جستجوی استاد راهنمای دانشگاهی

• Bioinformatics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Ole Winther is Professor in High dimensional biological data analysis/Machine learning at the Department of Biology, University of Copenhagen and Professor in Data science and complexity at DTU Compute, Technical University of Denmark. He serves as CRO and co-founder of raffle.ai, CTO and co-founder of FindZebra, Head of ELLIS Unit Copenhagen, and co-PI of the Machine Learning for Life Science Center. His research spans Bioinformatics , Machine Learning , and AI for Science , focusing on applying deep learning to biological sequence analysis, latent variable models, and medical NLP. Winther's work develops predictive and generative models for bioinformatics, with significant contributions to protein localization tools (SignalP, DeepLoc, DeepTMHMM), single-cell genomics, and novel deep learning architectures like variational autoencoders and diffusion models. Analysis of Winther's recent publications (2023-2025) reveals a strong trend toward integrating protein language models with traditional bioinformatics approaches and applying diffusion models to scientific problems. His work bridges theoretical machine learning advancements with practical applications in biology and medicine, particularly in protein sequence analysis, medical search engines, and scientific simulation acceleration. Winther currently supervises a diverse research group including Panagiotis Antoniadis, Rachael M. DeVries, Jun Wang, Beatrix M. G. Nielsen, Felix G. Teufel, Irene R. Rodriguez, Anders Christensen, and Christopher Heje Grønbech. His former students have established successful careers at institutions including Google, Apple, and various startups, with notable alumni like Casper Sønderby (Google Brain) and Søren Sønderby (Apple). He leads significant research initiatives including the ELLIS Unit Copenhagen and the Machine Learning for Life Science Center, while maintaining active industry partnerships through his co-founded companies raffle.ai (enterprise search using NLP) and FindZebra (search engine for rare diseases). His teaching includes Deep Learning courses at both DTU (02456) and University of Copenhagen (NDAK24002U).

Hauke Smidtمشاهده پروفایل

استاد

• Microbiology
• Environmental Microbiology
• Gut Microbiota
• +۴ مورد دیگر

Hauke Smidt is a Personal Professor at Wageningen University & Research, affiliated with the Molecular Ecology group within the Faculty of Veterinary Medicine and Animal Sciences. His research focuses on microbial ecology, particularly gut microbiota dynamics, antibiotic resistance, environmental microbiology, and the One Health framework. Smidt has supervised over 50 PhD students and contributed to 519 publications, including studies on microbiome resilience, fermented food impacts, and bioremediation strategies. Education and affiliations include leadership roles in projects addressing antimicrobial resistance, pig health, and drinking water microbiology. His work spans collaborations across Europe and Asia, with notable contributions to understanding microbial community responses to environmental stressors and dietary interventions. Smidt is actively involved in public outreach, as seen in media contributions discussing microbiome research and health benefits. Key projects include aquifer treatment for drinking water, microbiome simulation models, and combating plant pathogens. His awards and recognition are not explicitly listed, but his extensive publication record and project leadership highlight significant academic impact.

• Plant Biotechnology
• Molecular Biology
• Synthetic Biology
• +۵ مورد دیگر

Jun Hyung Lee is a Visiting Assistant Professor in the Department of Environmental Biology at SUNY College of Environmental Science and Forestry (ESF). His research focuses on advancing forest tree improvement and conservation through molecular and synthetic biology approaches, with a particular emphasis on enhancing plant resilience to environmental stresses via beneficial microbial interactions. He teaches courses in plant biotechnology and tissue culture methods. Education includes a Ph.D. in Forest Genetics from Purdue University (USA), and M.S. and B.S. degrees in Plant Science from Seoul National University (South Korea). His work integrates cutting-edge genetic engineering techniques with ecological studies to address challenges in plant stress tolerance, symbiosis, and epigenetic regulation. Recent projects include identifying novel symbiosis pathways for thermotolerance and analyzing flooding tolerance in hybrid poplars. Publications highlight contributions to plant-microbe interaction research, synthetic biology applications, and genome editing epigenetic impacts. Collaborations span institutions like Oak Ridge National Laboratory and the University of Georgia, reflecting his transdisciplinary approach to plant science. Lee’s teaching emphasizes practical skills in biotechnology, bridging laboratory innovation with field applications.

Syed Hani Hassan Abidiمشاهده پروفایل

دانشیار

• Virology
• Immunology
• Viral Oncology
• +۷ مورد دیگر

Syed Hani Hassan Abidi is an Associate Professor at the Department of Biomedical Sciences , School of Medicine , Nazarbayev University , Kazakhstan. His research integrates virology , immunology , viral oncology , and bioinformatics , with a focus on HIV molecular epidemiology , viral evolution , and drug resistance . He has led international projects across Pakistan, Kenya, Afghanistan, and Kazakhstan, and is recognized for innovative teaching and MOOC development. Education: PhD in Virology and Immunology Research Interests: His laboratory employs bioinformatics (machine learning, AI), genomics , and proteomics to study HIV phylodynamics , viral co-infections , and oncogenic viruses like EBV in prostate cancer. He also explores microbiome-immunity interactions and designs antiviral drugs/vaccines . Recent Research Trends: His 2025 publications emphasize COVID-19 immunopathology , HIV/syphilis epidemiology in Pakistan , and particle physics contributions via ATLAS , showcasing interdisciplinary impact. Awards & Recognition: Outstanding Teachers Award (2019, Aga Khan University) Fellowship of Higher Education (UK, 2022) Teaching & Grants: He pioneered Pakistan’s first MOOC on Computer-Based Drug Discovery (2014) and received a 2022 SoTL grant for MOOC-based molecular biology education. His teaching integrates animations , films , and flipped classrooms . Collaborations & Labs: Leads projects on HIV drug resistance , HCV genomics in Kazakhstan , and AI-driven dementia diagnostics (Kazakh Brain Atlas). His lab collaborates with global institutions to advance viral disease surveillance and therapeutic innovation .

Alexis Battleمشاهده پروفایل

دانشیار

• Genomics
• Machine Learning
• Computational Biology
• +۳ مورد دیگر

Alexis Battle is an Associate Professor at Johns Hopkins University with appointments in Biomedical Engineering , Computer Science , and Genetic Medicine (secondary). She directs the Malone Center for Engineering in Healthcare and serves as Deputy Director of the Data Science and AI Institute . Educated at Stanford University (PhD in Computer Science, 2013), Battle transitioned to academia after leadership roles at Google. Research Focus: Battle’s work bridges genomics and machine learning , emphasizing the impact of genetic variation on human health. Her lab develops tools like Watershed to predict functional effects of rare variants, aiming to enhance rare disease diagnosis. Key themes include non-coding DNA analysis , personalized genomics , and systems biology , with applications in cardiovascular disease and neurodegenerative disorders . Publications & Awards: Over 60 peer-reviewed articles in journals like Nature , Science , and Genome Biology , with recent emphasis on single-cell transcriptomics , multiomics integration , and telomere biology . Recipient of the President’s Frontier Award (2022), Microsoft Investigator Fellowship (2019), and Searle Scholar (2016). Scientific Awards: 2022 President’s Frontier Award 2019 Microsoft Investigator Fellowship 2019 Johns Hopkins Discovery Award 2017 Johns Hopkins Catalyst Award 2016 Searle Scholar Advising & Funding: Mentors 11 PhD students, 3 undergraduates, and postdoctoral fellows. Her research is funded by NIH, Searle Scholars, and institutional grants. The Battle Lab collaborates on projects like the GTEx Consortium , focusing on gene regulation and clinical genomics .

Martin T. Wellsمشاهده پروفایل

استاد

• Applied Statistics
• Theoretical Statistics
• Bayesian Statistics
• +۷ مورد دیگر

Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.

Alexandre Bouchard-Côtéمشاهده پروفایل

استاد

• Computational Statistics
• Bayesian Inference
• Monte Carlo Methods
• +۴ مورد دیگر

Alexandre Bouchard-Côté is a Professor of Statistics at the University of British Columbia (UBC), affiliated with the Department of Statistics within the Faculty of Science. His research focuses on computational statistics, Bayesian methods, and Monte Carlo techniques, with applications in evolutionary biology, cancer genomics, and computational linguistics. Education : PhD in Computer Science (with Designated Emphasis in Statistics) from UC Berkeley (2010), BSc in Mathematics and Computer Science from McGill University (2005). Affiliations : Director of the Blang probabilistic programming project and leader of the Bouncy Particle Sampler research group. Research Interests : Bouchard-Côté develops scalable Bayesian computational methods, including non-reversible Monte Carlo algorithms like the Bouncy Particle Sampler, and applies these to problems in cancer phylogenetics, evolutionary dynamics, and historical linguistics. His work emphasizes bridging theoretical foundations with practical tools for data science. Publications Trends : Recent work spans distributed sampling frameworks (e.g., Pigeons.jl), variational phylogenetic inference, and cancer clonal evolution modeling. His articles often address algorithmic scalability and interdisciplinary applications in biology and astronomy. Awards : CRM-SSC Prize in Statistics (2024) PIMS-UBC Mathematical Sciences Young Faculty Award (2018) Tweedie New Researcher Award (2016) Advising & Grants : Supervises graduate students (e.g., Son Luu, Nikola Surjanovic) and leads funded projects on distributed MCMC and cancer genomics. Collaborates with institutions like the Simons Foundation and the Canadian Statistical Sciences Institute (CANSSI). Labs/Teams : Core member of the UBC Statistical Machine Learning group, contributing to open-source tools like Blang and the Bouncy Particle Sampler implementation.

• Evolutionary Biology
• Marine Biology
• Taxonomy
• +۵ مورد دیگر

Mikael Thollesson is a Senior Lecturer at Uppsala University, affiliated with the Department of Organismal Biology; Systematic Biology and Klubban’s Biological Station. His research focuses on evolutionary biology, phylogenetics, taxonomy, and molecular biology, particularly in marine and freshwater sponges (Porifera), bacterial pathogens, and computational methods in evolutionary analysis. Evolutionary Biology Marine Biology Taxonomy His recent publications highlight trends in sponge biodiversity, phylogeography, bacterial horizontal gene transfer, and mitochondrial gene evolution. Key articles include studies on Swedish demosponge faunas, Silene sect. Arenosae systematics, and computational tools like SPRIT for detecting gene transfers. No explicit awards or grants are mentioned.

Anthony Rollettمشاهده پروفایل

استاد

• Additive Manufacturing
• Advanced Materials Processing and Manufacturing
• Digital Twins
• +۶ مورد دیگر

Anthony Rollett is a Professor in the Department of Materials Science and Engineering at Carnegie Mellon University , where he has been a faculty member since 1995. He serves as the Principal Investigator and Co-Director of the NASA-supported Institute for Model-Based Qualification & Certification of Additive Manufacturing (IMQCAM) and co-director of the Next Manufacturing Center . Prior to CMU, he held leadership roles at Los Alamos National Laboratory (1991-1995). Education: Ph.D., Materials Engineering, Drexel University (1987) MA, Metallurgy and Materials Science, Cambridge University (1977) Research Interests: Rollett’s work focuses on microstructural evolution and microstructure-property relationships in 3D using experiments and simulations. His expertise spans additive manufacturing , metal 3D printing , materials for energy systems , grain growth , recrystallization , and stereology , with techniques like high-energy diffraction microscopy (HEDM) and dynamic x-ray radiography (DXR) . Scientific Contributions: He has over 320 peer-reviewed publications and an h-index >80 . His recent articles highlight machine learning for laser processing , fatigue analysis of additively manufactured alloys, and design optimization for heat exchangers in supercritical CO2 and solar thermal applications . Scientific Awards: Fellow of ASM International (1996) Fellow of the Institute of Physics (UK) (2004) Fellow of The Minerals, Metals & Materials Society (TMS) (2011) Cyril Stanley Smith Award (TMS, 2014) Member of Honor, French Metallurgical Society (2015) US Steel Professor (2017) Francqui International Professor (2020-2021) International FAME Award (2023) Leadership & Impact: Rollett co-led the development of a NASA Space Technology Research Institute for additive manufacturing and established a new master’s program in additive manufacturing (2018). His research group is funded by industry , federal agencies , and Pennsylvania state grants . He also serves on the Basic Energy Science Advisory Committee and Defense Programs Advisory Committee for the Department of Energy.

Angela D Kentمشاهده پروفایل

استاد

• Microbial Ecology
• Nitrogen Cycling
• Agroecosystems
• +۳ مورد دیگر

Angela D. Kent is a Professor in the Department of Natural Resources and Environmental Sciences at the University of Illinois Urbana-Champaign, where she also serves as Director of the Program in Ecology, Evolution, and Conservation Biology within the School of Integrative Biology. She is affiliated with the Carl R. Woese Institute for Genomic Biology. Her research focuses on microbial communities in agroecosystems and natural environments, particularly their roles in nitrogen cycling, soil health, and sustainable bioenergy production. Key research interests include microbial interactions in plant-microbe systems, the impact of genetic variation in crops on microbial processes, and the ecological and biogeochemical implications of soil microbiomes. She has authored over 99 publications and supervised datasets on topics such as denitrification dynamics, rhizosphere microbiome assembly, and microbial contributions to nitrogen retention. Dr. Kent has received the NACTA Educator Award (2012) and has contributed to high-impact studies on topics like microbial community responses to environmental stressors and the application of stable isotopes in bioenergy research. Her work bridges microbial ecology, agronomy, and environmental science, emphasizing practical solutions for sustainable agriculture and ecosystem management.

Itsik Pe'erمشاهده پروفایل

استاد

• Human Genetics
• Computational Biology
• Genomics
• +۳ مورد دیگر

Itsik Pe'er is a Full Professor and Vice-Chair in the Department of Computer Science at Columbia University's Fu Foundation School of Engineering & Applied Science, and holds a joint appointment as Professor of Systems Biology at the Vagelos College of Physicians and Surgeons. His research focuses on computational methods in human genetics, including genetic variation analysis, disease association studies, and algorithm development for genomic data. He leads the Itsik Pe'er Lab of Computational Genomics, which develops tools like Xplorigin, Germline, and SEACells to address challenges in genomics and medical research. His work spans machine learning applications in healthcare, microbiome analysis, and cancer genomics. Notable contributions include studies on hypertensive disorders in pregnancy, bias correction in predictive models, and the development of non-Euclidean learning libraries like Manify. Pe'er has advised students including Vladimir Vacic, Anat Kreimer, and Arthi Ramachandran, and collaborates on grants addressing genetic epidemiology and computational biology. His lab's location is in the Computer Science Building at Columbia's Morningside Campus.

Ahmet Acarمشاهده پروفایل

دانشیار

• Cancer Biology
• Precision Medicine
• Drug Resistance Mechanisms
• +۳ مورد دیگر

Dr. Ahmet Acar is an Associate Professor at the Department of Biological Sciences, Middle East Technical University (METU), Ankara, Turkey. He leads the Cancer Precision Medicine and Drug Resistance Laboratory, focusing on understanding mechanisms of drug resistance in cancer. His research integrates experimental models, next-generation sequencing, and deep learning to address clinical challenges in cancer therapy. Dr. Acar holds a B.Sc. from METU's Biological Sciences department and a Ph.D. from the Cancer Research UK Manchester Institute. He completed postdoctoral training at the Institute of Cancer Research, London, and the University of Manchester. Research Interests: Drug resistance mechanisms, precision oncology, tumor microenvironment modeling, patient-derived organoids, computational pathology, and evolutionary cancer biology. His lab develops 2D/3D co-culture systems, PDO biobanks, and AI-driven histopathology tools to improve treatment strategies. Recent Work Trends: Recent publications emphasize tumor evolution modeling, matrix mechanics in drug resistance, and AI applications in histopathology. Collaborations with hospitals in Turkey and Europe support PDO biobank initiatives. His team explores evolutionary steering strategies to exploit collateral drug sensitivities. Labs/Teams: Precision Medicine and Drug Resistance Lab at METU focuses on interdisciplinary approaches combining wet-lab experiments with computational methods. Current projects include ex vivo tumor modeling and AI-driven diagnostic tools for oncology.

Antti Honkelaمشاهده پروفایل

استاد

• Privacy-preserving machine learning
• Differential Privacy
• Bayesian Machine Learning
• +۳ مورد دیگر

Antti Honkela is a Professor of Data Science at the University of Helsinki's Department of Computer Science, within the Faculty of Science. He also serves as the Coordinating Professor for the Privacy-preserving and Secure AI Research Programme at the Finnish Center for Artificial Intelligence (FCAI), and as Deputy Director of the Master's Programme in Data Science. His roles include membership in the Health and Social Data Permit Authority (Findata) and as an Action Editor for Transactions on Machine Learning Research. Honkela's research focuses on privacy-preserving machine learning, differential privacy, Bayesian methods, and their applications in computational biology and healthcare. He leads projects such as the European Lighthouse in Secure and Safe AI (ELSA) and the Data Literacy for Responsible Decision-making initiative. His work emphasizes developing robust frameworks for privacy-aware AI, including differentially private synthetic data and federated learning. Honkela has advised numerous PhD and Master's students, and his contributions span theoretical advancements and practical implementations, such as the D3p Python package for differentially private probabilistic programming. Key contributions include advancements in Bayesian inference from synthetic data, privacy accounting mechanisms, and computational methods for genomic epidemiology. His interdisciplinary approach bridges machine learning, statistics, and healthcare, addressing challenges in data privacy and secure AI deployment.

Michele Klingbeilمشاهده پروفایل

استاد

• Parasitology
• Molecular Biology
• Microbiology
• +۴ مورد دیگر

Michele Klingbeil is a Professor in the Department of Microbiology at the University of Massachusetts Amherst, where she leads the Klingbeil DNA Replication Laboratory. She received her PhD in Cell and Molecular Biology from the University of Toledo in 1996 and previously worked at Johns Hopkins School of Medicine before moving to UMass in July 2007. Her educational background includes: PhD in Cell and Molecular Biology, University of Toledo, 1996 Dr. Klingbeil's research focuses on the unique biology of trypanosomatid parasites, particularly Trypanosoma brucei , the causative agent of African sleeping sickness. Her laboratory investigates two main areas: (1) replication of the unusual mitochondrial DNA network called kinetoplast DNA (kDNA), and (2) nuclear DNA replication initiation. Her work on kDNA is particularly significant as this structure is essential for parasite survival but has no counterpart in mammalian hosts, making it an attractive drug target. She employs a combination of reverse genetics (RNAi), cell biology, and biochemistry to understand the replication and repair mechanisms of kDNA, with a special focus on a family of four DNA polymerases related to bacterial Pol I. Dr. Klingbeil's recent publications reveal her laboratory's deep investigation into mitochondrial DNA polymerases in trypanosomatids, with discoveries showing multiple polymerases having specialized functions in kDNA replication and repair. Her research has established that several of these polymerases are essential for parasite viability, opening new avenues for drug development. She has also made significant contributions to understanding the simplified Origin Recognition Complex in trypanosomatids compared to other eukaryotes. Dr. Klingbeil has received the Thomas G. Lessie Distinguished Lectureship Award for her impact on teaching at the graduate level. Her research is funded by the National Institutes of Health, U.S. Department of Agriculture, the Joeph P. Healey Endowment, and the University of Massachusetts Amherst. She has mentored numerous graduate and undergraduate students, including current PhD candidates Dave Bruhn, Jeniffer Concepción, and Juemin Luo, as well as visiting scholar Eva Vidal Rico. Her former students have gone on to positions at institutions including Dana Farber/Broad Institute, Regis College, and Flagship Ventures. The laboratory regularly participates in scientific conferences including the Molecular Parasitology Meeting at Woods Hole and the Kinetoplastid Molecular Cell Biology conference. Dr. Klingbeil teaches several courses including Parasitology (MICRO 590S), Parasitology Lab (MICRO 590L), Molecular Mechanisms of Pathogenesis (MICRO 797P), Advanced Cell Biology (MCB 641), and Writing in Microbiology (MICRO 360). Her laboratory organizes regular social events including pumpkin carving parties and outings to Six Flags New England and Mt. Sugarloaf.

Lourdes Pena-Castilloمشاهده پروفایل

استاد

• Bioinformatics
• Genomics
• Machine Learning
• +۵ مورد دیگر

Dr. Lourdes Pena-Castillo is a Professor jointly appointed in the Departments of Computer Science and Biology at Memorial University of Newfoundland's Faculty of Science. Her research focuses on applying machine learning and bioinformatics to study bacterial gene regulation, with emphasis on transcriptomics, gene expression pathways, and microbiology. She leads the Bioinformatics Lab at MUN, developing computational tools like Promotech for promoter prediction and sRNARFTarget for sRNA target identification. Education: BSc in Information Systems Engineering, ITESM-Mexico MSc in Computer Science, University of Alberta PhD in Computer Science (Doktoringenieurin), Otto-von-Guericke Universität Magdeburg Postdoc in Bioinformatics, University of Toronto Research Interests: Bioinformatics, Genomics, Machine Learning, Artificial Intelligence, Transcriptomics, Gene Regulation, Microbiology Her work integrates computational methods with biological data to address challenges in molecular biology, including analyzing bacterial sRNA functions, promoter recognition, and disease diagnostics using machine learning. She has advised numerous graduate students, including PhD candidates Purvikalyan Pallegar and Bonita McCuaig, and MSc students like Ruben Chevez-Guardado and Kratika Naskulwar. Her lab focuses on translational research with applications in both basic science and clinical contexts. Publications span computational methods for bacterial gene regulation, bioinformatics tool development, and interdisciplinary projects in VR and healthcare informatics. Her research has contributed to understanding symbiotic relationships in marine organisms, inflammatory bowel disease diagnostics, and clavulanic acid production in Streptomyces. Grants & Collaborations: Works with interdisciplinary teams across computer science and biology, supported by grants enabling projects in bacterial genomics and computational tool development. Labs & Teams: Leads the Bioinformatics Lab at MUN, fostering collaborations with researchers in microbiology, computer science, and healthcare.