جست‌وجوی استاد و پژوهشگر

• Theoretical and Computational Chemistry
• Physical Chemistry
• Biochemistry and Cell Biology
• +۷ مورد دیگر

Professor Ian Gould is a Senior Research Investigator in the Department of Chemistry at Imperial College London's Faculty of Natural Sciences. He has been affiliated with the university since March 1995 and is a co-founder of the Institute of Chemical Biology, which coordinates interdisciplinary research and teaching in chemical biology. His research focuses on computational chemical biology, with expertise in molecular dynamics simulations, quantum chemistry, and machine learning applications. Key projects include the development of the AMBER software package and lipid force fields (e.g., Lipid14 and Lipid21). He has pioneered the use of GPU-accelerated computing for large-scale biomolecular simulations. Dr. Gould's affiliations include the Agri Futures Lab, the CDT in Chemical Biology (as a supervisor), and the Centre for Translational Nutrition and Food Research. His work spans theoretical chemistry, membrane biophysics, and drug discovery, with applications in cardiology and nanotechnology. His career includes postdoctoral research at UCSF (1989–1992) and a research fellowship at the University of Manchester (1992–1995). He has maintained a decades-long association with the AMBER molecular dynamics platform, contributing to foundational force field development and computational methodologies.

• Forensics
• Toxicology
• Population Genetics
• +۶ مورد دیگر

Ivan Dolanc is a researcher at the Institute of Anthropology in Zagreb, Croatia, with a dual academic background in forensic science and chemical engineering. He holds a Master of Forensic Science (2012) and a BSc in Chemical Engineering (2010) from the Faculty of Chemistry and Chemical Technology at the University of Split. Forensics Toxicology Population Genetics Pharmacogenomics Gut Microbiota Analysis His research spans interdisciplinary domains, focusing on analytical chemistry applications in bioanthropology, toxicological burden analysis, and understanding interactions between environmental factors (e.g., heavy metals) and health outcomes during the COVID-19 pandemic. He has collaborated on international projects like unCoVer (HORIZON2020), CRIBS (Croatian Islands’ Birth Cohort Study), and MICROBIOCOV (gut microbiome in COVID-19 prognosis). Recent publications highlight his expertise in bioinformatics , cheminformatics , and mass spectrometry techniques (ICP-MS/MS, GC-MS/MS). He has also contributed to studies on dietary behavior during pandemics, leveraging the CRIBS cohort to explore maternal health impacts and neonatal outcomes. Ivan actively participates in scientific organization, serving on committees for international conferences on forensic genetics, auxology, and anthropology. His laboratory skills include DNA isolation , inductively coupled plasma mass spectrometry , and laser ablation .

Samantha Pearman-Kanzaمشاهده پروفایل

پژوهشگر ارشد

• Semantic Web
• Linked Data
• Ontologies
• +۸ مورد دیگر

Dr. Samantha Pearman-Kanza is a Principal Enterprise Fellow at the University of Southampton , specializing in the application of Semantic Web technologies and Artificial Intelligence to scientific domains. She leads the Careers and Skills for Data-driven Research (CaSDaR) project and serves as the Pathfinder Lead for Process Recording in the Physical Sciences Data Infrastructure (PSDI) initiative. Her work bridges computer science with chemistry , agriculture , and social sciences to enhance digital research environments. Research Focus: Digitisation of scientific research and knowledge management Development of electronic lab notebooks and smart laboratories Integration of IoT devices in scientific workflows Ontologies and linked data for cross-domain interoperability Ethical AI applications in food supply chains and education Key Achievements: Published interdisciplinary work in Science, Technology, & Human Values and the Journal of Cheminformatics Contributed to AI4Green4Students, advancing sustainable chemistry education through digital tools Collaborated on zombie cheminformatics projects for legacy data conversion Contact: S.Pearman-Kanza@soton.ac.uk

Arindam Chatterjeeمشاهده پروفایل

استادیار

• Drug discovery
• Computational chemistry
• Neurodegeneration
• +۲ مورد دیگر

Arindam Chatterjee is an Assistant Professor at the Notre Dame of Maryland University in the School of Pharmacy . He holds a Ph.D. in Medicinal Chemistry from the University of Mississippi and a B.S. (Honors) in Chemistry from Calcutta University. Ph.D. – Medicinal Chemistry, University of Mississippi M.S. – Medicinal Chemistry, University of Mississippi B.S. (Honors) – Chemistry, Calcutta University B.Tech. – Pharmaceutical Technology, Calcutta University His research focuses on drug discovery targeting neurodegeneration , oncology , and metabolic syndrome . He develops modulators for Kinase and Nuclear Hormone Receptors using virtual screening , medicinal chemistry , and computational methods . Recent work includes drug molecules for Alzheimer’s Disease , Cancer , Obesity , and Type 2 Diabetes . Key recent publications highlight ERR agonists for metabolic syndrome, REV-ERB agonists for nuclear receptor activation, and pan-ERR agonists for broad receptor targeting. His work integrates computational chemistry with structure-activity relationship studies. Scientific Awards: Intramural CFRD Grant $8328.00 for 2024-2025 Intramural CFRD Grant $6000.00 for 2023-2024 He actively collaborates with institutions like Vanderbilt University and Washington University of St. Louis , and contributes to American Chemical Society and International Alzheimer’s Association .

• Systems Biology
• Synthetic Biology
• Ubiquitin-Proteasome System
• +۵ مورد دیگر

Michael David Tyers is an Associate Professor at the Université de Montréal's Faculté de médecine and Département de médecine. He holds the Canada Research Chair in Systems and Synthetic Biology. His research focuses on understanding cellular networks' organization and control, particularly the ubiquitin-proteasome system's role in cell cycle regulation and cancer biology. Tyers leads the Systems and Synthetic Biology Unit at IRIC (Institut de recherche en immunologie et en cancérologie), developing chemical genetics and synthetic biology platforms for drug discovery and systems medicine. Education: PhD in Biochemistry (McMaster University), Postdoctoral training at Cold Spring Harbor Laboratory (NY). Previous roles include positions at the University of Toronto and University of Edinburgh. Research interests: Systems-level analysis of genetic networks, synthetic biology for antibiotic discovery, CRISPR-based genome-wide screens in human cancer cells, and chemical modulation of cellular pathways. His team combines proteomics, genetics, microscopy, and computational modeling to uncover therapeutic targets in cancer and infectious diseases. Key projects include developing synthetic biotic platforms for microbiome-based therapies, identifying genetic vulnerabilities in SARS-CoV-2, and discovering novel antibiotics using natural product-like compounds. Over 150 grants and collaborations span institutions like Génome Canada, NIH, and the Bill & Melinda Gates Foundation. Awards: Canada Research Chair (2018-2024), multiple grants from IRSC, CRSNG, and Apogée Canada.

Rahul Kumarمشاهده پروفایل

پژوهشگر

• Environmental Chemistry
• Environmental Health
• Wastewater-Based Epidemiology
• +۳ مورد دیگر

Dr. Rahul Kumar is a Research Scientist at the New York State Center for Clean Water Technology. He holds a Ph.D. in Civil Engineering from the University of Auckland (2020) and a master’s in Environmental Science and Engineering from IIT Dhanbad (2013). His postdoctoral training was conducted at Arizona State University’s Biodesign Center for Environmental Health Engineering. Dr. Kumar’s expertise spans Environmental Chemistry, Environmental Health, and Wastewater-Based Epidemiology (WBE), with a focus on monitoring public health threats through wastewater analysis and mitigating emerging contaminants in the environment. His work has been supported by prestigious scholarships from India, New Zealand, and the American Chemical Society. He is an active member of the American Chemical Society and a collaborator with the Institute for Health Metrics and Evaluation (IHME) on global burden of disease studies. His research integrates innovative methods for assessing community health trajectories, including the development of novel solutions for wastewater treatment and the application of WBE to track substance use and disease prevalence. Dr. Kumar’s contributions include advancing understanding of chemical contaminants’ environmental fate and their human health implications. He has also contributed to global epidemiological studies, such as analyzing mortality trends and cardiovascular disease burdens across populations. Key awards and recognitions include scholarships from the Ministry of Human Resource Development (India), Ministry of Foreign Affairs and Trade (New Zealand), and the American Chemical Society. His work emphasizes interdisciplinary collaboration, evidenced by projects in low-to-middle-income countries and open-access wastewater monitoring networks.

Rolf Fagerbergمشاهده پروفایل

استاد

• Algorithms
• Data Structures
• Computational Biology
• +۷ مورد دیگر

Rolf Fagerberg is a Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU). His research centers on algorithms, data structures, and their applications in computational biology and cheminformatics. His research interests include: Algorithms and data structures, particularly dynamic and geometric data structures Graph theory with emphasis on subgraphs, Yao graphs, and hypergraphs Algorithmic cheminformatics and modeling of chemical reaction networks Computational biology, including metabolic pathway analysis Theoretical computer science and discrete mathematics Recent publications highlight a strong trend toward interdisciplinary research combining computer science with chemistry and biology, particularly in modeling chemical reaction networks using hypergraphs and mixed-integer linear programming. His work also includes algorithmic solutions for palindromic subsequence problems and efficient extraction of reaction rules from large databases, reflecting a blend of theoretical and applied algorithm design. Rolf Fagerberg has served as senior coordinator on multiple research projects, including 'Algorithmic Cheminformatics' and 'Fundamental Data Structures', funded by the Danish Ministry of Higher Education and Research. He has also contributed to peer review and editorial work for major conferences such as the ACM Symposium on Parallelism in Algorithms and Architectures and the International Symposium on Experimental Algorithms. He has supervised PhD students and is actively involved in academic service, including membership in assessment committees at Aarhus University and IT University of Copenhagen. His research has received media attention, including coverage of a 'mathematical breakthrough' and applications in understanding intestinal systems in obesity.

• Cheminformatics
• Bioinformatics
• Perturbation-Theory Machine Learning
• +۱۰ مورد دیگر

Humbert González-Díaz is an Ikerbasque Research Professor at the University of the Basque Country (UPV/EHU), affiliated with the Faculty of Science and Technology, Department of Organic and Inorganic Chemistry, where he leads the CHEMIF.PTML LAB. His research integrates computational and theoretical methods into chemistry and biology, focusing on predictive modeling for drug discovery and complex systems. Research Interests: His primary research areas include Cheminformatics, Bioinformatics, Perturbation-Theory Machine Learning (PTML), Predictive Algorithms, Organic and Medicinal Chemistry, Pharmaceutical Sciences, Neurosciences, Nanotechnology, Biophysics, Biotechnology, Systems Biology, and Complex Networks. He develops machine learning models to predict molecular behavior and biological activity, contributing significantly to computational drug design and systems-level analysis of biological networks. Scientific Awards: Award for PhD in Organic Chemistry (2005) Multiple awards for published papers in scientific journals Advising and Grants: Humbert has supervised over 10 PhD theses and co-authored two patents and more than 10 scientific software tools. His research is funded by the Ministry of Science, Innovation and Universities, the Ministry of Economy, the Basque Government, the European Commission, and industrial partners, reflecting a strong record of competitive grant acquisition and impactful research translation. Labs and Teams: He leads the CHEMIF.PTML LAB at UPV/EHU, a research group dedicated to developing and applying PTML methods in cheminformatics and bioinformatics. The lab fosters interdisciplinary collaboration across chemistry, biology, and computer science, contributing to both theoretical advances and practical applications in pharmaceutical and biotechnological domains.

Andrey Golovمشاهده پروفایل

پژوهشگر

• Theoretical Materials Science
• Computational Chemistry
• Crystal Chemistry
• +۴ مورد دیگر

Andrey Golov is a Researcher at CIC energiGUNE, where he contributes to the Atomistic Modelling and Computational Studies group under Dr. Javier Carrasco. His work focuses on advancing computational methodologies for electrochemical energy storage materials, particularly through atomistic simulations and structural analysis of ion-conducting compounds. His academic foundation includes: Master's degree in Chemistry Science from Samara State University (Russia), completed in 2014 PhD from Samara National Research University (2019) under Prof. Vladislav A. Blatov, developing Voronoi partition algorithms for geometrical-topological analysis of crystal structures Postdoctoral research at Samara State Technical University (2019-2020) involving IonExplorer program development for ion diffusion analysis Golov's research integrates theoretical materials science with computational chemistry to address energy storage challenges. He specializes in high-throughput quantum mechanical simulations of fast ion conductors, geometrical-topological characterization of microporous crystalline materials, and graph theory applications for crystal structure design. His work establishes critical correlations between pore descriptors and physical-chemical properties in microporous compounds, directly supporting next-generation battery material development. No scientific awards or honors were documented in the source material. Information regarding graduate student advising, research grants, or collaborative projects beyond his core group activities was not disclosed in the available text. He operates within CIC energiGUNE's specialized research ecosystem, leveraging the Atomistic Modelling and Computational Studies group's infrastructure for electrochemical energy storage innovation, with particular emphasis on computational screening of inorganic conductors and solid-state phase transition modeling.

Mattia Felice Palermoمشاهده پروفایل

پژوهشگر

• Computational Chemistry
• Molecular Dynamics
• Quantum Mechanics
• +۵ مورد دیگر

Mattia Felice Palermo is a Researcher at CIC energiGUNE, where he joined in November 2023 as part of the Computational Modeling and Simulation group. Previously, he headed the Computational Chemistry group and served as IT Manager at GES - Green Energy Storage from 2021, and held post-doctoral positions at the University of Bologna. His career spans academia, industrial R&D at Sherwin-Williams Italy, and specialized energy storage research. His educational background includes: Ph.D. in Computational Chemistry from the Department of Industrial Chemistry at the University of Bologna (2015) Dr. Palermo specializes in computational prediction of energy material properties using Molecular Dynamics and Quantum Mechanical simulations, with expertise in high-throughput screening workflows for electrolytes and redox flow batteries. His methodological approach integrates cheminformatics with materials science to optimize energy storage systems. His research trajectory demonstrates consistent focus on liquid crystalline materials, coating formulations, and polymer chemistry, evolving toward industrial-scale energy applications. Current work emphasizes computational modeling of electrochemical properties for next-generation batteries. No scientific awards or student advising details are documented in the source material. At GES, he led HPC infrastructure development and technological strategy implementation while directing computational chemistry research. His dual expertise in simulation workflows and IT management enables cross-functional leadership in energy storage innovation at CIC energiGUNE.

• Cheminformatics
• Machine Learning
• Pharmacology
• +۳ مورد دیگر

Tianshi Yu is a Postdoctoral Researcher at the School of Pharmacy , University of Kansas, affiliated with the Wang Lab . Their research focuses on applying machine learning and cheminformatics approaches to drug discovery and pharmacological studies, particularly in the areas of enzyme inhibition, neuropharmacology, and antimicrobial resistance. Primary Affiliation : School of Pharmacy, University of Kansas Lab Affiliation : Wang Lab Research Interests : Tianshi Yu's work combines computational biology with medicinal chemistry to analyze structure-activity relationships (SAR) and quantitative SAR (QSAR) of drug candidates. Key areas include: Machine learning applications in drug design Angiotensin-converting enzyme (ACE) inhibitors LpxC and NDM-1 inhibitors for antibiotic resistance Androgen receptor antagonists for prostate cancer CYP17A1 enzyme inhibition mechanisms Neuropharmacological effects of heroin abstinence Recent Publications : Analysis of heroin abstinence effects (2025); computational studies on ACE, LpxC, androgen receptor, CYP17A1 inhibitors (2023); and NDM-1 inhibitors for antibiotic resistance (2022). The work demonstrates expertise in integrating cheminformatics, machine learning, and pharmacological modeling.

Rebecca Davisمشاهده پروفایل

دانشیار

• Asymmetric Organocatalysis
• Computational Chemistry
• Physical Organic Chemistry
• +۶ مورد دیگر

Rebecca Davis is an Associate Professor in the Department of Chemistry at the University of Manitoba , Faculty of Science. Her research integrates computational, kinetic, and synthetic methods to address challenges in asymmetric organocatalysis and antibiotic discovery. Academic Rank: Associate Professor Institution: University of Manitoba Contact: Rebecca.Davis@umanitoba.ca Research Interests: Davis specializes in asymmetric organocatalytic reactions, focusing on mechanisms and catalyst design. She employs computational modeling and machine learning to develop molecular feature libraries for antibiotic discovery, particularly targeting Gram-negative bacteria. Her work also includes photo-aminocatalysis, remote functionalization, and cheminformatics applications. Publication Trends: Recent articles highlight her interdisciplinary approach, combining machine learning with synthetic chemistry for drug discovery, mechanistic studies in organocatalysis, and photophysical characterization of excited-state intermediates. Scientific Awards: Davis served as Past Chair of the CSC Organic Division and is a member of the Digital Research Alliance of Canada’s Researcher Council. Advising: She supervises graduate and undergraduate researchers in projects spanning asymmetric synthesis, computational modeling, and antibiotic development. Labs & Collaborations: The Davis Research Group collaborates with academic and industrial partners on predictive models for synthetic methods and data generation for machine learning in drug discovery.

Bartosz Zambrońمشاهده پروفایل

دانشیار

• Stereocontrolled organic synthesis
• Stereoselective dearomatization
• Reactions of functionalized organometallic compounds
• +۱ مورد دیگر

Bartosz Zambroń is a habilitated doctor (dr hab.) and head of a research group at the Institute of Organic Chemistry, Polish Academy of Sciences, specializing in advanced organic synthesis methodologies. His work bridges fundamental reaction mechanisms with practical applications in medicinal chemistry and materials science. His research concentrates on stereocontrolled organic synthesis, stereoselective dearomatization processes, reactions of functionalized organometallic compounds, and heterocyclic chemistry. He develops innovative strategies for constructing complex poly- and spirocyclic architectures from simple aromatic precursors, with emphasis on regio- and stereochemical precision. Current projects explore the interplay between ligand design and stereoselectivity in transition metal-catalyzed transformations. Analysis of his 2018-2024 publications reveals a consistent focus on palladium/indium-mediated reactions involving β-lactams and aldehydes, with growing integration of computational approaches. His 2024 Angewandte Chemie paper demonstrates pioneering application of machine learning for catalyst optimization in asymmetric magnesium-catalyzed reactions, signaling a strategic expansion into AI-assisted synthesis planning while maintaining core expertise in stereoselective organometallic chemistry. Dr. Zambroń actively mentors two PhD students (Sonali Garag and Marimuthu Rajasekar) and serves as Principal Investigator for the NCN SONATA BIS grant (2022/46/E/ST4/00163) titled "Stereoselective dearomatization of non-activated arenes via 'migrating alkene': Fast access to poly- and spirocyclic systems of high added value from readily available aromatic compounds". This project exemplifies his group's commitment to developing efficient synthetic routes to high-value molecular scaffolds. He leads a dedicated research team at the Institute of Organic Chemistry, Polish Academy of Sciences, which operates within state-of-the-art facilities for organic synthesis and characterization. The group maintains active collaborations with computational chemists and medicinal chemistry labs, particularly evident in their dual focus on reaction methodology development and biological activity screening as seen in their 2018 European Journal of Medicinal Chemistry publication.

• Computational biology
• Bioinformatics
• Metabolomics
• +۱۱ مورد دیگر

Dr. Miroslava Cuperlovic-Culf is an Adjunct Professor at the University of Ottawa's Faculty of Medicine, Department of Biochemistry, Microbiology and Immunology. She also serves as a Senior Research Officer and Team Leader at the National Research Council of Canada's Digital Technologies Research Center. BSc, University of Belgrade, Serbia MA, University of California, Santa Barbara, USA PhD, University of California, Santa Barbara, USA Post-doctoral Research, University of British Columbia, Canada Her research spans computational biology, bioinformatics, and metabolomics, focusing on systems biology approaches for disease modeling and therapeutic design. Key areas include: Machine learning in biomedical data analysis NMR spectroscopy for molecular profiling Computational cancer and neurodegenerative disease metabolism Host-pathogen interaction modeling Design of cell and gene therapy platforms Contact: Office: 613-993-0116 Mobile: 613-797-8294 Email: Miroslava.cuperlovic-culf@nrc-cnrc.gc.ca Alternate Email: mcuperlo@uOttawa.ca

• Drug design
• Medicinal chemistry
• Computational chemistry
• +۵ مورد دیگر

Roger Estrada Tejedor is a Full Professor at the IQS School of Engineering , Universitat Ramon Llull , where he leads the Pharmaceutical Chemistry Group (GQF) and contributes to both the Unit of Pharmaceutical Chemistry and the Unit of Continuous Chemical Processes . His academic journey includes a PhD in Pharmaceutical Chemistry (2011) from Universitat Ramon Llull, a Master's in Applied Statistics (2013) from UNED, and a Chemical Engineering degree (2006) from IQS. Academic Leadership: Accredited as a Reader by AQU (2015), he became a Full Professor in 2020. Research Focus: Computational drug design, AI-driven pharmaceutical algorithms, and targeting pathogenic RNA structures. Scientific Contributions span dual tyrosine kinase inhibitors for pancreatic cancer, allosteric CXCR4/IRAK4 modulators for lymphoma therapy, and structural simplification strategies in hit discovery. His work bridges molecular modeling with continuous manufacturing optimization, transforming batch chemical systems into efficient, sustainable processes. Collaborative projects include the Franco-Spanish PROTEOblood network addressing proteinopathies in hematological cancers.