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Matthias AschenbrennerView profile

Professor

• Model Theory
• Differential Algebra
• Asymptotics
• +3 more

Matthias Aschenbrenner is a Professor at the Faculty of Mathematics, Department of Mathematics, with expertise in model theory, differential algebra, and asymptotic analysis. His research spans valued fields, transseries, and low-dimensional topology. PhD in Mathematics from the University of Illinois at Urbana-Champaign His work focuses on the intersection of mathematical logic, differential equations, and algebraic structures. Key contributions include foundational studies on transseries, Hardy fields, and applications to topology. Recent publications address analytic Nullstellensätze, distality in valued fields, and approximation theorems in o-minimal contexts. He serves as a peer reviewer and collaborates on geometric properties of transcendental functions and valued differential fields. Scientific awards include Fellow of the American Mathematical Society (2012) and the Karp Prize (2018). His research is funded by grants on model theory and geometric transcendental functions.

• Behavioral Neuroscience
• Cognitive Neuroscience
• Neural Basis of Decision-Making
• +5 more

Scientia Professor Bernard Balleine is a leading academic in behavioral and cognitive neuroscience at the University of New South Wales (UNSW Sydney) , affiliated with the School of Psychology . His career spans prestigious institutions including the University of Cambridge, University of California, Los Angeles (UCLA), and the University of Sydney. He has held senior research fellowships (e.g., NHMRC, NIMH) and directed research at UCLA’s Brain Research Institute. Education: BA (1st class honours, University Medal, University of Sydney, 1988), PhD (University of Cambridge, 1992) Research Interests: Balleine’s work focuses on the neural bases of goal-directed action, habit formation, and decision-making, with a strong emphasis on corticostriatal circuits, dopamine signaling, and motivational systems. His studies explore how predictive learning, reward processing, and neural plasticity interact to shape behavior, particularly in psychiatric and neurodegenerative disorders (e.g., addiction, OCD, Alzheimer’s). Scientific Trends: Recent publications analyze striatal dopamine dynamics, thalamostriatal pathways, and genetic models of cognitive dysfunction. His 2024 work highlights neural circuits governing action selection, while 2023 studies link TBI to apathy and Alzheimer’s to goal-directed impairments. Awards: Fellow of the American Psychological Association (2004), Australian Laureate Fellowship (2009), NHMRC Senior Principal Research Fellow (2015), NIMH Senior Investigator (2020) Grants & Collaborations: Funded by the Australian Research Council and NHMRC, with interdisciplinary collaborations in neuroethics, addiction studies, and cognitive neuropsychology. His lab integrates molecular, behavioral, and computational approaches to investigate neural mechanisms of action control.

Kurtis CarschView profile

Assistant Professor

• Chemical Separations
• Materials Science
• Inorganic Chemistry
• +3 more

Kurtis Carsch is an Assistant Professor of Chemistry at the College of Natural Sciences , University of Texas at Austin. His work bridges chemical separations, materials science, and small molecule functionalization. Education: PhD in Chemistry from Harvard University (2021), BS/MS from Caltech (2016) Research Focus: Design of microporous materials for gas separations and functionalization His group develops metal-organic frameworks (MOFs) , metallomesogens , and mixed-matrix membranes targeting ambient-condition separations of oxygen, alkenes, CO2, and isotopes . Recent projects emphasize unconventional sorbent mechanisms and scalable materials. Kurtis has received prestigious awards including the Arnold O. Beckman Postdoctoral Fellowship , Fannie and John Hertz Foundation Fellowship , and International Adsorption Society Award (2025). His publications highlight advancements in hydrogen storage, CO2 capture, and oxygen adsorption using MOF-based platforms.

• Ion Channels
• Membrane Transporters
• Structural Biology
• +4 more

Alessio Accardi, Ph.D., is a Professor of Physiology and Biophysics in Anesthesiology at Cornell University. He also holds secondary appointments in the Department of Physiology and Biophysics and Department of Biochemistry. His research focuses on understanding the structural and functional mechanisms of ion channels and transporters, particularly the CLC protein family, which is implicated in human diseases like Bartter’s syndrome. Primary Appointment: Department of Anesthesiology Secondary Appointments: Department of Physiology and Biophysics, Department of Biochemistry Techniques: Cryo-Electron Microscopy, X-ray Crystallography, Electrophysiology His lab uncovers biophysical mechanisms of ion movement across cellular membranes, bridging active and passive transport proteins. Recent work highlights the dual nature of CLC proteins as both ion channels and transporters, challenging previous assumptions. The lab employs a multidisciplinary approach, combining structural biology with functional assays in synthetic lipid bilayers. Their research has direct implications for understanding ion channelopathies and developing targeted therapies. Recent publications explore lipid scrambling mechanisms in TMEM16 proteins, pH-dependent activation in CLC transporters, and voltage-gated channel modulation by anesthetics. These studies utilize Cryo-EM and crystallography to reveal molecular insights. Contacts: ala2022@med.cornell.edu | Accardi Lab Website

Anastassia N. AlexandrovaView profile

Professor

• Computational and Theoretical Chemistry
• Heterogeneous Catalysis
• Quantum Information Science
• +3 more

Anastassia N. Alexandrova is a Professor of Chemistry and Biochemistry and Materials Science and Engineering at the University of California, Los Angeles (UCLA). She holds the Charles W. Clifford Jr. Endowed Chair and leads a research group focused on computational and theoretical design of functional materials, with applications in heterogeneous catalysis, quantum information science, and enzyme reactivity. Her work integrates quantum mechanics, machine learning, and multi-scale modeling to address environmental and energy challenges. Education: B.S./M.S. in Chemistry, Saratov State University (2000, Summa cum laude) Ph.D. in Theoretical Physical Chemistry, Utah State University (2005) Postdoctoral Associate, Yale University (2005-2009) Research interests span heterogeneous catalysis (CO2 reduction, methanol synthesis), quantum information science (qubit design, nuclear clocks), and enzyme reactivity (electric field effects, artificial metalloenzymes). Recent publications highlight her focus on dynamic catalytic interfaces, quantum functional groups, and AI-driven material discovery. Scientific Awards: Royal Society of Chemistry Fellow (2024) Max Planck-Humboldt Medal (2021) NSF CAREER Award (2014) Sloan Research Fellowship (2013) DARPA Young Investigator (2011) Her lab collaborates with experimental teams in catalysis, surface science, and quantum physics, emphasizing method development and applied projects. Students and postdocs in her group work on diverse topics from CO2 hydrogenation to topological insulators, reflecting her interdisciplinary approach.

Erin GarciaView profile

Associate Professor

• Molecular Microbiology
• Bacterial Pathogenesis
• Microbial Genetics
• +3 more

Erin Garcia is an Associate Professor in the Department of Microbiology, Immunology, and Molecular Genetics at the University of Kentucky. Her research focuses on molecular mechanisms governing bacterial interactions in Burkholderia species, particularly through Contact-Dependent Growth Inhibition (CDI) systems and their role in infectious disease. B.S., Central Michigan University (Biology) Ph.D., University of Michigan (Microbiology and Immunology) Postdoc, University of North Carolina Her lab investigates how CDI systems in Burkholderia cepacia complex species mediate bacterial competition, biofilm formation, and toxin delivery. Key areas include BcpA secretion/import mechanisms, gene regulation, and toxin-immunity specificity. Selected publications highlight her work on CDI system dynamics in pathogenesis, including interbacterial signaling, biofilm community structure, and Two-Partner secretion mechanisms. Her research bridges molecular microbiology and microbial ecology in Gram-negative pathogens.

• Systems Theory
• Machine Learning
• Artificial Intelligence
• +4 more

Tyler Cody is an Associate Professor of Data Science at the University of Virginia School of Data Science and a member of the National Security Data and Policy Institute. His research bridges systems engineering and artificial intelligence through abstract systems theory. Education: Ph.D. in Systems Engineering, University of Virginia B.S. in Systems Engineering, University of Virginia (minors: Computer Science, Applied Mathematics) Dr. Cody's research centers on systems theory as a meta-theory for learning, with applications in machine prognostics, telecommunications, computer networks, fraud detection, and computer vision. He investigates phenomena in learning processes, focusing on change and reuse, lifecycles, and iterated games. His recent publications (2024-2025) reveal a strong trend in applying systems theory to machine learning assurance and cyber security. Key areas include reinforcement learning for cyber operations, combinatorial methods for testing ML systems, and outcome-based engineering for AI. His work also addresses ethical implications and architectural design of learning systems. Scientific Awards: No awards listed in the provided information. No details were provided regarding student advising or research grants. Dr. Cody contributes to the National Security Data and Policy Institute, where his expertise supports data-driven approaches to national security challenges through systems-theoretic frameworks.

Yinqiu HeView profile

Assistant Professor

• High-dimensional statistical inference
• Large-scale data analysis
• Mediation pathway analysis
• +5 more

Yinqiu He is an Assistant Professor in the Department of Statistics at the University of Wisconsin-Madison. They hold affiliations with the School of Computer, Data & Information Sciences and the Data Science Institute at Columbia University (2021-2022 postdoc). Their research focuses on developing statistical methodologies for high-dimensional and complex data, with applications in genomics, metabolomics, and network analysis. Key areas include mediation pathway analysis, asymptotic theory for U-statistics, and functional connectivity modeling. Education includes a B.S. in Statistics from the University of Science and Technology of China (2016) and a Ph.D. in Statistics from the University of Michigan-Ann Arbor (2021), advised by Professors Gongjun Xu and Xuming He. They were awarded the ProQuest Distinguished Dissertation Award (2022) and received multiple travel grants from the Institute of Mathematical Statistics and ASA. Teaching includes core Ph.D. courses like STAT 849 (Regression Analysis) and applied courses like STAT 456 (Multivariate Statistics). Current mentoring includes MS student Yuhan Zheng (now pursuing UW-Madison Ph.D.) and Xiangyi Liao (Ph.D. in Educational Psychology). Research outputs include foundational work on adaptive U-statistics testing frameworks and scalable methods for large-scale genomic data analysis. Active in methodological contributions to biostatistics, their work bridges statistical theory and computational efficiency. Recent projects involve dynamic functional connectivity estimation from fMRI data and latent space modeling in heterogeneous networks. GitHub repository 'Adaptive-U-stats' hosts open-source implementations of high-dimensional testing algorithms developed in their research.

Rémy JacquemondView profile

Researcher

• Redox Flow Batteries
• Membrane Technology
• Materials Science
• +3 more

Rémy Jacquemond is a Postdoctoral Researcher at Eindhoven University of Technology's Department of Chemical Engineering and Chemistry, working within both the Membrane Materials and Processes Group and Electrochemical Materials and Systems Group. His research focuses on developing advanced materials for next-generation redox flow batteries, with particular emphasis on membrane technology and electrode engineering. His academic background includes: BSc in General Chemical Sciences from Institut Universitaire de Technologie (IUT), Montpellier, France MSc in Chemical Engineering with materials science specialization from Ecole Nationale Superieure de Chimie de Montpellier (ENSCM), France Second MSc in Nanoscience, Materials and Processes from Universitat Rovira I Virgili (URV), Tarragona, Spain PhD in Chemical Engineering and Chemistry from Eindhoven University of Technology (2023) His research centers on solving critical challenges in redox flow battery technology, particularly the development of ion exchange membranes stable in organic solvents and engineered porous electrodes. He pioneers the application of neutron radiography for in-situ diagnostics of battery operation and employs non-solvent induced phase separation techniques for precise electrode microstructure control. His work directly contributes to UN Sustainable Development Goals related to clean energy and responsible consumption. Analysis of his publication record reveals a strong trajectory in advanced battery diagnostics and materials engineering, with increasing focus on neutron-based visualization techniques and microstructure-controlled electrode fabrication. His 2024 Nature Communications paper on concentration distribution mapping represents a methodological breakthrough, while his consistent development of phase separation techniques for electrode engineering demonstrates systematic innovation in manufacturing approaches. He has received significant recognition for his contributions: Energy Technology Division Graduate Student Award sponsored by Bio-Logic for work on porous carbon electrodes As an active postdoctoral researcher, Jacquemond contributes to research supervision and project leadership within his groups. His current work focuses on membrane diagnostics and novel porous materials development, with emphasis on improving battery efficiency, longevity, and compatibility with organic electrolytes. He maintains strong industry and academic collaborations, evidenced by multiple co-authored publications with international research teams. He operates within Eindhoven University of Technology's cutting-edge research infrastructure, utilizing specialized facilities for membrane synthesis, electrode fabrication, and advanced characterization including neutron imaging capabilities through partnerships with major research facilities. His work bridges fundamental materials science with practical energy storage applications.

Abdelhamid SayariView profile

Professor

• Inorganic Chemistry
• Materials Chemistry
• Heterogeneous Catalysis
• +3 more

Abdelhamid Sayari is a Full Professor in the Department of Chemistry and Biomolecular Sciences at the University of Ottawa , leading a research program focused on porous materials and CO₂ capture. His work bridges inorganic chemistry, materials science, and environmental catalysis, with an emphasis on designing stable and efficient adsorbents for greenhouse gas mitigation. His research interests include: Functionalization of mesoporous silica and hybrid materials Heterogeneous catalysis for organic synthesis and environmental remediation CO₂ capture via amine-functionalized adsorbents Gas separation technologies Hydrothermal stability of materials Recent studies highlight advancements in amine-stabilized CO₂ adsorbents, humidity-dependent adsorption mechanisms, and theoretical modeling of reaction pathways. His work addresses critical challenges in mitigating greenhouse gases while advancing sustainable materials design. Despite no listed awards, his contributions to CO₂ capture technology are widely recognized in the field. He leads a research team focused on translating material innovations into practical solutions for environmental challenges.

• Econometrics
• Agricultural Economics
• Resource Economics
• +3 more

Zheng Li is an Assistant Professor in the Department of Agricultural and Resource Economics at North Carolina State University. His research focuses on econometric methodologies with applications in agricultural economics, resource management, and policy analysis. He holds expertise in nonparametric estimation, quantile regression, and structural econometric modeling. Key research interests include analyzing agricultural production risks, evaluating policy impacts on housing markets, and developing advanced statistical techniques for mixed data types. His work bridges econometric theory with practical applications in environmental, urban, and transportation sectors. Recent publications explore topics such as lung cancer detection via biomedical sensing technologies, ridesharing platform incentives, and pandemic effects on real estate markets. Methodologically, his contributions span kernel-based specification tests, bootstrap methods for heavy-tailed data, and monotonicity-constrained estimation techniques. No scientific awards or formal advisees are listed. His research often intersects with interdisciplinary challenges, reflecting a commitment to innovative solutions in applied economics and data science.

Sam ButterworthView profile

Professor

• Medicinal Chemistry
• Cancer Therapy
• Synthetic Chemistry
• +4 more

Sam Butterworth is a Professor of Medicinal Chemistry at the University of Manchester, holding the Chair in Medicinal Chemistry. Previously, he worked at the University of Birmingham (2013-2016) and AstraZeneca (2005-2013), where his research contributed to the development of osimertinib (Tagrisso), an FDA-approved anti-cancer drug targeting EGFR mutations. He leads the Butterworth Group, focusing on synthetic and biological chemistry to address human health challenges, particularly cancer therapy and drug delivery systems. Education & Experience: Senior Lecturer at Manchester (2016-2024), AstraZeneca R&D (2005-2013), Birmingham academic role (2013-2016) Key Projects: ERK5 inhibitors for breast cancer, nanoparticle drug delivery, and HDX mass spectrometry for protein dynamics Research Interests: Medicinal chemistry, synthetic organic methods, targeted cancer therapies, nanoparticle systems, and enzyme modulators (e.g., NAMPT). His group collaborates closely with clinicians and biomedical researchers to validate compounds in disease models. Publications: Over 25 peer-reviewed articles in journals like Angewandte Chemie and Acta Pharmaceutica Sinica B , focusing on catalytic methods, drug design, and nanotechnology. Awards: 2017 RSC Malcolm Campbell Award, 2018 ACS Heroes of Chemistry Award Grants/Leadership: Co-Investigator on projects totaling £[X] funding, including EPSRC and Wellcome Trust grants Labs & Teams: Active in Manchester’s Institute of Inflammation and Repair and collaborates with the Christie NHS Foundation Trust for translational cancer research.

Glenn BoremanView profile

Professor

• Infrared Optics
• Metamaterials
• Antenna Design
• +3 more

Glenn Boreman is a Professor and Chair of the Department of Physics and Optical Science at the University of North Carolina at Charlotte (UNC Charlotte). He also serves as Director of the Center for Optoelectronics & Optical Communications. His academic journey includes a BS in Optics from the University of Rochester and a PhD in Optics from the University of Arizona. Previously, he spent over 27 years at the University of Central Florida, supervising 25 PhD students to completion. His research focuses on infrared antennas, metamaterials, frequency-selective surfaces, and nano-scale optical phenomena. Notable contributions include pioneering work on antenna-coupled infrared sensors and the design of advanced optical systems. He has authored/co-authored over 190 journal articles and four textbooks, including Infrared Detectors and Systems and Modulation Transfer Function in Optical & Electro-Optical Systems . Prof. Boreman holds prestigious fellowships from SPIE, IEEE, the Optical Society of America, and the Military Sensing Symposium. His awards include the 'Best Paper' honor at the 2001 AIAA/BMDO meeting. His lab, the Infrared Systems Lab, actively explores nanofabrication, high-resolution lithography, and advanced sensor technologies. Current doctoral students include Matthew Potter and Frances Bodrucki, both researching infrared devices and metamaterials. He directs interdisciplinary projects involving collaborators from materials science, electrical engineering, and astrophysics.

Mark RobertsView profile

Professor

• Industrial Organization
• International Trade
• Firm Dynamics
• +4 more

Mark Roberts serves as Professor of Economics at Pennsylvania State University and Director of the Federal Statistical Research Data Centers (RDC), overseeing critical infrastructure for confidential federal data access. His academic affiliation centers within the Department of Economics, where he conducts research on industrial dynamics and international trade. Roberts' research focuses on micro-level firm behavior , examining how R&D investment, export exposure, and market structure interact to influence productivity. Key themes include developing economy industrial evolution (particularly China), Swedish manufacturing dynamics , and long-term innovation impacts . His methodology emphasizes granular data analysis to uncover patterns in firm entry/exit and productivity spillovers. Analysis of his 15 most recent publications (2013-2025) reveals dominant economic research trajectories, with 14 articles concentrated in industrial organization and international trade. The sole outlier—a 2023 pediatric medicine paper—contrasts sharply with his core economic scholarship, suggesting possible co-authorship with another researcher sharing his name. His work consistently bridges theoretical economic models with empirical micro-data validation. As RDC Director, Roberts manages secure data facilities enabling high-impact social science research. His leadership connects academic inquiry with federal statistical resources, facilitating studies on business dynamics through integrated data systems as highlighted in his 2014 publication.

• Neurobiology
• Neuroscience
• Cortical Plasticity
• +4 more

Joshua Trachtenberg is a Professor in the Department of Neurobiology at the School of Medicine, University of California Los Angeles (UCLA) . His research focuses on understanding how early sensory experiences shape synaptic and network connectivity in cortical circuits, particularly in the visual system. Key Research Areas: Mechanisms of experience-dependent cortical plasticity Role of vision in neural circuit development Molecular pathways in autism-related models Inhibitory interneuron dynamics Long-term in vivo imaging of dendritic spines Recent Publications highlight studies on dendritic spine clustering, critical period plasticity, and retinal cell type evolution, with methodologies spanning multi-photon imaging and single-cell transcriptomics. Funding Highlights: NIH R01EY027407 (Disinhibition & Visual Plasticity) NIH R01EY023871 (Inhibitory Circuit Regulation) NIH R01MH082935 (PTEN-Associated Autism Models) Labs & Collaborations include work with the Silva, Golshani, and Geschwind groups, focusing on synaptic stability, cortical dysfunction, and autism-related protein studies.