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Jaewon LeeView profile

Assistant Professor

• Nanotechnology
• Self-Assembly
• Crystal Growth
• +5 more

Jaewon Lee is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of Missouri. He holds a PhD in Chemical Engineering from Purdue University and BS/MS degrees in Chemical Engineering from Yonsei University. His research focuses on understanding self-assembly mechanisms and crystal growth dynamics, with applications in photonics, energy storage, and biomedical technologies. Education: PhD in Chemical Engineering, Purdue University MS in Chemical Engineering, Yonsei University BS in Chemical Engineering, Yonsei University Research Interests: Jaewon Lee’s work explores the interplay between colloidal forces, nanoparticle dynamics, and material properties. His studies bridge fundamental nanotechnology with practical applications, including thermoelectric materials, energy storage systems, and biocompatible nanoparticles for diagnostics. Key areas include defect engineering in nanocrystals, phase-change material encapsulation, and real-time characterization of self-assembly processes. Awards: Excellent Academic Record, Yonsei University Outstanding Graduate Student in Cancer Research, SIRG Outstanding Postdoctoral Performance, Pacific Northwest National Lab Grants & Collaborations: Lee secured a $1.1M grant ($800K NSF + $300K university) to develop real-time microscale reaction visualization tools. He also collaborates with Samsung Advanced Institute of Technology and the Korea Institute of Chemical Engineers. Labs & Teams: His lab integrates advanced microscopy, computational modeling, and materials synthesis to address challenges in nanotechnology and energy systems. Research is conducted at the interface of chemical engineering and mechanical engineering disciplines.

Cory SimonView profile

Associate Professor

• Machine Learning
• Bayesian Optimization
• Computational Materials Science
• +3 more

Cory Simon serves as Associate Professor in the Department of Chemical, Biological, and Environmental Engineering within Oregon State University's College of Engineering. His research integrates machine learning, optimization, and chemical engineering to advance materials discovery and environmental sensing systems. His academic foundation includes a Ph.D. in Chemical Engineering from the University of California, Berkeley and a B.S. in Chemical Engineering from The University of Akron. Simon's work centers on Bayesian methodologies for scientific challenges, featuring: Bayesian optimization for adaptive materials synthesis Statistical inversion of physical systems with uncertainty quantification Computational design of nanoporous sensor arrays Stochastic algorithms for robotic environmental monitoring Recent publications demonstrate accelerating focus on multi-fidelity optimization for molecular design and atmospheric water harvesting, bridging chemical engineering with computational science through data-driven approaches. Leading The Simon Ensemble research group, Simon champions a versatile 'buffet-style' research philosophy—drawing from mathematics, statistical mechanics, and machine learning to address interdisciplinary problems across chemistry, materials science, and environmental engineering.

Barbara SharanowskiView profile

Professor

• Phylogenetic Systematics
• Insect Evolution
• Genomics
• +3 more

Barbara Sharanowski is a Professor in the Department of Biology at the University of Central Florida (College of Sciences). Her research integrates phylogenetics, genomics, and ecology to study parasitic Hymenoptera evolution, particularly Braconidae wasps, with applications in biodiversity conservation and biocontrol. She directs an active lab developing mobile tools for integrated pest management. Education includes advanced degrees in Entomology/Evolutionary Biology. Research focuses on: Macroevolutionary patterns in parasitic wasps Genome evolution and viral symbionts in insects Biocontrol optimization using digital solutions Publications emphasize insect systematics, with recent work exploring genomic adaptations in parasitoids and field applications for sustainable agriculture. Awards include leadership of the International Society of Hymenopterists and NSF grants. Mentorship spans 6+ graduate students studying wasp taxonomy and tri-trophic interactions. Lab activities include international fieldwork and bioinformatics tool development.

Dirk DorfsView profile

Associate Professor

• Colloidal nanoparticle synthesis
• Plasmonic materials
• Nanocrystal chemistry
• +5 more

Dr. Dirk Dorfs is an Associate Professor at Leibniz University Hannover, working within the Faculty of Natural Sciences at the Institute of Physical Chemistry and Electrochemistry. He serves as Group Leader of the Section Colloid Chemistry of Metals and Semiconductors, Spectroscopic Effects, and is part of the lecturing staff. His research spans multiple areas of nanoscience and physical chemistry with a particular focus on colloidal nanoparticle synthesis and characterization. Dr. Dorfs' primary research interests include shape and composition control in colloidal nanoparticle synthesis, alternative plasmonic materials, and temperature gradients on the nanometer scale. His work bridges fundamental nanomaterial science with practical applications in electrocatalysis, energy conversion, and optoelectronics. He has developed expertise in creating complex nanostructures including cryogels, semiconductor-metal hybrid systems, and plasmonic nanomaterials. His publication record demonstrates consistent research output over two decades, with recent work focusing on cryogel-based electrocatalysts, plasmonic nanocrystals, and semiconductor-metal hybrid systems. The research trends show a progression from fundamental nanocrystal synthesis to more applied materials for energy conversion and catalysis. Dr. Dorfs has contributed significantly to advances in colloidal chemistry, particularly in the areas of nanoparticle-based cryogels, plasmonic nanomaterials, and semiconductor heterostructures. His work has been published in high-impact journals including ACS Nano, Small, Journal of Physical Chemistry, and Advanced Materials. He leads research activities focused on developing novel nanomaterials with controlled properties for applications in energy conversion, catalysis, and optoelectronics. His group investigates the fundamental physical and chemical processes that govern nanomaterial behavior while developing practical applications for these advanced materials.

Andrew LloydView profile

Professor

• Drug Delivery Systems
• Biomedical Materials
• Medical Device Applications
• +5 more

Professor Andrew Lloyd is Deputy Vice-Chancellor at the University of Brighton, overseeing academic strategy, policy, and institutional leadership. He holds a Professorship in Biomedical Materials and has served in senior roles including Dean of the Faculty of Science and Engineering, Pro-Vice-Chancellor (Academic Operations), and Interim Vice-Chancellor. His research focuses on drug delivery systems, biomaterials for medical devices, and ophthalmic applications, with over 300 publications and funding from EPSRC, BBSRC, and industry partners. Education: BSc Natural Sciences (University of Cambridge, 1986), PhD in Biopharmaceutics (Brighton, 1989). Awards include the Patani Gold Medal (1990), Lilly Prize (1999), and multiple leadership roles in professional societies like the Royal Society of Chemistry and EPSRC Peer Review Council. He has advised pharmaceutical companies and co-founded Cellective Ltd for contract research in biomedical materials. Research interests emphasize novel materials for drug delivery, including contact lenses and anti-inflammatory nanocomposites. He has contributed to textbooks on drug targeting and serves on editorial boards for journals like Journal of Biomaterials Science . His voluntary roles include governance positions at schools and the Blond McIndoe Research Foundation. Key scientific awards include recognition for pharmaceutical research, biomaterials innovation, and educational leadership. His work bridges academia and industry, promoting regional economic growth through university partnerships.

Irina PaciView profile

Professor

• Self-assembly on solid surfaces
• Monte Carlo methods
• Multi-scale computational methods
• +3 more

Dr. Irina Paci is a Professor of Chemistry at the University of Victoria, specializing in theoretical and computational chemistry. Her research focuses on understanding molecular self-assembly processes, particularly at solid surfaces, and developing multi-scale computational methods to model materials' dynamic behavior under external fields. She holds a PhD from Queen's University and completed postdoctoral research at Queen's and Northwestern University. Her work integrates Monte Carlo simulations, density functional theory (DFT), and quantum chemistry to study surface adsorption mechanisms, catalytic reactions, and nanocomposite dielectric properties. Key areas include cysteine adsorption on gold surfaces, palladium-catalyzed cross-coupling reactions, and the impact of solvent effects on reaction pathways. Recent studies explore aluminum oxide degradation in perovskite solar cells and quantitative reactivity models for nucleophilic aromatic substitution. Teaching interests span physical chemistry, quantum mechanics, and computational methods. Dr. Paci leads the Paci Research Group, which includes graduate students like Archita Adluri and Natalie Stubb, focusing on advancing computational methodologies for energy materials and surface science. Her lab's work bridges fundamental theory with applications in nanotechnology and sustainable energy systems.

Martin WeberView profile

Professor

• Behavioral Finance
• Household Finance
• Decision Theory
• +1 more

Prof. Dr. Martin Weber is a Senior Professor at the Faculty of Business Administration (University of Mannheim) since 2017, focusing on Finance and Banking . He previously held professorships at the University of Cologne and University of Kiel. His research integrates Behavioral Finance , Decision Theory , and Experimental Economics to analyze deviations from classical financial models. Education : Not explicitly mentioned Research Interests : Weber’s work examines how psychological biases affect financial decisions. Key themes include mental accounting , trust in delegated investing , and dynamic inconsistency in risk preferences . He bridges empirical studies with behavioral modeling to understand market anomalies. Article Trends : His recent publications span Behavioral Finance (2025: Expectation Formation, Dividend Behavior) and interdisciplinary topics like Biomedical Engineering (2025: Artificial Knee Joint). The 2024 works include Health Economics and Retirement Timing , reflecting a broader interest in behavioral drivers across domains. Scientific Awards : Honorary Doctorate (Dr. hc) Teaching & Team : He oversees courses and theses at the Chair of Finance. The team includes researchers conducting experimental studies and policy-focused analyses, with collaboration in EU Cohesion Policy and Health in All Policies frameworks.

Cristian CiobanuView profile

Professor

• Nanoscale Surface Physics
• Two-Dimensional Materials
• Computational Materials Design
• +3 more

Cristian Ciobanu serves as Professor in the Department of Mechanical Engineering at Colorado School of Mines, where he has maintained continuous faculty appointment since 2004. His academic journey includes postdoctoral research at Brown University prior to joining Mines, with progressive promotions from Assistant to Associate to full Professor by 2014. Educational background: PhD in Physics, The Ohio State University (2001) MS in Physics, The Ohio State University (1998) BS in Physics, University of Bucharest (1995) His research program integrates computational and experimental approaches to address fundamental challenges in nanoscale surface physics and two-dimensional materials . Specialized expertise includes evolutionary algorithms for atomic structure optimization, development of materials for renewable energy applications, and investigation of self-organized nanostructures on crystal surfaces. Current work emphasizes machine learning applications in high-entropy alloy design and piezoelectric property engineering of layered systems. Publication trends reveal sustained focus on transition metal dichalcogenides, computational materials discovery, and piezoelectric response enhancement through alloying. Recent work increasingly incorporates machine learning for materials design while maintaining strong experimental validation through advanced microscopy and spectroscopy techniques. Key recognitions include: NSF Career Award (2009-2014) Research Excellence Award at Colorado School of Mines (2013) Fellow of the Institute of Physics (elected 2014) Ohio State Presidential Fellowship (2000-2001) Research funding has been secured through competitive mechanisms including the NSF Career Award, supporting his authorship of over 60 technical publications and a coauthored book on atomic structure determination. He actively advises graduate students in computational materials science and nanotechnology research within the Mechanical Engineering department. His scholarly activities are complemented by professional memberships in the Materials Research Society, American Physical Society, and American Vacuum Society. While specific laboratory facilities aren't detailed in source materials, his publication record indicates capabilities in computational modeling, scanning probe microscopy, and thin film characterization relevant to nanoscale materials research.

Angela YaoView profile

Associate Professor

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +3 more

Angela Yao is a Dean's Chair Associate Professor and Assistant Dean of Research at the National University of Singapore's School of Computing, Department of Computer Science. She leads the Computer Vision and Machine Learning Group and specializes in visual perception of people, focusing on both high-level semantics of human actions and lower-level physical modeling. Her research interests span Computer Vision , Machine Learning , and Artificial Intelligence , with specific expertise in human action recognition, 3D human modeling, video understanding, and small data AI. Dr. Yao's work bridges theoretical advances with practical applications, particularly in activity anticipation and human-computer interaction. Dr. Yao's publication trends reveal a strong focus on zero-shot learning for activity anticipation, 3D human modeling, and techniques for working with limited training data. Her research has evolved from foundational work in 3D pose estimation to more recent innovations in diffusion models and cross-modal learning, demonstrating consistent contributions to advancing computer vision capabilities. NRF Fellowship for Artificial Intelligence (2019) German Pattern Recognition (DAGM) Award (2018) Dr. Yao has successfully mentored PhD students including Fadime Sener and secured significant research funding including the NRF Fellowship. Her research group focuses on developing AI systems capable of understanding and anticipating human activities with applications in robotics and human-computer interaction. She teaches CS4243 Computer Vision and Pattern Recognition and leads the Computer Vision and Machine Learning Group at NUS Computing.

• Formal Verification and Control
• Safety-Critical Systems
• Machine Learning
• +5 more

Dr. Yulong Gao is an Assistant Professor in the Department of Electrical and Electronic Engineering at Imperial College London, affiliated with the Control and Power Research Group. He holds a B.E. in Automation from Beijing Institute of Technology (2013), M.E. in Control Science & Engineering (2016), and a joint Ph.D. in Electrical Engineering from KTH Royal Institute of Technology and Nanyang Technological University (2021). He has held postdoctoral positions at Oxford University and KTH. His research focuses on formal verification and control, machine learning, and their applications to safety-critical systems, including autonomous systems and control synthesis under uncertainty. His work emphasizes robust control strategies, data-driven optimization, and formal methods to ensure safety in dynamic systems. Recent publications address challenges in autonomous vehicle motion planning, risk-aware Bayesian neural networks, and adaptive task planning using temporal logic. He has contributed to stochastic modeling, distributed MPC, and resilient control under cyber-physical threats. Research affiliations include the Control and Power Research Group at Imperial College London, leveraging interdisciplinary collaboration to advance theoretical and applied control systems research.

• Lattice Dynamics
• Thermoelectrics
• Computational Chemistry
• +6 more

Jonathan Skelton is a Senior Lecturer in Computational and Theoretical Chemistry at the University of Manchester's School of Chemistry. He holds a Ph.D. in Computational Chemistry from the University of Cambridge (2010–2013) and a B.A. and M.Sc. in Natural Sciences from Trinity College, Cambridge (2006–2010). His research focuses on lattice dynamics and computational modeling of materials, particularly thermoelectrics, to enhance energy efficiency and sustainability. Education Ph.D. in Computational Chemistry, University of Cambridge (2010–2013) M.Sc. and B.A. Natural Sciences, Trinity College, University of Cambridge (2006–2010) Research Interests : Lattice dynamics, density-functional theory (DFT), thermoelectric materials, thermal transport, and computational materials design. His work emphasizes structural dynamics' role in material properties and the development of open-source tools for broader accessibility. Recent Research Trends : Recent publications explore thermoelectric properties of oxides (e.g., LaCoO₃), lanthanide frameworks, and 2D materials. His studies highlight advances in thermal conductivity reduction and phonon engineering for energy applications. Awards & Memberships : Associate Fellow of the UK Higher Education Academy, Member of the Royal Society of Chemistry. Grants & Supervision : Advised multiple PhD theses on topics like actinide systems and functional perovskites. Active in reviewing and conference participation. Labs & Collaborations : Works on open-source software development and collaborates globally on energy materials research.

Brent C. MelotView profile

Professor

• Materials Design
• Inorganic Chemistry
• Photovoltaics
• +3 more

Brent C. Melot is a Professor of Chemistry at the University of Southern California (USC), specifically within the Department of Chemistry at the USC Dornsife College of Letters, Arts and Sciences. He earned his Ph.D. and B.S. in Chemistry from the University of California, Santa Barbara in 2010 and 2006, respectively. His research focuses on materials design, including the synthesis and characterization of novel compounds for applications in photovoltaics, Li/Na/F-ion batteries, and heterogeneous catalysis. The Melot group emphasizes atomic structure analysis and functional property evaluation to advance sustainable energy technologies. His academic contributions span over two decades, with publications addressing topics such as metallic conductivity in frameworks, battery electrode materials, and anion redox mechanisms. While no specific awards are listed, his work reflects significant engagement with cutting-edge materials chemistry. The group operates a dedicated website detailing ongoing projects and collaborative opportunities. His research aligns with USC Dornsife's focus on interdisciplinary innovation, bridging chemistry, physics, and engineering to address global energy challenges.

Barry C. ThompsonView profile

Professor

• Organic Chemistry
• Polymer Science
• Photovoltaics
• +3 more

Barry C. Thompson is a Professor of Chemistry and Chair of the Department of Chemistry at the University of Southern California (USC), affiliated with the Loker Hydrocarbon Research Institute. He holds a Ph.D. from the University of Florida (2005) and a B.S. from the University of Rio Grande (2000). His research focuses on designing electroactive organic polymers, particularly for polymer-based solar cells and sustainable materials. Key projects include advancing Direct Arylation Polymerization (DArP) for conjugated polymers and exploring ternary blend photovoltaics. Thompson leads a research group with active grants from NSF, DOE, and industry. His lab includes advanced facilities like a nitrogen glove box, solar simulators, and analytical instruments. He has mentored numerous Ph.D. students and researchers, contributing over 120 peer-reviewed publications. Notable contributions include innovations in polymer synthesis, battery binders, and device engineering for renewable energy applications.

Kiyonori SuzukiView profile

Professor

• Magnetic Materials
• Nanocrystalline Materials
• Spintronics
• +3 more

Professor Kiyonori Suzuki is a faculty member in the Department of Materials Science and Engineering at Monash University. He holds the rank of Professor and is affiliated with the Faculty of Engineering. His research focuses on magnetic materials, particularly nanostructured soft magnetic materials and nanocomposite magnets, with applications in sustainable energy technologies such as hydrogen storage and electromagnetic devices. He has contributed to patents for nanocrystalline Fe-M-B alloys and developed the two-phase random anisotropy model. His work integrates advanced techniques like melt-spinning, neutron scattering, and atomic probe microscopy. Education: PhD, MEng, BEng, GCHE (details not specified). Research interests include magnetic properties of non-equilibrium materials, nanostructural formation mechanisms, and functional materials for energy applications. Key projects involve core loss mechanisms in soft magnetic nanostructures and hydrogen permeation alloys. He collaborates internationally and leads facilities like the National Hydrogen Materials Reference Facility. Notable contributions include patents on nanocrystalline alloys and foundational models in magnetic materials science. His publications span over 200 articles, emphasizing energy-efficient materials and advanced characterization techniques.

Claudio De PersisView profile

Professor

• Automatic Control
• Data-driven Control
• Cyber-Physical Systems
• +4 more

Claudio De Persis is a Professor in the Faculty of Science and Engineering at the University of Groningen, Netherlands. He holds a Laurea degree (cum laude) in Electrical Engineering from the University of Rome La Sapienza (1996) and a PhD in Control Systems (2000) from the same institution. His research focuses on automatic control, particularly data-driven control, nonlinear systems, cyber-physical systems, and energy systems. He has held academic positions at the University of Rome La Sapienza (2002–2011), the University of Twente (2009–2011), and currently leads the Groningen Center for Systems and Control within the Engineering and Technology Institute. His expertise includes fault detection in nonlinear systems, resilient control under Denial-of-Service attacks, and distributed control of energy networks. He has authored over 250 publications, including seminal works on quantized control and cyber-physical systems. He serves on editorial boards of journals like Automatica and IEEE Transactions on Automatic Control . De Persis has received two IEEE Outstanding Paper Awards for contributions to control theory. His research integrates control theory with data science, addressing challenges in smart grids and distributed systems. He holds patents for energy system control and collaborates on interdisciplinary projects, such as data center optimization and resilient networked systems. His current research emphasizes data-driven methods for controller synthesis, leveraging convex optimization and system identification to ensure stability and performance. He also explores privacy-preserving distributed control algorithms for power networks and aggregative games.