Find Academic Supervisors

• Biomedical Informatics
• Computational Biology
• Immunoinformatics
• +7 more

María Rodríguez Martínez is an Associate Professor of Biomedical Informatics and Data Science at Yale School of Medicine, where she leads research at the intersection of computational biology, immunology, and artificial intelligence. Her work focuses on understanding T and B cell function in complex diseases like cancer and autoimmune disorders through integrated computational approaches. Her primary research interests involve developing interpretable deep learning methods to uncover biological mechanisms behind immune responses. Rodríguez Martínez's lab integrates mechanistic models with AI to predict T cell receptor binding, investigate B cell development, and analyze complex disease mechanisms. Her work emphasizes model interpretability to extract biological insights from computational predictions rather than treating AI as a black box. Her recent publications demonstrate strong focus on immunoinformatics, with significant contributions to TCR-epitope prediction challenges, cell-specific gene network analysis in autoimmune diseases, and domain-specific protein language models for immunological applications. The research consistently bridges computational methodology development with biological discovery in immunology and cancer. Prof. Rodríguez Martínez serves as editor for multiple journals including ImmunoInformatics, Frontiers in Systems Biology, BMC Bioinformatics, and IEEE Transactions on Molecular, Biological, and Multi-Scale Communications. She is a frequent speaker and organizing committee member at major conferences such as ISMB, the Society for Mathematical Biology, and ECCB. Prior to Yale, she was Technical Leader of Systems Biology at IBM Research Europe (Switzerland), where she established the computational systems biology team and led EU-funded consortia on prostate and pediatric cancers. Her background spans physics (PhD in Gravitation and Cosmology from Institut d'Astrophysique de Paris, 2003), postdoctoral work at Weizmann Institute of Science and Columbia University, and extensive industry research experience at IBM.

Jukka CoranderView profile

Professor

• Bayesian Statistics
• Inference Methods
• Stochastic Simulation Algorithms
• +7 more

Jukka Corander is a Professor at the University of Oslo's Department of Biostatistics, Faculty of Medicine, and concurrently holds positions at the University of Helsinki's Department of Mathematics and Statistics. He specializes in Bayesian statistics, microbial genomics, and evolutionary biology, with a focus on bacterial pathogen evolution and antibiotic resistance mechanisms. Affiliations: Professor, Department of Biostatistics, University of Oslo (since 2016) Professor, Department of Mathematics and Statistics, University of Helsinki (since 2009) Former roles at Åbo Akademi University and Churchill College, University of Cambridge Research Interests: Bayesian inference methods, stochastic simulation algorithms, machine learning applications in genomics, population genetics of bacteria, and forensic statistical analyses. Key Awards: 2015 Cozzarelli Prize (PNAS) for groundbreaking work on bacterial pathogen evolution 2008 Per Brahe Award (Young Scientist of the Year) Grants & Leadership: ERC StG Grant (SmartBayes, 2009–2014) COIN Centre of Excellence (Vice-Director, 2015–2017) Leadership roles in Helsinki Institute of Information Technology (HIIT) Labs & Collaborations: Leads the Corander Lab, focusing on computational methods for microbial genomics and evolutionary analysis. Collaborates globally on projects involving antibiotic resistance, pathogen transmission, and epidemiological modeling.

• Structural Health Monitoring
• Vibration Control
• Statistical Energy Analysis
• +3 more

Antonio Culla is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Sapienza University of Rome. His research focuses on structural health monitoring, vibration control, and nonlinear dynamics. He specializes in applying advanced analytical techniques to mechanical systems, robotics, and biomedical engineering. His work includes developing algorithms for damage detection in infrastructure and studying collective behavior in biological systems like bird flocks. Culla also explores energy harvesting from vibrations and acoustic optimization in aerospace structures. Key projects include the SUNMARE marine vehicle and OPTYRE tire performance analysis. His methodologies combine statistical energy analysis (SEA), machine learning, and experimental validation. He has contributed to interdisciplinary fields such as biomechanics, robotics, and materials science, with a strong emphasis on real-world applications in automotive, aerospace, and civil engineering sectors.

• Cancer
• Genetics
• Genomics
• +2 more

Paul Thomas Spellman is a Professor in both Medicine and Human Genetics at the University of California Los Angeles (UCLA). His research program focuses on applying genomic and computational technologies to improve human health, with particular emphasis on improving outcomes for cancer patients. He maintains an active laboratory that works across the entire translational spectrum from technology development to clinical implementation. Dr. Spellman received his education from prestigious institutions: SB in Biology from MIT (1995), PhD in Genetics from Stanford University School of Medicine (2000), and postdoctoral training in Gene Regulation/Genomics from UC Berkeley (2003). This strong foundation in both basic and clinical sciences has positioned him at the forefront of cancer genomics research. His research interests span Cancer, Genetics, Genomics, Precision Medicine, and Computational Biology . Dr. Spellman's work bridges fundamental genomic science with clinical applications, particularly in cancer genomics. His laboratory investigates molecular mechanisms of cancer development and progression while developing computational approaches to analyze complex genomic datasets. A significant portion of his research focuses on translating genomic discoveries into clinical practice through biomarker development and implementation science. His work includes systematic analysis of genetic and gene regulation information in clinical cohorts as part of the Genome Data Analysis Network and clinical trials implementing genetic health screening for hereditary breast and ovarian cancer and Lynch syndromes. Analysis of Dr. Spellman's recent publications (2024-2025) reveals a strong focus on cancer genomics, with particular emphasis on tumor evolution, liquid biopsy technologies (ctDNA and cell-free RNA), precision diagnostics, and the molecular basis of cancer progression. His work spans multiple cancer types including breast, prostate, pancreatic, and hematological malignancies, often employing cutting-edge genomic technologies and computational approaches. A notable theme across his publications is the integration of basic science discoveries with clinical applications to improve cancer diagnosis and treatment. Dr. Spellman leads multiple research initiatives including the Genome Data Analysis Network and clinical trials implementing genetic health screening. His laboratory develops and applies genomic technologies across the translational spectrum from basic discovery to clinical implementation. His work on polygenic risk implementation and modeling represents an important frontier in precision medicine. Dr. Spellman's research program includes population-scale studies such as the Healthy Oregon Project, which focuses on statewide cancer research and recruitment approaches for population cohorts. His work on understanding the molecular biology of cellular replication provides fundamental insights that inform his cancer research. The integration of diverse methodologies and approaches across his research program represents a comprehensive strategy to improve cancer outcomes through genomic medicine.

Christine ZargesView profile

Senior Lecturer

• Artificial Intelligence
• Evolutionary Algorithms
• Optimization
• +3 more

Christine Zarges is a Senior Lecturer in the Department of Computer Science at Aberystwyth University. Her research focuses on evolutionary algorithms, artificial immune systems, and optimization techniques, with applications in data preprocessing, anomaly detection, and bioinformatics. She has contributed significantly to the theoretical foundations of immune-inspired randomized search heuristics and has explored their practical implementations in various domains. Her work often addresses challenges in combinatorial optimization, such as improving variable orderings in OBDDs and developing efficient algorithms for Lyndon factorization of biosequences. Recent projects include applications of adversarial diffusion for video anomaly detection and the use of rough set theory for big data preprocessing. She has also been involved in initiatives to address bias in physical science and engineering research. Christine has led and collaborated on externally funded projects, including the Horizon 2020-funded RoSTBiDFramework project and EPSRC grants focused on bias reduction in STEM fields. She has supervised graduate students, such as Yumna Zahid, whose work contributes to video anomaly detection. She actively contributes to the academic community by organizing conferences like EvoCOP and the Genetic and Evolutionary Computation Conference (GECCO), and serves on editorial boards of journals including Evolutionary Computation and IEEE Transactions on Evolutionary Computation .

Thomas LaFramboiseView profile

Professor

• Cancer Genomics
• Bioinformatics
• Computational Biology
• +3 more

Dr. Thomas LaFramboise is a Professor in the Department of Genetics and Genome Sciences at Case Western Reserve University School of Medicine . He serves as a member of the Cancer Genomics and Epigenomics Program within the Case Comprehensive Cancer Center. His research focuses on computational oncogenomics and bioinformatics methodology for identifying molecular variants in cancer. Key areas include: Development of R software packages for genomic data analysis Statistical modeling of SNP microarray data in tumors Investigation of germline-somatic interactions in myeloid malignancies Exploration of mitochondrial DNA dynamics in cancer progression Recent publication trends show interdisciplinary work spanning hematologic malignancies , solid tumors , and neurodegenerative disease models . His group integrates high-dimensional data mining with experimental validation in human cancer cells. Contact: thomas.laframboise@case.edu

• Game Theory
• Evolutionary Algorithms
• Artificial Immune Systems
• +6 more

Paweł Jarosz serves as an Assistant Professor in the Department of Computer Science at the Faculty of Computer Science and Telecommunications , Cracow University of Technology. His work bridges computational intelligence with engineering applications. Academic Rank: Assistant Professor Department: Computer Science Faculty: Computer Science and Telecommunications University: Cracow University of Technology Research focuses on game theory, evolutionary algorithms, and multi-objective optimization, particularly in: Development of immune-inspired game-theoretic optimization methods Multi-criteria decision-making systems MEMS design optimization Biologically-inspired algorithmic frameworks Sustainable transportation modeling Distributed computing environments His publications (2010-2024) demonstrate sustained research in combining game theory with artificial immune systems for complex optimization challenges across various domains including microactuator design and spatial data analysis.

• Bioinformatics
• DNA Sequencing
• Genomics
• +3 more

Dries Decap is a postdoctoral researcher at the Faculty of Engineering and Architecture, Ghent University, within the Department of Information Technology (INTEC). His work focuses on bioinformatics, DNA sequencing, and computational biology with applications in genomics and high-performance computing. Research Interests: Dr. Decap specializes in developing scalable bioinformatics frameworks for DNA and RNA sequencing analysis, including tools like elPrep and Halvade . His research spans variant calling, motif discovery, and parallel computing implementations. Projects: He led his doctoral project (2011-2017) on "Doctoral project Dries Decap" under supervisors Bart Dhoedt and Jan Fostier. He also contributed to projects like IAMBEE for adaptive pathway analysis and BLSSpeller for regulatory motif discovery. Collaborations: Collaborators include Kathleen Marchal, Charlotte Herzeel, and Pascal Costanza. He has worked with institutions like IMEC and Ghent University on scalable genomic data processing solutions.

Elisa LaurentiView profile

Professor

• Stem Cell Biology
• Hematopoiesis
• Single-Cell Biology
• +5 more

Professor Elisa Laurenti holds a faculty position at the Cambridge Stem Cell Institute and Department of Haematology, University of Cambridge. Her research focuses on understanding human hematopoietic stem cell (HSC) biology across health, aging, and disease contexts. Cambridge Stem Cell Institute Department of Haematology, University of Cambridge Research Overview: Elisa's lab employs single-cell biology techniques to investigate HSC functional heterogeneity, stress responses, and age-related changes that impact regenerative medicine and blood cancer therapies. Key areas include: Transcriptional landscapes of HSCs across hematopoietic sites Stem cell adaptation to ex vivo culture Molecular mechanisms of erythroid priming in β-thalassemia Clonal dynamics during human aging Stress-induced signaling pathways (TGFβ, TNFα-NFκB) Stem cell-niche interactions in health and disease Scientific Awards: International Society for Experimental Hematology Janet Rowley Award (2021) Key Contributions: Elisa's work has advanced understanding of: Human HSC dormancy regulation Extramedullary hematopoiesis mechanisms Chemotherapy-induced genomic toxicity Functional assays for HSC lineage commitment Computational models of clonal dynamics Laboratory: Located at the Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, her group includes postdocs, PhD students, and research associates investigating HSC behavior through experimental and computational approaches. Funding sources include Wellcome Trust , Royal Society, Aging Biology Foundation, and Leukemia & Lymphoma Society.

Burcu ÇARKLI YAVUZView profile

Assistant Professor

• Data Mining
• Bioinformatics
• Artificial Intelligence
• +3 more

Burcu ÇARKLI YAVUZ serves as an Assistant Professor at Sakarya University's Faculty of Computer and Information Sciences, Department of Information Systems Engineering. Her academic career spans over a decade with continuous contributions since 2013, including current administrative roles as Dean's Assistant (2023-2024) and Department Vice Chair (2021-2023). Education: PhD in Computer and Information Engineering (2019), Sakarya University - Thesis: 'Hemoglobin Protein Secondary Structure Prediction by Improved Clonal Selection Algorithm' MS in Computer and Information Engineering (2010), Sakarya University - Thesis: 'A Data Mining Application with Apriori Algorithm in the Healthcare Sector' BSc in Mathematics-Computer Programming (2005), Istanbul Cultural University Her research integrates artificial intelligence with critical applications across healthcare and renewable energy. Specializing in data mining and bioinformatics, she develops novel algorithms for protein structure prediction, medical diagnostics, and photovoltaic system optimization. Current work focuses on Marine Predators Algorithm applications for perinatal mental health screening and adaptive MPPT techniques for solar energy systems, demonstrating interdisciplinary impact from biomedical engineering to climate change mitigation. Publication analysis reveals three dominant research thrusts: (1) AI-driven healthcare solutions (depression/anxiety detection, diabetes diagnosis), (2) Photovoltaic optimization (MPPT algorithms, flicker analysis), and (3) Bioinformatics (protein structure prediction using clonal selection). Her work consistently bridges theoretical algorithm development with practical implementations, evidenced by industry collaborations like the 2023 'Electric Vehicle Regulation-Compliant Sound Alert Systems' project. Teaching responsibilities include graduate and undergraduate courses in Deep Learning, Python Programming, Operations Research, and Introduction to AI. She has supervised numerous graduation projects and taught specialized courses like 'Big Data Technologies' in collaboration with Havelsan. Her editorial service for IEEE Access (2018-2020) and conference organization roles demonstrate academic leadership beyond teaching and research.

Lynn B. JordeView profile

Professor

• Human Genetics
• Genetic Variation
• Disease-Gene Identification
• +5 more

Lynn B. Jorde, Ph.D. , is a Professor in the Department of Human Genetics at the University of Utah. His research focuses on human genetic variation, disease-gene identification, and the evolutionary dynamics of mobile elements. Using Utah’s large families and Tibetan populations, he has pioneered studies on mutation rates, high-altitude adaptation, and complex disease genetics. Institute: Eccles Institute of Human Genetics (EIHG), University of Utah Key Collaborators: Joseph T. Prince, Lynn B. Jorde, Mark Yandell Research Interests include: Estimating intergenerational mutation rates via whole-genome sequencing of three-generation families Identifying genes under natural selection in Tibetan high-altitude adaptation Studying mobile element retrotransposition and its genomic impacts Investigating genetic factors in preterm birth, ALS, schizophrenia, and hypertension Publication Trends span computational genomics, human evolution, and clinical applications. His articles from 2018–2025 explore variant prioritization tools (VVP), germline mutation dynamics, and ancestry-disease associations, with a focus on structural variants and population-specific adaptations. Lab Affiliations include the Eccles Institute of Human Genetics (EIHG) in Salt Lake City, where he leads research on: Genomic instability in cancer and neurological diseases Mobile element biology in diverse populations Pharmacogenomics and reproductive health Contact: lbj@genetics.utah.edu | Office: 801.581.4566 | Lab: EIHG 7220B

Gabor MarthView profile

Professor

• Computational Genomics
• Precision Oncology
• Rare Disease Diagnostics
• +3 more

Gabor Marth is a Professor of Human Genetics and Co-Director of the Utah Center for Genetic Discovery at the University of Utah Medical School. Holding the H.A. and Edna Benning Presidential Endowed Chair , he develops computational tools for genomic analysis, including standardized formats like SAM/BAM and VCF . His lab focuses on precision oncology, rare disease diagnostics, and somatic mosaicism discovery, with funding from NIH institutes and private foundations. Current Research Areas Machine learning for cancer therapy selection Reference-free somatic mutation detection Phenotype-driven patient matching Real-time genomic data visualization Leadership Roles Principal Investigator, NHGRI/NIH grants Co-founder & Chief Scientific Officer, Frameshift Genomics Scientific Advisory Board, Ontario Institute for Cancer Research His team has published extensively on variant calling algorithms, tumor subclone reconstruction, and clinical implementation of genomic tools. Recent work includes deep learning frameworks for breast cancer treatment selection and single-cell RNA sequencing applications in neurological disorders. Scientific Awards : H.A. and Edna Benning Presidential Endowed Chair Advisees : Gage Black (Bioinformatics Scientist) Isabelle Cooperstein (PhD Student) Taeho Kim (PhD Student) Patrick Ozark (MD/PhD Student) Aniruddh Saxena (PhD Student) Casey Sederman (MD/PhD Student) Stephanie Gardiner (PhD Student) Lab members also include senior software engineers and researchers working on clinically driven variant analysis and tumor modeling.

Frederick MatsenView profile

Professor

• Computational Biology
• Phylogenetics
• Evolutionary Immunology
• +5 more

Dr. Frederick "Erick" Matsen is a Professor in the Public Health Sciences Division at Fred Hutchinson Cancer Research Center, where he serves as Associate Program Head of the Herbold Computational Biology Program. He is also an Affiliate Associate Professor of Genome Sciences and Statistics at the University of Washington and a Howard Hughes Medical Institute Investigator. Dr. Matsen leads the Matsen Lab, which focuses on computational approaches to evolutionary biology and immunology. Dr. Matsen's research centers on computational biology, particularly developing algorithms to analyze biological data from DNA sequencing of viruses, immune cells, and complex environmental samples. His team works on phylogenetic methods, evolutionary tree construction, and software development for computational biology. Key research areas include Bayesian phylogenetics via optimization , phylodynamics with many sequences , antibody sequence analysis , and learning immune mechanisms from receptor sequences . His work bridges mathematics, computer science, and biological discovery, with applications to HIV, SARS-CoV-2, and other pathogens. The Matsen Lab has developed numerous influential resources including phyloseminar.org, B-T.CR, and phylobabble.org. Recent publications demonstrate a strong focus on machine learning applications in phylogenetics, antibody evolution analysis, and computational approaches to viral evolution. His team's work has significant implications for understanding immune responses to pathogens and developing better vaccines and treatments. Howard Hughes Medical Institute Investigator (2021-present) Howard Hughes Medical Institute-Simons Foundation Faculty Scholar Dr. Matsen maintains an active mentoring program, with an impressive track record of trainees securing tenure-track faculty positions. His lab fosters a collaborative environment where biologists learn analytical tools and computational scientists work directly with biological problems. Current projects include developing computational methods for outbreak control and analyzing antibody responses to SARS-CoV-2 using phage-immunoprecipitation sequencing. The Matsen Lab operates within Fred Hutch's collaborative ecosystem, including membership in the Immunotherapy Integrated Research Center, Pathogen-Associated Malignancies Integrated Research Center, and Translational Data Science Integrated Research Center. The lab has recently moved to the Lake Union Steam Plant facility, specifically designed to facilitate collaboration between clinical researchers, data scientists, and evolutionary biologists.

• Virology
• Immunology
• Hepatitis C Virus
• +5 more

Alexander Paul James Underwood serves as an Assistant Professor in Virology within the Department of Immunology and Microbiology at the University of Copenhagen's Faculty of Health and Medical Sciences. His research focuses on viral immunology with particular emphasis on hepatitis viruses and SARS-CoV-2. He maintains active collaborations with leading researchers including Jens Bukh and Nina Weis. Underwood's research investigates critical aspects of viral pathogenesis and immune responses. His work examines T cell exhaustion in hepatitis C virus (HCV) infection, viral evolution under immune pressure in hepatitis B, and mechanisms of SARS-CoV-2 entry and neutralization. Key research areas include viral spike protein dynamics, monoclonal antibody development, vaccine efficacy against emerging variants, and the interplay between B-cell responses and viral reinfection outcomes. Analysis of his recent publications reveals strong trends in viral immunology with significant contributions to understanding immune evasion mechanisms. His work spans multiple viral systems but maintains consistent focus on host-pathogen interactions at the molecular level, particularly regarding viral entry mechanisms, antibody neutralization, and T-cell responses. The publications demonstrate interdisciplinary approaches combining virology, immunology, and structural biology. While no specific scientific awards are listed in the available information, his research has garnered attention across multiple platforms including news outlets, social media (X, Bluesky, Reddit), and academic networks like Mendeley. Underwood actively participates in collaborative research networks, particularly with the Bukh laboratory at the University of Copenhagen. His work involves both experimental virology and computational analyses, suggesting involvement in multidisciplinary research teams focused on viral pathogenesis and immune responses. The publications indicate leadership roles in several studies examining viral evolution and immune escape mechanisms. His laboratory work appears centered on viral culture systems, particularly using Vero cells for SARS-CoV-2 adaptation, and employs advanced techniques for analyzing T-cell and B-cell responses. The research spans both basic virology investigations and translational applications for vaccine and therapeutic development.