جستجوی استاد راهنمای دانشگاهی

Prof. Kai S. Exner is a Professor of Theoretical Inorganic Chemistry at the University of Duisburg-Essen's Faculty of Chemistry and a member of the Zentrum für Medizinische Biotechnologie (ZMB). His research focuses on electrocatalysis , particularly optimizing electrode materials for energy applications such as batteries, electrolyzers, and fuel cells. He employs computational methods like ab initio calculations and microkinetic modeling to bridge theoretical insights with experimental and industrial applications, emphasizing sustainable catalyst design without relying on noble metals. His work integrates basic research with applied medical biotechnology through ZMB collaborations, though his primary affiliation lies in the Faculty of Chemistry. Exner has pioneered concepts like the electrochemical-step asymmetry index and free-energy span model, which are critical for screening electrocatalysts. His research group, 'Theoretical Inorganic Chemistry,' actively explores mechanisms behind oxygen and chlorine evolution reactions, emphasizing selectivity control and reaction pathway complexity. Exner received the Gottschalk-Diederich-Baedeker-Preis (2024) for advancing the energy transition through foundational electrocatalysis research. He leads Aktuelles Projekt funded by third-party grants and collaborates with facilities like the Analytics Core Facility Essen (ACE) and Imaging Center Campus Essen (ICCE). His advisory role focuses on guiding theoretical and computational approaches in electrochemistry, and he has established a reputation for interdisciplinary research connecting computational chemistry with practical energy solutions.

• Electrocatalysis
• Inorganic Chemistry
• Materials Science
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Prof. Paul Stupple is a Professor of Medicinal Chemistry at Monash University, Australia, with over 20 years' experience in pharmaceutical industry and academia. He holds leadership roles at Canthera Discovery and manages the Australian Translational Medicinal Chemistry Facility. His expertise lies in small molecule drug discovery, particularly targeting cancer therapies and epigenetic regulators. Affiliations: Monash University, Faculty of Pharmacy and Pharmaceutical Sciences Canthera Discovery (Director, Medicinal Chemistry) Education: BA and DPhil in Chemistry from the University of Oxford (1992–1999). Early career at Pfizer as a medicinal chemistry leader, delivering 6 clinical candidates. Key contributions include: Licensing deals with Merck (2016) and Pfizer (2018) for preclinical projects Leading the Cancer Therapeutics CRC's medicinal chemistry program Research Interests: Small molecule drug discovery focused on histone acetyltransferase inhibitors, cancer therapeutics, and epigenetic modulation. Notable projects include development of KAT6A/B inhibitors for ER+ breast cancer and STING agonists for immunotherapy. Grants/Projects: Principal Investigator for major initiatives like MedChem Australia (2023–2028) and drug target identification platforms. Collaborates widely with institutions like WEHI and University of Sydney. Over 28 peer-reviewed publications spanning 1997–2025. Labs/Teams: Oversees the Australian Translational Medicinal Chemistry Facility, a key resource for drug discovery in Australia.

• Small Molecule Drug Discovery
• Cancer Therapeutics
• Pharmaceutical Chemistry
• +۳ مورد دیگر

David S. Eisenberg is a Professor of Chemistry and Biochemistry and Biological Chemistry at the University of California, Los Angeles, where he also serves as Director of the UCLA-DOE Institute for Genomics and Proteomics and as an HHMI Investigator. His research focuses on protein interactions, particularly the structural basis for conversion of normal proteins to the amyloid state and conversion of prions to the infectious state. Dr. Eisenberg earned his undergraduate degree in biochemical sciences from Harvard College and his D.Phil. degree in theoretical chemistry from Oxford University on a Rhodes Scholarship. His postdoctoral research was on ice and water with Walter Kauzmann at Princeton and in protein crystallography with Richard Dickerson. He joined the UCLA faculty after his postdoctoral studies. Dr. Eisenberg and his research group focus on protein interactions in amyloid and prion diseases. These diseases involve protein aggregation where normal functional proteins convert to abnormal aggregated forms. Systemic amyloid diseases like dialysis-related amyloidosis result from fiber accumulation until organ failure, while neurodegenerative diseases like Alzheimer's, Parkinson's, ALS, and prion conditions appear to be caused by smaller oligomers. In 2005, his team determined the atomic-level structure for the amyloid fiber spine, revealing a 'steric zipper' of two parallel beta sheets packed across a dry interface. Since then, they've determined approximately 90 amyloid spines from 15 disease-related proteins. In 2010, they identified the structure of a toxic amyloid-related oligomer consisting of six anti-parallel beta strands forming a cylindrical barrel. His recent publications demonstrate continued innovation in amyloid research, with focus areas including structural prediction of amyloid formation, mechanisms of tau fibril disassembly in Alzheimer's disease, cryo-EM analysis of amyloid polymorphism, and structure-based design of inhibitors for amyloid toxicity. His work integrates computational, structural, and biochemical approaches to understand protein aggregation across multiple disease contexts. Dr. Eisenberg has received numerous prestigious awards and honors: National Academy of Sciences Member American Philosophical Society Member Institute of Medicine Member Howard Hughes Medical Institute Investigator Biophysical Society Emily M. Gray Award Harvard Westheimer Medal UCLA Seaborg Medal Technion - Israel Institute of Technology Harvey Prize in Human Health As Director of the UCLA-DOE Institute for Genomics and Proteomics and an HHMI Investigator, Dr. Eisenberg leads significant research initiatives in protein structure and aggregation. His laboratory combines X-ray crystallography, bioinformatics, and biochemical techniques to investigate protein interactions, with particular emphasis on amyloid-forming proteins and their role in disease. The Eisenberg Lab, located in Boyer Hall at UCLA, maintains an active research program investigating the structural basis of protein aggregation. The lab continues to build on its landmark discoveries of amyloid structures while exploring new frontiers in understanding protein misfolding diseases and developing potential therapeutic interventions.

• Protein Aggregation
• Amyloid Structures
• Prion Diseases
• +۵ مورد دیگر

Sachdev Sidhu is a Research Professor and Entrepreneur in Residence at the University of Waterloo. His research focuses on synthetic antibodies, protein engineering, and biotechnological applications. He leads efforts in developing novel therapeutic antibodies, engineered protein systems, and molecular tools for biomedical research. His work spans cancer therapy, viral infection countermeasures, and regenerative medicine. Sidhu is also involved in translational research, bridging academic discoveries with commercial applications through entrepreneurial ventures. Key research interests include synthetic antibody libraries, CAR T-cell engineering, ubiquitin-based therapeutics, and phage display technologies. He has contributed to advancements in targeted therapies for glioblastoma, leukemia, and ocular diseases. His team develops innovative methods for protein design, such as engineered ubiquitin variants and modular antibody architectures. Publications highlight breakthroughs in antibody-based treatments, including synNotch CAR T cells for glioblastoma and neutralizing antibodies against SARS-CoV-2. His work integrates structural biology, molecular biology, and computational approaches to address complex biomedical challenges. Sidhu collaborates with industry partners to advance technologies into clinical and commercial settings.

• Synthetic Antibodies
• Protein Engineering
• Biotechnology
• +۵ مورد دیگر

Prof. Dr. Mathias Christmann is a faculty member at the Institute of Chemistry and Biochemistry, Freie Universität Berlin , leading the research group in Organic Chemistry . His work focuses on strategic and methodological challenges in synthetic chemistry, particularly in total synthesis, organocatalysis, and renewable resource transformations. Position: Professor Contact: mathias.christmann@fu-berlin.de Location: Takustr. 3, Room 24.16, 14195 Berlin Research Interests include: Natural product-inspired small molecule synthesis for biological pathway modulation Minimizing C-C bond formations through selective functionalization of terpene building blocks Organocatalytic and metal-catalyzed reactions in multistep sequences Flow chemistry applications for scalable and sustainable synthesis Biological evaluation of TRPC channel agonists/antagonists for cancer therapy Publication Trends highlight expertise in total synthesis of complex terpenoids, organocatalysis for stereocontrolled reactions, flow chemistry for late-stage transformations, and TRPC4/5 channel modulation in renal cancer studies. His group pioneers asymmetric desymmetrization , photo-oxidation protocols , and electrosynthesis methods with minimal reagent waste. Advisees include PhD candidates Jan-Hendrik Dickoff , Mayar Elbendary , Nadine Kreidt , Tobias Olbrisch , Kamar Shakeri , and Zhen Wang , focusing on terpene-based drug discovery and catalytic reaction design.

• Organic Chemistry
• Natural Product Synthesis
• Organocatalysis
• +۶ مورد دیگر

Ron Dror is the Cheriton Family Professor of Computer Science at the Stanford Artificial Intelligence Lab , with courtesy appointments in Structural Biology and Molecular & Cellular Physiology . He also holds affiliations with Bio-X, the Institute for Human-Centered Artificial Intelligence (HAI), the Institute for Computational and Mathematical Engineering (ICME), Sarafan ChEM-H, and the Wu Tsai Neurosciences Institute. Education: PhD in Electrical Engineering and Computer Science, MIT MPhil in Biological Sciences, University of Cambridge (Churchill Scholar) BS in Mathematics and Electrical & Computer Engineering, Rice University (summa cum laude) Ron leads a multidisciplinary research group that combines molecular simulation and machine learning to study biomolecular structure, dynamics, and function. His work focuses on developing computational methods to accelerate drug discovery by predicting molecular interactions and designing more effective therapeutics. Current projects include the PENSA software library for analyzing biomolecular ensembles and FRAME framework for structure-based ligand design. His research has produced groundbreaking work on G-protein-coupled receptors (GPCRs) , RNA structure prediction , and mitochondrial transport mechanisms . Key publications highlight applications of geometric deep learning and molecular dynamics simulations in structural biology. Scientific Awards: Cheriton Family Professorship (2023) Two Gordon Bell Prizes (2014, 2009) Best Paper Awards at NeurIPS (2021), IPDPS (2013), SC11 (2011), SC09 (2009), SC06 (2006) Science Magazine Top 10 Breakthrough (2010) Fulbright Scholarship , NSF Fellowship , DoD Fellowship , Whitaker Foundation Fellowship Ron has advised numerous doctoral and master’s students including EJ Fine , Masha Karelina , and Briana Sobecks . His lab collaborates with experimentalists across academia and industry, applying computational methods to diverse biomedical problems such as RNA structure prediction , GPCR signaling , and mitochondrial metabolism .

• Computational Biology
• Machine Learning
• Molecular Dynamics Simulation
• +۶ مورد دیگر

Raphael Franzini serves as Associate Professor of Medicinal Chemistry at the University of Utah, actively contributing to the Biological Chemistry PhD Program. His research pioneers innovative chemical approaches for therapeutic development, with dual focus on DNA-encoded library technologies and bioorthogonal drug delivery systems. His educational foundation includes an M.S. from the Swiss Federal Institute of Technology (Lausanne) and a Ph.D. from Stanford University. This training underpins his group's multidisciplinary methodology combining organic synthesis, bioconjugation, computational modeling, and advanced imaging techniques. Dr. Franzini's research program centers on two transformative areas: First, advancing DNA-encoded library screening through computational integration to identify leads for challenging targets like Tankyrase and Sirtuin 6, with recent work addressing false negatives in machine learning prediction. Second, developing novel bioorthogonal release chemistry using isonitrile-tetrazine reactions for spatiotemporally controlled drug activation, validated in zebrafish models. His group emphasizes both technological innovation and therapeutic translation, with chemistry designed to minimize off-target effects in solid tumors. Analysis of his 15 most recent publications reveals escalating integration of computational methods with experimental library screening, alongside refinement of bioorthogonal release kinetics. The work spans chemical biology, medicinal chemistry, and pharmaceutical sciences, with growing emphasis on machine learning for library data interpretation and in vivo validation of drug-release systems. Dr. Franzini maintains an active research laboratory that provides comprehensive training in cutting-edge drug discovery methodologies. His group culture prioritizes both scientific innovation and researcher development, with projects spanning from fundamental reaction kinetics to therapeutic applications. The lab's infrastructure supports organic synthesis, molecular imaging, and computational analysis for advancing precision therapeutics.

• Drug Discovery
• Medicinal Chemistry
• Bioorthogonal Chemistry
• +۳ مورد دیگر

Peter O'Brien is Professor of Chemistry at the University of York, leading research in organic synthesis and medicinal chemistry. His group develops novel methods for stereospecific Negishi/Suzuki-Miyaura cross-coupling reactions and 3D fragment-based drug discovery. Collaborations with AstraZeneca, Diamond X-Chem, and Redbrick Molecular focus on COVID-19 therapeutics and building-block libraries. O'Brien employs high-throughput robotics for reaction optimization and mechanistic studies. His work bridges fundamental organolithium chemistry with applications in synthesizing bioactive heterocycles (piperidines, pyrrolidines). The York 3D Fragment Library, featuring shape-diverse compounds, identified hits against SARS-CoV-2 proteins. Awards include the RSC Stereochemistry Award (2013) and YUSU Teacher of the Year (2019). Selected honors: EPSRC/IAA grants for 3D building blocks commercialization Industrial Fellowships with AstraZeneca (2019-2022) Vice-Chancellor's Teaching Award (2015)

• Organic Synthesis
• Medicinal Chemistry
• Suzuki-Miyaura Coupling
• +۲ مورد دیگر

Dr. Yang Zhang is a Professor at the National University of Singapore (NUS), holding appointments in the Department of Computer Science (School of Computing) and the Department of Biochemistry (Yong Loo Lin School of Medicine). He also leads the Zhang Lab, which focuses on AI-driven computational methods for protein structure prediction and design. Previously, he was a Professor at the University of Michigan. His research integrates artificial intelligence, deep learning, and physics-based models to address challenges in computational biology. Affiliations: School of Computing; Yong Loo Lin School of Medicine; Cancer Science Institute of Singapore Key Roles: Principal Investigator of Zhang Lab; Developer of I-TASSER algorithm Research interests span AI-driven protein design, deep learning for RNA structure prediction, and drug discovery. Projects include the EvoDesign server for protein interaction design and TripletRes for coevolution-based contact prediction. Major contributions include the I-TASSER algorithm, ranked top in CASP experiments for protein structure prediction. Awards: Alfred P. Sloan Award, NSF CAREER Award, and seven-time Highly Cited Researcher (2015–2021).

• Computational Biology
• Bioinformatics
• Algorithms
• +۶ مورد دیگر

Professor Charlotte Deane is a leading academic in structural bioinformatics, holding the position of Professor at the University of Oxford's Department of Statistics and Executive Chair of the Engineering and Physical Sciences Research Council (EPSRC). She leads the Oxford Protein Informatics Group (OPIG), focusing on protein structure prediction, immunoinformatics, and AI-driven drug discovery. Her research integrates computational methods with biological insights, developing tools widely used in academia and industry. Prior roles include Head of the Department of Statistics, Deputy Head of the Mathematical, Physical and Life Sciences (MPLS) Division at Oxford, and Chief Scientist of Biologics AI at Exscientia. During the COVID-19 pandemic, she served on SAGE and as UKRI's COVID-19 Response Director. In 2022, she was awarded an MBE for her contributions to pandemic research. Her research group's work spans antibody design, T-cell receptor analysis, and small molecule discovery, with a focus on open-source software development. Current projects include advancing AI methods for protein structure prediction and therapeutic antibody engineering. Recent publications highlight innovations in computational drug design, antibody developability, and machine learning applications in structural biology.

• Structural Bioinformatics
• Protein Structure Prediction
• Immunoinformatics
• +۳ مورد دیگر

Jian Peng is an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. His research focuses on computational biology, machine learning, and their applications to protein structure prediction, drug design, and molecular modeling. He has contributed to advancements in antibody engineering, protein-ligand docking, and generative models for biological systems. Key research areas include: Machine Learning for Molecular Modeling Protein Structure Prediction Antibody and Peptide Design Genomics and Single-Cell Analysis Structure-Based Drug Discovery His work emphasizes integrating deep learning techniques with biological datasets to address challenges in precision medicine, drug development, and systems biology. Notable achievements include developing the FastFold system to accelerate AlphaFold training and pioneering flow-based methods for antibody design. Awards include the Overton Prize (2020), recognizing contributions to computational biology. His research has been published in top journals and conferences, spanning topics from protein mutation prediction to geodesic-based immune complex modeling.

• Machine Learning
• Bioinformatics
• Computational Biology
• +۵ مورد دیگر

Lawton Robert Burns is the James Joo-Jin Kim Professor and Professor of Healthcare Management at the Wharton School, University of Pennsylvania . He serves as Co-Director of the Roy and Diana Vagelos Program in Life Sciences and Management and Chairperson of the Health Care Systems Department since 2008. His career spans academic roles at the University of Chicago, University of Arizona, and University of Wisconsin. Education: PhD in Sociology, University of Chicago (1981) MBA in Health Administration, University of Chicago (1984) MA, University of Chicago (1976) BA, Haverford College (1973) Dr. Burns specializes in healthcare organization design , strategic change , and supply chain dynamics . His work examines hospital-physician relationships , integrated delivery systems , and market forces in healthcare. His recent publications analyze Pharmacy Benefit Managers (PBMs) , Group Purchasing Organizations (GPOs) , and strategic implementation failures. Notable awards include the Arthur Anderson Distinguished Visitor (2001), Edwin Crosby Memorial Fellowship (1992-93), and Udall Fellowship (1990-91). His research has been featured in Knowledge at Wharton , LDI News , and American Political Science Review . Dr. Burns co-authors works with experts like David Dranove and Stephen Shortell , focusing on clinical integration , retail supply chains , and global healthcare models (India, China).

• formal organizations
• health care management
• hospital-physician relationships
• +۵ مورد دیگر

Francesca Grisoni serves as an Assistant Professor in the Department of Biomedical Engineering at Eindhoven University of Technology (TU/e), where she currently leads the Molecular Machine Learning team. She additionally holds appointments as an ICMS Core member and Associate Professor at EAISI (Eindhoven Artificial Intelligence Systems Institute), reflecting her cross-disciplinary role at the intersection of computational science and biomedical applications. Academic Background : Grisoni completed her Environmental Sciences degree and earned a Ph.D. in 2016 from the University of Milano-Bicocca, where her dissertation focused on interpretable machine learning for molecular property prediction. During doctoral studies, she conducted research at ETH Zurich's Department of Chemistry and Applied Biosciences and the U.S. EPA's National Center for Computational Toxicology. Ph.D., University of Milano-Bicocca, 2016 (Dissertation: Interpretable machine learning for molecular property prediction) Environmental Sciences, University of Milano-Bicocca Her research integrates artificial intelligence, chemistry, and biology to develop computational methods for drug discovery, emphasizing wet-lab experimental validation alongside algorithmic innovation. Key focus areas include overcoming activity cliffs in molecular machine learning, generative modeling for scaffold hopping, and AI-augmented decision-making in therapeutic development, with the ultimate goal of achieving 'better decisions faster' in drug discovery pipelines. Analysis of her recent 2025 publications reveals a concentrated trend toward chemical language models and generative deep learning frameworks, specifically addressing low-data drug discovery challenges through active learning and neural network architectures. These works bridge computer science with pharmacology, targeting bioactivity prediction, molecular representation, and enzyme design while maintaining strong ties to experimental validation. Scientific Awards : Lush Young Researcher Prize Early Career Award 2022 from the Dutch Royal Netherlands Academy of Arts and Sciences (KNAW) ERC Starting Grant (2022) Grants and Supervision : Dr. Grisoni secured the prestigious ERC Starting Grant in 2022 to advance her molecular machine learning research. Institutional records indicate she has supervised 7 students (as shown in TU/e's 'Supervised Work (7)' repository section), though specific names aren't provided in the source material. Her group maintains active industry collaborations, including past engagement with Bracco Pharmaceuticals. Laboratory and Team : The Molecular Machine Learning team operates under the ICMS and EAISI frameworks, merging computational AI development with experimental wet-lab validation. This collaborative unit focuses on fragment-based molecular design, chirality representation (evidenced by fragSMILES work), and high-throughput nanoparticle identification using machine learning, as highlighted in recent press coverage and datasets.

• Artificial Intelligence
• Machine Learning
• Drug Discovery
• +۸ مورد دیگر

Lawton R. Burns is the James Joo-Jin Kim Professor of Health Care Management and Professor of Management at the Wharton School, University of Pennsylvania. He serves as Co-Director of the Roy and Diana Vagelos Program in Life Sciences and Management and Chairperson of the Health Care Systems Department since 2008. Dr. Burns holds a PhD in sociology and an MBA in health administration from the University of Chicago, along with a BA from Haverford College. PhD, University of Chicago (1981) MBA, University of Chicago (1984) MA, University of Chicago (1976) BA, Haverford College (1973) His research focuses on healthcare supply chains, organizational innovation, and strategic management in health systems. He has authored or co-authored 15+ books, including analyses of integrated healthcare, pharmaceutical and medical device sectors, and global health systems in India and China. Recent works examine evidence-based healthcare innovation and the role of GPOs/PBMs in drug pricing. Dr. Burns advises on healthcare policy, including Senate testimony on pharmacy benefit managers and antitrust implications of physician-hospital organizations. His teaching covers healthcare strategy, managed care, integrated delivery networks, and the U.S. healthcare ecosystem, with courses requiring competitive analysis of producer, purchaser, and provider organizations. Board of Institute of Medicine, Health Services Research Section (2003) Arthur Anderson Distinguished Visitor, University of Cambridge (2001) Teacher of the Year, Administrative Medicine Program (1999) Edwin Crosby Memorial Fellowship (1992-93) Udall Fellowship (1990-91) Invited Lecture Series, Catholic University of Rome (1997)

• formal organizations
• health care management
• hospital-physician relationships
• +۵ مورد دیگر

Bertrand Jean-Claude serves as a Senior Scientist at the Research Institute of the McGill University Health Centre (RI-MUHC) at the Glen site and holds a Professorship in the Department of Medicine within McGill University's Faculty of Medicine and Health Sciences. His primary affiliation lies with the Metabolic Disorders and Complications Program under the Centre for Translational Biology. His research centers on innovative anticancer drug development, specifically focusing on the design and synthesis of multitargeted drug candidates engineered to simultaneously block multiple pathways in tumor cells. Key methodologies include kinase inhibitor development , molecular modeling , and pharmacokinetic analysis of combi-drugs—hybrid molecules designed for dual mechanisms of action such as EGFR receptor inhibition coupled with DNA damage. His publication history reveals consistent contributions to molecular oncology, with recent work emphasizing EGFR and DNA repair pathway dual targeting Fluorescence-based drug distribution tracking Overcoming P-glycoprotein-mediated drug resistance Stable combi-molecule fragmentation mechanisms His work bridges medicinal chemistry and translational cancer research, aiming to develop more effective tumor-selective therapies. Jean-Claude maintains active laboratory operations within the RI-MUHC's Centre for Translational Biology, where his team investigates combi-targeting strategies for oncology applications. His research program receives support through institutional frameworks of McGill University and the RI-MUHC, with emphasis on translating molecular discoveries into preclinical therapeutic candidates.

• Cancer Drug Research
• Pharmacokinetics
• Molecular Modeling
• +۳ مورد دیگر