowships from the Royal Society (FRS), Institute of Physics (FInstP), and Institute of Mathematics and its Applications (FIMA). His recent work explores thermal macroeconomics, financial market dynamics, and geometric approaches to plasma confinement. He advises PhD students and postdocs in nonlinear dynamics and PDE theory, fostering the next generation of complexity scientists.

• Nonlinear Partial Differential Equations
• Calculus of Variations
• Materials Science
• +5 more

Robert V. Kohn is the Silver Professor of Mathematics at New York University, affiliated with the Courant Institute of Mathematical Sciences (CIMS). He holds academic positions within the Department of Mathematics at the College of Arts & Science and the Graduate School of Arts & Science. His research focuses on nonlinear partial differential equations (PDEs), calculus of variations, and their applications to materials science, thin elastic sheets, and machine learning. Education: Ph.D. in Mathematics from Princeton University (1979), M.Sc. from the University of Warwick (1975), and A.B. from Harvard University (1974). Research interests span elastic energy-driven pattern formation (e.g., wrinkling, folding), PDEs in machine learning (e.g., prediction with expert advice), and continuum mechanics. Recent work includes variational analysis of thin film mechanics and PDE-based approaches for binary sequence prediction. His articles explore topics ranging from metamaterials to stochastic growth models. Notable themes in his publications include energy minimization in materials, optimal control analogies in learning algorithms, and mathematical modeling of physical phenomena. While no formal awards are listed, his contributions to PDE theory and applied mathematics are widely recognized. Advising and grants details are not explicitly documented here.

Ayşe BaşarView profile

Professor

• Machine Learning
• Bayesian Inference
• Decision Making under Uncertainty
• +7 more

Ayşe Başar is a Professor in the Department of Mechanical, Industrial, and Mechatronics Engineering at Toronto Metropolitan University. She serves as Director of the Data Science Lab and Program Director of the Data Science Masters Program. Her research integrates machine learning and Bayesian methods to build predictive models and recommender systems, with applications in software engineering and healthcare. BSc, Boğaziçi University MASc, University of Alabama in Huntsville PhD, London School of Economics Her research focuses on advancing machine learning through Bayesian inference, deep reinforcement learning, and explainability. She develops models that simulate expert decision-making, particularly in complex environments like emergency rooms and software development. Her work emphasizes uncertainty quantification , social learning in networks , and evidence-based decision support systems . The selected publications reflect a strong trend in applying machine learning to real-world problems—particularly in software engineering defect prediction, healthcare team dynamics, and social network analysis. Her work consistently uses probabilistic modeling and ensemble methods to improve prediction accuracy and interpretability. Paper among top 3 most cited in Empirical Software Engineering Journal (2009–2014) Best Paper Award, AAAI (2010) Best Paper Award, IFIP/IEEE IM Symposium (2019) Best Paper Award, ESEM (2013) Dr. Başar actively supervises students and leads impactful research collaborations with institutions like St. Michael’s Hospital and IBM. She has held leadership roles including Director of Big Data for the Provost’s Office and Program Director for Data Analytics Certificates. She is an affiliated scientist at St. Michael’s Hospital and a research fellow at IBM CAS. She leads the Data Science Lab , which focuses on developing advanced machine learning models for complex decision-making. The lab works on projects involving large-scale data integration, predictive analytics, and human-in-the-loop AI systems.