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Joel RosenthalView profile

Professor

• Inorganic Chemistry
• Materials Chemistry
• Electrochemistry
• +7 more

Joel Rosenthal is Professor and Chair of the Department of Chemistry and Biochemistry at the University of Delaware, where he also serves as Associate Dean for Research and Graduate Affairs in the College of Arts and Sciences. His group integrates inorganic synthesis, electrochemistry, and photochemistry to create functional materials and catalysts for energy, environmental, and biomedical challenges. Education & Training B.S. with Honors, New York University (2001) Ph.D., Massachusetts Institute of Technology (2007) NIH Postdoctoral Fellow, MIT (2007-2010) Research Directions The Rosenthal Research Lab pursues four intertwined themes: Environmental & energy sustainability via CO₂ reduction and solar-to-fuel conversion. Design of catalytic platforms for small-molecule up-conversion. Light-activated therapeutics targeting cancer and other diseases. Electrosynthetic routes to advanced inorganic materials and coordination complexes. To tackle these goals, the group synthesizes non-traditional tetrapyrroles, porous inorganic frameworks, and metal alloys, then interrogates them with electrochemical, spectroscopic, and ultrafast methods in collaboration with colleagues across UD, other universities, and National Laboratories. Recent Publication Trends Between 2021-2025 the group has published extensively on (i) selective electrochemical CO₂ reduction using bismuth, tin, and alloy catalysts, (ii) structure–function relationships in palladium and ruthenium tetrapyrrole complexes for singlet-oxygen generation, and (iii) new metal–organic framework (MOF) electrosyntheses. The work bridges fundamental mechanistic insights with practical device demonstrations, including 3-D-printed flow cells and solar-powered reactors. Scientific Awards & Honors While specific awards are not enumerated in the provided text, Prof. Rosenthal has garnered recognition through sustained federal funding, invited colloquia, and extensive peer-reviewed publication records. Students, Collaborators & Infrastructure The group actively recruits graduate students, post-docs, and undergraduates interested in interdisciplinary research. Trainees gain expertise spanning chemical synthesis, electrochemical cell design, ultrafast spectroscopy, computational modeling, and biological assays through partnerships both on campus and at national user facilities. The lab maintains state-of-the-art instrumentation for electrochemistry, photochemistry, and materials characterization, and communicates its latest findings via Twitter @rosenthal_lab .

Marat I. LatypovView profile

Assistant Professor

• Materials Science
• Computational Materials Science
• Materials Informatics
• +4 more

Marat I. Latypov serves as Assistant Professor in the Department of Materials Science and Engineering at the University of Arizona's College of Engineering. He is also a member of the Applied Mathematics Graduate Interdisciplinary Program and leads the Materials Informatics Lab. His research spans computational materials science, sustainable alloy design, and machine learning applications for materials development. Dr. Latypov holds a PhD in Materials Science and Engineering from Pohang University of Science and Technology (POSTECH, South Korea, 2014) and a Dipl.-Ing. in Engineering Physics from Ufa State Aviation Technical University (Russia, 2011). His postdoctoral training included appointments at Georgia Tech/CNRS in France and the University of California, Santa Barbara. His research focuses on materials informatics , physics-informed machine learning , and sustainable structural alloys . Key methodologies include graph neural networks for polycrystal mechanics, vision transformers for microstructure representation, and adaptive experimental design for materials optimization. Recent work emphasizes circular economy applications through construction waste recycling and copper mine tailings valorization. Analysis of his publication record reveals strong emphasis on computational microstructure-property linkages (35% of recent work), machine learning for materials design (30%), and sustainable materials processing (25%), with growing integration of large language models for materials knowledge extraction. NSF CAREER Award (2025) : For damage control in recycled aluminum alloys ISTI Distinguished Faculty Scholar (2024) : At Los Alamos National Laboratory Novelis Hackathon First Prize (2021) : Computer vision application Acta Materialia Outstanding Reviewer (2018) Young Researcher Award (2017) : NanoSPD7 Conference Dr. Latypov advises PhD students including Herbold Fellow Zhuocheng Huang and leads projects funded by NSF and the Grantham Foundation. Current initiatives include chalcopyrite leaching optimization for copper mining and graph neural network development for fatigue prediction. His Materials Informatics Lab maintains collaborations with Los Alamos National Laboratory, MIT, and industry partners including Novelis. The lab operates at the intersection of metallurgy , machine learning , and high-performance computing , with capabilities spanning deep learning, Bayesian inference, and cloud-based computational infrastructure. Recent news highlights participation in CODAS-HEP summer school and publication of vision transformer work in Acta Materialia.

Anke KirchnerView profile

Researcher

• Superconductivity
• Magnetic Materials
• Thin Film Deposition
• +2 more

Dr. Anke Kirchner is a Researcher at the Leibniz Institute for Solid State and Materials Research Dresden (IFW Dresden) in the Department of Functional Oxide Layers and Superconductors. Her work focuses on superconducting materials, magnetic systems, and advanced thin-film deposition techniques for applications in levitation and energy-efficient transportation. Her research spans high-temperature superconductivity, nanocrystalline magnetic materials, and REBCO coated conductor development. Key contributions include optimizing artificial pinning centers in superconducting films, analyzing grain boundary structures in permanent magnets, and pioneering microacoustic sol atomization (MASA) for thin-film deposition. Her interdisciplinary approach bridges fundamental materials science with practical engineering applications in transportation and energy. Analysis of her 15 most recent publications (2000-2024) reveals consistent focus on superconducting levitation technologies and REBCO conductor performance enhancement. Her work demonstrates evolution from foundational studies of NdFeB magnet microstructures to cutting-edge innovations in coated conductor joints and tape-stack levitation systems, with strong emphasis on nanoscale characterization and process optimization. No scientific awards are mentioned in the provided text. Information regarding student advising, doctoral supervision, or research grants is not specified in the source material. The department specializes in oxide layer engineering and superconductor development, with Dr. Kirchner contributing to IFW Dresden's internationally recognized research on quantum levitation and magnet-superconductor interactions, frequently collaborating with Prof. L. Schultz on applied superconductivity projects.

Pavel P. KuksaView profile

Academic

• Bioinformatics
• Computer Science
• Functional Genomics
• +5 more

Pavel P. Kuksa is a Research Assistant Professor in the Department of Pathology and Laboratory Medicine, specializing in bioinformatics, computer science, and functional genomics. His work focuses on high-throughput sequencing analysis, chromatin interaction data, and developing scalable software platforms for genomics research.

NICOLA PESERICOView profile

Research Professor

• Integrated Optical Circuits
• Silicon Photonics
• Hardware for Machine Learning
• +4 more

Nicola Peserico is a Research Professor in the Department of Electrical & Computer Engineering at the University of Florida, affiliated with the College of Engineering. His primary research focus is on Integrated Optical Circuits and Silicon Photonics, with an emphasis on heterogeneous integration, hardware for Machine Learning/Neural Networks, and biosensing applications using integrated photonics. Education: Ph.D. (2018), M.S. (2014), and B.S. (2011) in Telecommunication Engineering from Politecnico di Milano. His research explores cutting-edge photonic technologies for accelerating neural networks, including Fourier-based convolution operations, reconfigurable circuits for solving PDEs, and energy-efficient optical interconnects. Recent work highlights advancements in photonic-electronic ICs, thermal management in photonic systems, and overcoming bottlenecks in memory and compute architectures. His publications emphasize photonic tensor cores, joint transform correlators, and silicon photonics integration for AI acceleration. Notable contributions include roadmap analyses for neuromorphic photonics and innovative packaging strategies for photonic neural network accelerators. No scientific awards or grants are explicitly listed in the provided texts. His advising record is not documented here. Labs/Teams: His work is part of broader efforts in photonic computing and AI hardware acceleration at the University of Florida, leveraging silicon photonics for next-generation computing systems.

• Clinical Genetics
• Molecular Genetics
• Neurodevelopmental Disorders
• +7 more

Rob Willemsen is an Associate Professor in the Department of Clinical Genetics at Erasmus MC, a leading academic medical center in the Netherlands. His research is centered on the molecular and genetic basis of neurodevelopmental and inherited disorders, with a focus on fragile X syndrome and related conditions. He employs advanced models such as zebrafish and in vivo systems to investigate gene regulation, methylation dynamics, and disease mechanisms. His research interests span clinical genetics , molecular genetics , neurodevelopmental disorders , epigenetic regulation , and rare genetic diseases . Using zebrafish models, he explores gene function and pathogenic variants associated with conditions like pediatric cardiomyopathy, hereditary spastic paraplegia, and refractive errors. His work often bridges basic science with translational applications, including drug testing in preclinical models. The trends in his recent publications indicate a strong focus on gene discovery , functional genomics , and therapeutic intervention for monogenic disorders. His studies frequently involve international collaborations and multidisciplinary teams, leveraging high-throughput sequencing, transcriptomics, and animal modeling to validate candidate genes from GWAS and clinical findings. Rob Willemsen has supervised 14 research projects, indicating an active role in mentoring students and junior researchers. He has received significant attention for his work, with mentions in news outlets and citations in major journals, though specific grants or funding sources are not detailed in the text. His collaborations span multiple institutions and countries, reflecting a broad scientific network. His research is conducted within the Clinical Genetics department at Erasmus MC, where he contributes to both fundamental research and potential clinical applications. While no specific lab name is mentioned, his work involves molecular and cellular analysis, animal models, and collaboration with clinical teams to translate findings into patient care.

Robert ThorneView profile

Professor

• Biological Physics
• Experimental Condensed Matter Physics
• Physics Education Research
• +7 more

Robert Thorne is a Professor in the Department of Physics at Cornell University's College of Arts and Sciences. His research spans biological physics, experimental condensed matter physics, and physics education innovations. He holds a B.Sc. from the University of Manitoba (1981) and a Ph.D. from the University of Illinois at Urbana (1987). Stephen H. Weiss Presidential Fellow (2011-present) Founder and CTO of MiTeGen LLC (2004-present) Research Interests: Thorne's work focuses on: Single-particle cryo-EM and time-resolved molecular movies Advanced X-ray crystallography and SAXS techniques Water/ice physics in biological and materials contexts X-ray fluorescence imaging for archaeology Physics education curriculum reform and outreach programs Publication Trends: His 15 most recent articles (2004-2021) demonstrate expertise in: Structural biology methodology Radiation damage mitigation Nanoconfined material behavior Cultural heritage imaging Physics education innovation Crystallography instrumentation Awards: Presidential Young Investigator (1988-1993) Alfred P. Sloan Fellow (1988-1990) Stephen H. Weiss Presidential Fellow (2011-present) Advising & Grants: Active mentor of M.S. student Myeonghak Lee and undergraduate Andrew DiFabbio . His research has received grants supporting student engagement and CHESS synchrotron upgrades.

David SuterView profile

Associate Professor

• Gene Regulation
• Cell Identity
• Transcriptional Memory
• +13 more

David Suter is an Associate Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Life Sciences (SV) and the Institute of Bioengineering (IBI-SV), leading the UPSUTER research unit focused on Gene Regulation & Cell Identity. He is based in the AI building at Station 19, Lausanne, and holds active teaching and leadership roles across multiple departments, including Life Sciences Engineering. He serves as Director of the Doctoral Program in Molecular Life Sciences (EDMS), and is a member of the Doctoral School Committee and the PhD Program Committee for Computational and Quantitative Biology. His research centers on the quantitative analysis of gene expression dynamics and cell identity, employing cutting-edge techniques such as ultrasensitive bioluminescence imaging, fluorescent protein timers, genome editing, and high-throughput genomics (ChIP-seq, ATAC-seq, CUT&RUN). His lab investigates transcriptional memory, proteostasis, transcription factor search dynamics, and cell fate decisions using embryonic stem cells and cancer cells as model systems. These approaches enable real-time, single-cell resolution studies of transcription factor behavior, mRNA production, and protein turnover across cell divisions. The publication trends in his work emphasize live-cell imaging, quantitative molecular biology, and systems-level understanding of gene regulation. His articles reflect a strong focus on visualizing and quantifying biological processes in living cells, particularly around transcription factors like Sox2 and their role in pluripotency and differentiation. The integration of biophysical tools with molecular biology allows his team to decode the mechanisms underlying cell identity maintenance and fate transitions. He actively supervises PhD students, both current and past, contributing significantly to doctoral education at EPFL. His leadership in the EDMS program underscores his commitment to training the next generation of scientists in molecular and quantitative life sciences. While no specific grants are mentioned in the text, his lab's advanced technological development (e.g., bioluminescence imaging tools) suggests strong funding support. David Suter leads the Suter Lab, a multidisciplinary research group combining molecular and cell biology with computational and biophysical methods. The lab fosters close collaborations and maintains a strong technical core in imaging and genomics, enabling innovative research on the fundamental principles of gene regulation during development and disease.

Robert J BrunnerView profile

Professor

• Data Science
• Machine Learning
• Statistical Analysis
• +3 more

Robert J. Brunner is a Professor at the University of Illinois with primary appointments in the Gies College of Business (Department of Accountancy) and the School of Information Sciences. He holds affiliate roles across multiple departments including Astronomy, Computer Science, and Statistics, as well as research centers like the Beckman Institute and NCSA. His research focuses on applying statistical/machine learning to solve complex problems in astronomy, finance, and large-scale data science. Education: Ph.D. in Astrophysics from Johns Hopkins University (advisor: Alex Szalay). Postdoctoral work at Caltech on the Digital Sky project. Research Interests: Machine learning applications, computational techniques, data management/visualization, and observational cosmology. His work bridges astrophysical data analysis with modern data science methodologies. Recent work includes developing spatio-temporal neural networks for forecasting, evaluating AI-driven financial analysis tools, and planning for the Vera C. Rubin Observatory. He collaborates internationally on large-scale surveys like the Dark Energy Survey and SDSS. Labs/Teams: Leads data science initiatives at the University of Illinois Research Park. Active in interdisciplinary teams at NCSA and Beckman Institute focusing on algorithm optimization and data-intensive research.

Wei GaoView profile

Associate Professor

• Cyber-Physical Systems
• On-Device AI
• Mobile and Embedded Computing
• +7 more

Wei Gao is an Associate Professor at the Swanson School of Engineering, University of Pittsburgh. His research focuses on the design, deployment, analysis and measurement of on-device AI architectures and algorithms on mobile, embedded and networked systems. He has strong interests in unveiling analytical principles underneath practical AI deployment problems, and designing systems based on these principles. The developed AI and system solutions are widely applied to various application scenarios, including Internet of Things, edge computing and smart health. Dr. Gao received his PhD from Pennsylvania State University in 2012 and his B.E. from the University of Science and Technology of China in 2005. Dr. Gao's research spans across Cyber-Physical Systems , Infrastructure Security , High Performance Computing , and the Distributed Governance of Information . His work particularly emphasizes on-device AI architectures and algorithms for mobile and embedded systems. He explores how to deploy AI efficiently on resource-constrained devices, with applications in Internet of Things, edge computing, and smart health. His research aims to bridge theoretical principles with practical system implementations, focusing on creating efficient, secure, and reliable AI solutions for real-world deployment scenarios. His recent work has increasingly focused on bringing Large Language Models to edge devices while maintaining performance and security. Analysis of Dr. Gao's recent publications (2021-2025) reveals a strong focus on on-device AI, particularly around Large Language Models for resource-constrained environments. His work addresses critical challenges including model personalization, security against illegal adaptation, sparse activation techniques, and physics-grounded generation. Much of his research targets making AI more efficient, secure, and practical for deployment on edge devices with limited computational resources, while also exploring applications in health monitoring and power systems. Dr. Gao has received significant recognition for his research, including: NSF Faculty Early Career Development (CAREER) Award (2016) Dr. Gao mentors numerous graduate students who contribute to his research in mobile computing, embedded systems, and on-device AI. His research has been supported by various grants, most notably the NSF CAREER award, enabling his team to explore innovative approaches to mobile and embedded AI systems. His lab investigates how to optimize AI for resource-constrained environments while maintaining performance and security, with particular focus on balancing computational efficiency with model accuracy. Dr. Gao leads a research group focused on mobile and embedded AI systems, with particular emphasis on making AI practical for deployment on everyday devices. His team explores novel techniques for model compression, efficient inference, and secure deployment of AI models on edge devices, with applications ranging from health monitoring to smart infrastructure.

Michael VeitView profile

Associate Professor

• Virology
• Viral Cell Biology
• Virus–Host Membrane Interactions
• +5 more

PD Dr. Michael Veit is an Associate Professor (Privatdozent) at the Institute of Virology, School of Veterinary Medicine, Freie Universität Berlin , where he heads the independent Research Group Veit – Cell Biology of Viral Infections . He is a faculty member of the Center for Infection Medicine and participates in the Berlin Equine Virus Lab (BEVL). Education & Training Doctorate (Dr. rer. nat.) in Virology/Biochemistry – exact institution not stated in text. Post-doctoral qualification (Privatdozent) awarded by Freie Universität Berlin. Research Focus Veit’s laboratory investigates the molecular and cellular biology of enveloped RNA viruses , with emphasis on virus–host membrane interactions and post-translational lipid modifications (S-acylation/palmitoylation). His group combines reverse genetics, live-cell imaging, mass spectrometry and structural approaches to dissect how viral glycoproteins are modified, trafficked and assembled into infectious particles. Model pathogens include influenza A, B, C and D viruses, coronaviruses (SARS-CoV-2, MERS-like CoVs, PHEV, PDCoV), arteriviruses (PRRSV, EAV), alphaviruses (Getah, CHIKV-like), and other emerging zoonotic agents. Publication Trends From 2020 to 2025 Veit has published >30 high-impact articles that cluster around four major themes: (i) coronavirus surveillance and zoonotic risk assessment , (ii) mechanistic dissection of protein acylation in influenza and arteriviruses , (iii) structure-function analysis of viral entry receptors (ACE2, LDLR), and (iv) development of reverse-genetic tools and reporter viruses for antiviral screening. Grants & Collaborative Networks Ongoing third-party funded projects coordinated by Veit are not explicitly listed in the text, but the continuous publication output and mention of “Current Collaborations” imply active grant support. He collaborates closely with other FU Berlin groups (Osterrieder, Kaufer, Azab) and international partners on coronavirus and influenza consortia. Laboratory & Teams The Research Group Veit comprises post-docs, PhD students and technicians working in BSL-2 and BSL-3 facilities at the Institute of Virology. Core platforms include confocal & FLIM microscopy, quantitative proteomics, and reverse-genetics suites for segmented RNA viruses.

• Cardiovascular Research
• Structural Biology
• Drug Design
• +7 more

Professor Alexander Breeze is a Chair in the School of Medicine at the University of Leeds, affiliated with the Multidisciplinary Cardiovascular Research Centre. His research focuses on structural biology, drug design, and molecular mechanisms of disease, particularly involving protein-protein interactions and NMR spectroscopy. Key areas include RAS oncogene inhibition, fibroblast growth factor receptors (FGFRs), and amyloid aggregation modulation. Education Background: Details of formal education not explicitly provided in the text, but extensive career history in structural biology and medicinal chemistry suggests advanced degrees in relevant fields. Research Interests: Professor Breeze’s work spans cardiovascular research, cancer biology, and infectious diseases. He develops novel therapeutics targeting oncogenic signaling pathways (e.g., RAS, FGFR) and investigates mechanisms of protein misfolding in amyloid diseases. His lab employs fragment-based drug design, NMR spectroscopy, and computational methods to study protein dynamics and drug interactions. Publications Overview: His recent work highlights advancements in small-molecule inhibitors for RAS proteins, CRACR2A genetic associations with COVID-19 severity, and modulation of amyloid aggregation pathways. Research trends emphasize translational applications, bridging basic science and clinical targets like cancer and neurodegenerative diseases. Awards & Recognition: No specific awards mentioned in the provided text, though his sustained high-impact publications suggest recognition in the field. Grants & Advising: Leadership in multidisciplinary cardiovascular research and training of early-career researchers through collaborative projects. No explicit grant details provided in this dataset. Labs & Teams: Active in the Multidisciplinary Cardiovascular Research Centre, fostering cross-departmental collaborations in cardiovascular and structural biology research.

Luke ChamberlainView profile

Professor

• Protein S-acylation
• Palmitoylation
• Post-translational modifications
• +12 more

Professor Luke Chamberlain is a leading researcher at the Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, where he investigates the role of protein S-acylation in health and disease. His work bridges fundamental biochemistry with therapeutic discovery, focusing on the zDHHC family of enzymes and their impact on cellular signaling, membrane trafficking, and disease mechanisms. Education: PhD in Role of Cysteine-String Protein in Regulated Exocytosis, University of Liverpool (1998) BSc in Microbiology, University of Edinburgh (1994) His research is primarily focused on protein S-acylation (palmitoylation) , a reversible lipid modification that regulates protein localization, stability, and function. He explores how defects in this process contribute to neurodegenerative diseases, cancer, and diabetes. His lab employs advanced techniques such as click chemistry, confocal microscopy, proteomics, and behavioral analyses to dissect molecular mechanisms. The recent publications highlight trends in understanding substrate specificity of zDHHC enzymes , development of inhibitors , and the regulatory role of S-acylation in metabolic and neurological pathways . His work increasingly emphasizes chemical biology approaches to target S-acylation therapeutically. Scientific Awards: No awards explicitly mentioned in the text. Prof. Chamberlain actively mentors postdoctoral researchers and prospective PhD students, offering support for fellowship applications. He is Principal Investigator on multiple grants, including an integrated analysis of S-acylation dynamics (BBSRC-funded) and a Strathclyde-led network with Thailand. His professional activities include serving as an examiner for PhD theses, chairing international conferences such as the FASEB meeting on Protein Lipidation, and participating in research visits to institutions like Tsinghua and Peking University. Labs and Facilities: His research group utilizes the Leica SP8 Confocal Microscope facility at the Strathclyde Institute, enabling high-resolution imaging of protein localization and dynamics in live and fixed cells.

Low Jun SiongView profile

Assistant Professor

• Immunology
• Cancer Biology
• Infectious Diseases
• +4 more

Assistant Professor Low Jun Siong is affiliated with the Department of Microbiology and Immunology at the National University of Singapore (NUS), under the Yong Loo Lin School of Medicine. His research focuses on understanding T and B cell biology in the context of infection, cancer, and autoimmunity. He collaborates with clinical partners to characterize immune cell responses in patient cohorts and explores strategies to manipulate these cells for therapeutic purposes. Key areas of interest include antigen specificity, immune cell dysfunction, and immune-based disease interventions. Education: Holds a BSc and PhD (specific disciplines unspecified). Affiliated with the Cancer Science Institute (CSI) and A*STAR Infectious Diseases Labs. His work spans translational immunology, virology, and cancer immunotherapy. Recent projects include studies on SARS-CoV-2 immune responses, tumor microenvironment interactions, and tropical sponge microbiome evolution. He employs high-throughput approaches and machine learning for immune profiling. Research highlights include: Characterizing T/B cell responses against pathogens and cancers Engineering immune cells for enhanced functionality Investigating antibody mechanisms against coronaviruses Dissecting metabolic influences on T cell efficacy in tumors Exploring symbiotic microbiome evolution in marine environments No specific grants or advising roles are detailed in the provided text. He contributes to collaborative initiatives like the Department Safety and Health Programme (DSHP) and the Department Microbial Culture Collection (DMCC).

• Neurodegenerative Diseases
• Alzheimer's Disease
• Tau Protein Biology
• +3 more

Dr. Charles Harrington is a Senior Research Fellow at the University of Aberdeen's School of Medicine, Medical Sciences and Nutrition. With a background in microbiology, he has transitioned to become a leading researcher in neurodegenerative diseases, particularly focusing on Alzheimer's disease and tau protein biology. His career spans over four decades, with significant contributions to understanding the molecular mechanisms of protein aggregation in neurodegenerative conditions. BSc (Hons) Microbiology, University of Glasgow (1977) PhD Microbiology, University of Glasgow (1980) Harrington's research interests center on the biology of tau protein in aging and Alzheimer's disease, with emphasis on diseases characterized by protein aggregation and methods to prevent these processes. His work has evolved from early studies on microbial cell walls to current investigations of tau pathology, demonstrating remarkable interdisciplinary expertise. He has developed assays for screening tau aggregation inhibitors and has extensively studied the therapeutic potential of hydromethylthionine. Analysis of his recent publications (2021-2025) reveals a strong focus on tau protein aggregation mechanisms, neuroinflammation, synaptic dysfunction in neurodegenerative diseases, and the therapeutic effects of tau aggregation inhibitors. His work frequently examines interactions between different therapeutic approaches, particularly how cholinesterase inhibitors might interfere with tau-targeting treatments. Harrington's research bridges molecular mechanisms with clinical applications, contributing significantly to the development of biomarkers and therapeutic strategies for Alzheimer's disease and related tauopathies. As Chief Scientific Officer for TauRx Therapeutics Ltd, Harrington oversees non-clinical activities for a company conducting phase 3 trials of hydromethylthionine. His collaborative work spans multiple international institutions, with numerous co-authors across neuroscience, biochemistry, and clinical research fields. While specific grant information isn't detailed in the provided text, his extensive publication record suggests substantial research funding support over his career. Harrington's laboratory work appears focused on tau transgenic mouse models, particularly investigating how tau pathology affects synaptic function, neurotransmitter systems, and behavioral outcomes. His research team has developed sophisticated methods for studying protein aggregation and its consequences in neurodegenerative disease models.