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David EggerView profile

Associate Professor

• Halide Perovskites
• Electronic Structure Theory
• Molecular Dynamics
• +6 more

Prof. Dr. David Egger is an Associate Professor at the Technical University of Munich (TUM) , leading the Associate Professorship of Theory of Functional Energy Materials under the TUM School of Natural Sciences . He joined TUM in 2019 as a Rudolf Mößbauer Professor and was promoted to Associate Professor in 2023. His work focuses on atomistic theories of energy materials , particularly solar cells , using electronic-structure and molecular-dynamics techniques to study molecules , solid-state materials , and nanoscale interfaces . His research interests span Halide Perovskites , Density Functional Theory , Machine Learning in Materials Science , and Optoelectronic Properties . Recent publications highlight advancements in machine-learning force fields for predicting dielectric properties and ion migration in energy materials, alongside studies on perovskite surface dynamics and phonon effects in solar energy conversion. Scientific Awards : Sofja-Kovalevskaja Award (2017) Best Thesis Award of TU Graz (2015) Koshland Prize (2014) Erwin Schrödinger Fellowship (2014) DOC Fellowship (2010) Teaching and Leadership : Prof. Egger teaches Computational Materials Physics and Advanced Topics in Theory of Functional Energy Materials . He serves as Executive Director of the Atomistic Modeling Center , fostering interdisciplinary research in energy materials.

Debabrota BasuView profile

Assistant Professor

• Machine Learning
• Reinforcement Learning
• Bandit Algorithms
• +6 more

Debabrota Basu is a tenured faculty member (Inria Starting Faculty Position - ISFP) at the Scool team (previously called SequeL) of Inria Centre at University of Lille in France. He teaches postgraduate-level courses on privacy, responsible machine learning, and research methods in AI at École normale supérieure-PSL University, Université de Lille, and Centrale Lille. He is also a member of the ELLIS Society (European Laboratory for Learning and Intelligent Systems) and the Paris unit of ELLIS. Dr. Basu earned his PhD in Computer Science from the Department of Computer Science, School of Computing, National University of Singapore, advised by Stéphane Bressan and Pierre Senellart. Prior to that, he obtained a B.E. degree with Honours in Electronics and Telecommunication Engineering from Jadavpur University. Before joining Inria, he was a postdoctoral researcher at Chalmers University of Technology's Data Science and AI Division. Dr. Basu's research focuses on constructing algorithms for developing efficient, robust, private, and ethical learning machines that solve real-world problems. His methodological approach blends statistics, machine learning, and optimization. His application interests span sustainable agro-ecology, medical and pharmaceutical applications, energy-efficient autonomous systems, and algorithmic audits. Recent collaborations include the Inria-Indian Statistical Institute associate team SeRAI for developing Sequential Testing and Learning Algorithms for Verifiably Robust and Responsible AI, and the Inria-INRAE collaboration on Resilient Agricultural Decision Making under Environmental Risks. His publication record demonstrates expertise in bandit algorithms, reinforcement learning, and privacy-preserving machine learning. Recent work shows a strong theoretical foundation with practical applications, particularly in pure exploration bandits, differential privacy mechanisms, constrained optimization, and fairness verification. His research bridges the gap between theoretical guarantees and real-world deployment challenges across multiple domains. Dr. Basu has received notable recognition for his contributions: Best Student Paper Award at ACM EAAMO 2022 for 'On Meritocracy in Optimal Set Selection' Young researcher (JCJC) grant from the French National Research Agency (ANR) in 2022 in 'Artificial Intelligence and Data Science' He leads the project 'RL under Real-life Constraints: Regrets and Algorithms' and supervises PhD students and postdoctoral researchers. His research is supported by multiple projects including REPUBLIC ('Vers l'IA responsable avec l'apprentissage par renforcement sous contraintes') and 'Foundations of robustness and reliability in artificial intelligence.' Dr. Basu actively collaborates with institutions worldwide, including establishing the RELIANT associate team with Kyoto University for investigating structured multi-armed bandit problems.

• Crystal structure determination
• Powder X-ray diffraction
• Solid-state NMR spectroscopy
• +6 more

Professor Kenneth Harris is a Distinguished Research Professor in the School of Chemistry at Cardiff University, specializing in the fundamental properties of solids and the development of advanced experimental techniques for materials characterization. His work bridges the gap between traditional crystallography and modern analytical methodologies, with a particular focus on overcoming limitations in structural analysis of complex materials. His research spans three primary interconnected themes: the development of techniques for determining crystal structures of organic solids directly from powder X-ray diffraction data; the advancement of in-situ solid-state NMR strategies for monitoring crystallization processes in real time; and the investigation of structural properties of anisotropic materials using polarized X-ray beam techniques, including the pioneering development of X-ray Birefringence Imaging (XBI). This work has significant implications for pharmaceutical development, materials science, and understanding biological crystallization processes. Analysis of his recent publications reveals a consistent trajectory toward increasingly sophisticated multi-technique approaches to materials characterization. His work increasingly integrates 3D electron diffraction, powder XRD, solid-state NMR, and computational methods like DFT calculations to solve previously intractable structural problems. A notable trend is the application of these methods to biologically relevant molecules (xanthine, riboflavin, L-tyrosine) and the development of techniques to monitor dynamic processes like crystallization and phase transitions in real time. His research demonstrates a shift from purely structural determination toward understanding the dynamic processes that govern material formation and transformation. Distinguished Research Professor title at Cardiff University Key contributor to the development of X-ray Birefringence Imaging Significant contributions to NMR crystallography methodologies Extensive publication record in top chemistry and materials science journals Professor Harris leads a research group focused on developing and applying cutting-edge techniques for materials characterization. His work has significant implications for pharmaceutical development, where understanding crystal structure and polymorphism is critical for drug efficacy and safety. His group has developed innovative approaches to monitor crystallization processes in real time, which has applications in both industrial manufacturing and understanding natural biomineralization processes. The group maintains strong collaborations with researchers across multiple disciplines, including physics, biology, and engineering, reflecting the interdisciplinary nature of modern materials science research.

HUANG LiView profile

Associate Professor

• Quantum Materials
• Novel Energy Materials
• Phase Selectivity under Nonequilibrium Conditions
• +7 more

HUANG Li is an Associate Professor in the Department of Physics at Southern University of Science and Technology (SUSTech) , where she has been since September 2019. She joined SUSTech in February 2013 as an Assistant Professor, advancing to her current rank. Her research focuses on quantum materials , novel energy materials , nonequilibrium phase selectivity , and surface/interfacial phenomena using first-principles computational methods and theoretical models . Educational Background: Ph.D. in Physics, Fudan University (2006) M.Sc. in Physics, Xiangtan University (2002) B.A. in Physics, Xiangtan University (1999) Research Interests span quantum materials (e.g., Moire superconductors , topological insulators ), novel energy materials (e.g., thermoelectrics , supercapacitors ), and surface/interfacial dynamics. Her recent work emphasizes two-dimensional systems , spin-valley-layer coupling , and nonequilibrium phase transitions in van der Waals heterostructures and metal-organic frameworks . Publications highlight her expertise in ab initio molecular dynamics , density functional theory , and quantum transport . Key trends include Moiré engineering in twisted bilayers, strain-tunable magnetism , and ferroelectricity in layered materials. Scientific Awards and Grants include leadership roles in projects funded by the National Natural Science Foundation of China and Shenzhen Science & Technology Commission . Notable grants address quantum state control in Moiré superlattices , nonlinear Hall effects , and thermoelectric performance enhancement . Professional Experience: Postdoctoral Research Associate at Ames Laboratory (2008–2012) Joint Postdoc at Georgia Institute of Technology & Ames Laboratory (2006–2008) Visiting Scholar at Harvard University & Oak Ridge National Laboratory (2004–2006)

John T. GrovesView profile

Professor

• Catalysis
• Synthesis
• Chemical Biology
• +3 more

John T. Groves is the Hugh Stott Taylor Chair of Chemistry and Professor of Chemistry at Princeton University, affiliated with the Department of Chemistry. His research bridges organic, inorganic, and biological chemistry, focusing on biomimetic catalysis, membrane-protein interactions, and radical-mediated transformations. He leads the Groves Group in the Frick Laboratory, collaborating with institutions like the Andlinger Center for Energy and Environment. Research interests include designing catalysts for energy and environmental applications, studying host-pathogen iron interactions via siderophores, and developing probes for peroxynitrite in biological systems. His work emphasizes metal-catalyzed processes, with notable contributions to methane oxidation, C-H functionalization, and enzyme-inspired chemistry. Dr. Groves has received over 50 honors, including the National Academy of Sciences membership (2012) and multiple ACS awards (e.g., 2015 Inorganic Chemistry Award). His research has led to innovations in fluorination, catalytic oxidation, and enzyme inhibition strategies. Key achievements include manganese-catalyzed fluorination techniques, iodate/chloride-driven alkane oxidation, and insights into cytochrome P450 mechanisms. His lab also investigates hypothetic applications in drug discovery and sustainable chemistry.

Tom PalmerView profile

Senior Lecturer

• Biostatistics
• Genetic Epidemiology
• Public Health
• +3 more

Dr. Tom Palmer is a Senior Lecturer in Biostatistics Applied to Genetics at the University of Bristol's Bristol Medical School. He holds advanced degrees including a PhD and specializes in biostatistical methodologies for genetic and epidemiological research. His work integrates Mendelian randomization techniques and large-scale observational studies, particularly focusing on cardiovascular diseases, diabetes, and the impacts of the SARS-CoV-2 pandemic. Palmer's research emphasizes causal inference and methodological innovations in public health, leveraging electronic health record systems like OpenSAFELY to analyze vaccine efficacy, post-infection complications, and chronic disease outcomes. His studies often involve large cohorts (e.g., 16 million people in England) and address critical questions about the long-term health effects of infectious diseases and vaccination strategies. Education: PG Cert, PhD, MSc, BSc (specific degree institutions not explicitly stated) Affiliations: Bristol Medical School (PHS), OpenSAFELY initiative His research interests include: Mendelian randomization and causal inference methods Genetic epidemiology of obesity, cardiovascular disease, and diabetes Evaluation of vaccine effectiveness and safety Public health responses to pandemics Palmer collaborates closely with leading epidemiologists and statisticians at the University of Bristol, including Professors George Davey Smith, Kate Tilling, and Jonathan Sterne. His work has significant implications for healthcare policy and clinical decision-making in post-pandemic and chronic disease management contexts.

Cindy Hsin-Liu KaoView profile

Assistant Professor

• Human-Computer Interaction
• Human-Robot Interaction
• Wearable Technology
• +4 more

Cindy Hsin-Liu Kao is an Assistant Professor in the Department of Design + Environmental Analysis at Cornell University. Her research focuses on human-centered design of wearable technologies, blending aesthetics and cultural perspectives into on-body interfaces. She leads Cindy's Lab , exploring topics like biodegradable e-textiles, sweat-sensing systems, and modular wearable frameworks. Dr. Kao earned a Ph.D. from the MIT Media Lab, followed by a Master's in Computer Science and dual Bachelor's degrees in Computer Science and Technology Management from National Taiwan University. Prior to academia, she worked at Microsoft Research developing cosmetics-inspired wearables. Her research interests span Hybrid Body Craft , emphasizing culturally inclusive design for wearables. Notable projects include texTENG (self-powered sensors) and MediKnit (medical-grade wearable devices). She has exhibited work globally, including at the Boston Museum of Fine Art and Dutch Design Week. Her work has garnered awards such as the ACM CHI Best Paper Honorable Mention and Fast Company Innovation by Design Finalist . Current projects investigate sustainable materials ( EcoThreads ) and collaborative robotics ( Weaved Inflatable Barriers ). Dr. Kao's lab actively explores intersections between technology and culture, with a focus on democratizing wearable prototyping through toolkits like SkinKit .

Grace YiView profile

Professor

• Statistical Methodology
• Measurement Error
• Causal Inference
• +3 more

Grace Yi is a Professor at the University of Western Ontario and holds a Tier I Canada Research Chair in Data Science. She is affiliated with the Departments of Statistical and Actuarial Sciences and Computer Science. Her research focuses on statistical methodology addressing challenges in measurement error, causal inference, missing data, and machine learning. Yi has authored influential works, including the monograph Statistical Analysis with Measurement Error or Misclassification and co-edited Handbook of Measurement Error Models . She has served as Co-Editor-in-Chief of The Electronic Journal of Statistics and President of the Statistical Society of Canada. Her accolades include the CRM-SSC Prize (2010), Fellowships from the IMS and ASA, and leadership roles in professional societies. Education: Ph.D. in Statistics (University of Toronto, 2000), M.A. in Statistics (York University, 1996), M.Sc. and B.Sc. in Mathematics (Sichuan University, China). Research Interests: Measurement error models, causal inference, high-dimensional data analysis, statistical machine learning. Yi’s work bridges theoretical advancements and practical applications, particularly in handling noisy data across disciplines like epidemiology and public health. Her recent studies include analysis of COVID-19 data dynamics and quarantine strategies. She has supervised numerous students and contributed to software development, including R packages like augSIMEX and swgee .

Simon MawhinneyView profile

Professor

• Composition
• Computer-assisted composition
• Electronic Music
• +3 more

Simon Mawhinney is a Professor in the School of Arts, English and Languages at Queen's University Belfast, specializing in composition with a focus on instrumental and electronic media. His work bridges complexist music, post-spectral harmonies, and cultural cantillation influences. Notable collaborations include projects with ensembles in Germany, France, and Iceland. He holds a Queen’s University Teaching Award (2012) and has pioneered modules on Messiaen’s music. His research explores new music performance, computer-assisted composition (using OpenMusic), and experimental technologies. Current roles include PhD supervision in composition, convening MA research methods modules, and undergraduate composition instruction. Key achievements include commissions from Ensemble Caput (Iceland) and Garth Knox/Quatuor Béla, resulting in works such as Marlacoo and a viola d’amore/string quartet piece premiered in Paris (2013). Recent projects involve recordings with pianist Mary Dullea and bass flutist Kolbeinn Bjarnason. His fingerprint research areas include labour studies in composition, technical performance practices, and avant-garde instrumentation. Over 35 compositions span decades, with 2016-2019 works emphasizing electronic integration and algorithmic processes. Awards include the AIC Composition Prize (2001) and Ann Driver Trust Award (2000). Professional service roles include Elected Member of the Academic Council since 2010 and Exams Liason Officer (2009-2011). Teaching: Undergraduate modules on Messiaen, Beethoven's late works, and composition techniques Research: Focus on postwar modernism, new musical technologies, and performance-based creation Public Engagement: Active in festivals, radio interviews, and international recitals

Zhen LiView profile

Assistant Professor

• Multiscale/Multiphysics modeling
• Soft matter and Smart materials
• Biophysics and Collective dynamics
• +7 more

Dr. Zhen Li is an Assistant Professor in the Department of Mechanical Engineering at Clemson University's College of Engineering, Computing and Applied Sciences. He joined Clemson in August 2019 after serving as a research associate professor at Brown University and a postdoctoral research associate at University of California, Merced. Education: Ph.D. in Fluid Mechanics, Shanghai University, 2012 MS in Fluid Mechanics, Shanghai University, 2008 BS in Engineering Mechanics, Wuhan University, 2005 Dr. Li's research focuses on multiscale modeling of soft matter, complex fluids, biophysics, and collective dynamics using both bottom-up (coarse-grained molecular modeling) and top-down (from continuum descriptions to fluctuating hydrodynamics) approaches, along with high-performance computing. His work spans mathematical theory for coarse-graining and model reduction, statistical methods and machine-learning approaches applied to multiscale modeling, memory effects in complex fluids, and concurrent coupling of heterogeneous solvers for scale-bridging. Analysis of Dr. Li's recent publications reveals a strong trend toward integrating machine learning with traditional computational methods, particularly neural operators for multiscale problems. His work spans diverse applications from bubble dynamics and blood flow to materials science and bioprinting, demonstrating the versatility of his computational approaches across multiple disciplines in engineering and physics. Awards and Recognition: CECAS Dean's Professor Award (2024) Award of Excellence - Junior Faculty (2021-2022) Best Research Poster Award at SC19 (2019) 2nd Place Award of Best Poster Presentation at DOE/EFRC AIM for Composites meeting (2024) Dr. Li actively mentors PhD students including Miles Lu, Ryan Wan, Haizhou Wen, and Ali Mohammadi, who have published significant research in computational mechanics. His research is supported by multiple grants including an NSF Elements grant as PI for 'SciMem: Enabling High Performance Multi-Scale Simulation on Big Memory Platforms', an NSF CDS&E grant as co-PI for 'HAM3R: Heterogeneous Automated Management of Multiscale Methods and Resources', a DOE/EFRC grant as Thrust lead co-PI for 'AIM for Composites', and a NASA EPSCoR grant as Science-PI. Dr. Li leads the MuthComp (Multiscale theory and Computation) research group, which focuses on developing interfaces between Engineering, Applied Mathematics, Physics-based Machine Learning, and High Performance Scientific Computing. The group has active collaborations with institutions including Idaho National Laboratory, University of Tokyo, and Brown University, and has developed open-source software including USERMESO for GPU-accelerated DPD simulations.

Luca Di GasperoView profile

Associate Professor

• Artificial Intelligence
• Combinatorial Optimization
• Metaheuristics
• +1 more

Luca Di Gaspero is an Associate Professor of Information Technology at the University of Udine, specializing in metaheuristic optimization techniques. His research enhances combinatorial optimization through hybridization of algorithms for scheduling, routing, and industrial applications. Research spans artificial intelligence in optimization, scheduling algorithms for manufacturing/healthcare, and metaheuristic framework development. Recent publications focus on LLMs in optimization, parallel batch scheduling, and energy-efficient manufacturing. Key Contributions: Developed EasyLocal++ framework for local search algorithms Advanced multi-neighborhood simulated annealing techniques Applied metaheuristics to healthcare logistics and emergency services

Yangchuan XingView profile

Professor

• Electrocatalysis
• Electrochemical Engineering
• Particle Technology
• +3 more

Yangchuan Xing is a Professor in the Department of Chemical and Biomedical Engineering at the University of Missouri, with an adjunct appointment in Mechanical and Aerospace Engineering (MAE). He holds a PhD from Yale University and a postdoctoral fellowship from Johns Hopkins University. His research focuses on advanced functional materials, electrocatalysis for fuel cells, and sustainable manufacturing of nanopowders. He has led over $5M in grants from NSF, DOE, and industry partners, and his work has been recognized with a named professorship (2025-2028). He teaches courses in transport phenomena, chemical reaction engineering, and process design. Education: PhD in Chemical Engineering, Yale University ME in Chemical Engineering, Chinese Academy of Sciences BE in Chemical Engineering, Northeastern University, China Research Interests: Dr. Xing’s work spans electrochemical energy storage systems (lithium-ion batteries, fuel cells), nanoparticle synthesis via flame spray pyrolysis, and nanocoating technologies for catalyst supports. He develops novel materials for CO₂ capture, optoelectronic devices using perovskite nanocrystals, and sustainable industrial processes. Key themes include defect engineering in materials and scalable production methods. Awards & Recognition: 2025: Named Professorship Appointment (University of Missouri) 2023: Engineering Faculty Award for Patented Technologies Lab & Collaborations: His laboratory focuses on material synthesis-structure-property relationships. Major collaborations include the Army Research Office (ARO) on battery materials and NSF-funded studies on perovskite optoelectronics. The 2023 lab renovation provided advanced characterization tools for nanoparticle research.

Augusto Luís Barros LopesView profile

Assistant Professor

• Materials Science and Engineering
• Electron Microscopy
• Microstructure Analysis
• +3 more

Augusto Luís Barros Lopes is an Assistant Professor in the Materials and Ceramic Engineering Department at the University of Aveiro since January 2009. Previously, he served as an Invited Assistant Professor at the same department (2004–2008). He holds a PhD in Materials Science and Engineering from the University of Aveiro (2001) and a Bachelor's in Ceramic and Glass Engineering (1989). He has been the Senior Technician responsible for the Electron Microscopy Service at the department (1991–2004). His research focuses on Materials Science and Engineering , with expertise in electron microscopy (SEM/TEM and EDS/PEELS) , microstructure-property relationships , and plastic deformation of materials . He teaches courses on metals, ceramics, characterization techniques, and mechanical properties. Key publications include studies on dual-phase steels, asymmetric rolling of aluminum alloys, and nanocomposite synthesis. He leads projects like EcoCerâmica (enhancing ceramics/crystal sector competitiveness) and FOCO (optimizing cabinet cooling). He advises PhD students and has collaborated internationally on materials processing and characterization. His work spans structural materials, energy-related materials, and advanced manufacturing techniques.

Mark R. MartenView profile

Professor

• Microbial Expression Systems
• Filamentous Fungi
• Proteomic Analysis
• +4 more

Mark R. Marten is a Professor and Department Chair at the University of Maryland, Baltimore County, in the College of Engineering and Information Technology, Department of Chemical, Biochemical and Environmental Engineering. He leads the Marten Lab, which focuses on understanding and manipulating microbial expression systems. Education: Ph.D. Chemical Engineering – Purdue University, 1991 M.S. Chemical Engineering – Purdue University, 1988 B.S. Chemical Engineering – State University of New York at Buffalo, 1986 Research interests center on fungal biology and biotechnology, particularly using advanced analytical tools like electron microscopy, atomic force microscopy, and proteomic analysis to study fungal cell walls and stress responses. Current projects investigate autophagy mechanisms and morphology-secretion relationships in filamentous fungi. His recent publications demonstrate a strong focus on Aspergillus nidulans cell wall stress responses, kinase signaling pathways, and mycelial material properties. Research integrates molecular biology with materials science, showing consistent themes in fungal adaptation mechanisms and biotechnological applications. Lab activities include collaborative projects on plant phenotype design, antifungal mechanisms, and nano-mechanical characterization of fungal structures.

Douglas AdamsonView profile

Professor

• Materials Synthesis
• Polymer Chemistry
• Graphene Applications
• +3 more

Douglas Adamson is a Professor in the Department of Chemistry at the University of Connecticut. His research focuses on materials synthesis, particularly on well-defined polymers and graphene-based composites. He utilizes high vacuum anionic polymerization and self-assembly techniques to create advanced materials with applications in energy storage, sensing, and environmental remediation. Ph.D., University of Southern California B.S., University of Evansville Research interests include: Graphene and 2D nanosheet composites Anionic polymerization for precision polymer architectures Conductive hydrogels and foams Bio-mimetic material design Flame-resistant polymer systems Recent publications highlight work on graphene-stabilized polyHIPE foams, conductive hydrogels, and bio-inspired polymer synthesis. His group explores the interplay between material microstructure and macroscopic properties through experimental and computational approaches. Lab and team activities center on creating novel polymer templates and scalable methods for graphene exfoliation. Projects include mineral separation technologies, wearable sensors, and self-assembled 3D graphene architectures.