Find Academic Supervisors

• Neuroblastoma
• Pediatric Oncology
• Translational Research
• +3 more

Dr. Katherine Matthay is a **Professor in the Department of Pediatrics at the UCSF School of Medicine** and the **Leader of the Pediatric Malignancies Program** in the Helen Diller Family Comprehensive Cancer Center. Her work focuses on **translational research in neuroblastoma**, with a particular emphasis on improving therapies and global oncology initiatives. She has led the **Global Neuroblastoma Network**, an international tumor board for resource-limited countries, and contributed to clinical trials and protocols for neuroblastoma treatment. **Research Interests**: Dr. Matthay’s research spans neuroblastoma biology, therapeutic strategies, and global health. She explores mechanisms driving tumor progression, drug resistance, and the development of targeted therapies. Her global efforts include mentoring projects in Africa and Central America, and adapting treatments for low-resource settings. **Articles**: Her recent work includes studies on Aurora Kinase A inhibition, ALK-driven therapies, and predictive biomarkers for MIBG response. These articles highlight advancements in drug combinations, molecular pathways, and global collaboration. **Awards**: While no specific awards are listed here, her contributions to neuroblastoma research and global health are widely recognized in the field. **Advising & Grants**: She leads large-scale clinical trials and collaborates with international teams. Her work includes optimizing response criteria and post-treatment follow-up in neuroblastoma. **Labs/Teams**: Active in the Helen Diller Cancer Center and the Global Neuroblastoma Network, fostering multidisciplinary approaches to pediatric oncology.

Chiara SabattiView profile

Professor

• Statistical Genetics
• Computational Biology
• Bayesian Statistics
• +2 more

Chiara Sabatti is a Professor of Biomedical Data Science and Statistics at Stanford University, with affiliations to the Stanford Center for Computational, Evolutionary and Human Genomics (CEHG), Bio-X, and the Stanford Cancer Institute. She serves as Associate Director for Stanford Data Science and has led the development of the Data Science Major curriculum since 2012. Research Focus: Statistical models for high-throughput genomics data, causal inference in genetic studies, false discovery rate control, and knockoff methods for variable selection. Key Leadership: Associate Chair for Education and Training (2020-present), Vice Chair of Biomedical Data Science (2018-2019). Her work bridges statistical genetics with data science education, emphasizing robustness and interpretability in scientific findings. Recent publications highlight innovations in genome-wide association studies (GWAS), causal variant localization, and cost-effective sequencing techniques for underrepresented populations. Current projects include developing knockoff-based methods to address population structure and multi-resolution hypothesis testing. Scientific Awards: Institute of Mathematical Statistics (IMS) Fellow (2022) NSF CAREER Award (2003-2008) She mentors doctoral and graduate students in Biomedical Data Science, collaborates with the Data Studio on interdisciplinary projects, and actively recruits curious researchers to her lab. Her outreach efforts focus on expanding data science education and increasing research participation from underrepresented groups.

Rachel EE Pui LaiView profile

Associate Professor

• Cancer Therapeutics
• Antimicrobial Peptides
• Drug Delivery Systems
• +5 more

Associate Professor Rachel EE Pui Lai is affiliated with the Department of Pharmacy and Pharmaceutical Sciences at the National University of Singapore (NUS), part of the Faculty of Science. Her research focuses on cancer therapeutics, antimicrobial peptides, drug delivery systems, and regenerative medicine. She holds a BSc (Pharm) from NUS and a PhD from the University of Illinois at Chicago. Research Interests: Development of antimicrobial peptides and peptoids targeting drug-resistant bacteria and mycobacteria. Design of hydrogels for stem cell delivery, wound care, and bioprinting applications. Wnt signaling pathway modulation in cancer and neuroprotection. Her work emphasizes translational research, including collaborations with institutions like the University of Tromsø and the Max Planck Institute. Recent studies highlight innovations in peptide-based therapies and biomaterials for combating antibiotic resistance. Grants & Advising: Advises PhD and Master's students on projects involving antimicrobial nanonets, hydrogel engineering, and peptide design. Students have won awards such as the 'Best Poster' at the Amgen Scholars Asia Symposium and the Marie Skłodowska-Curie Fellowship. Lab Activities: The Ee Research Group focuses on pharmaceutical science innovations, including the development of anti-infective biomaterials and drug delivery systems. Hosts international conferences and collaborates globally through programs like the IPSF exchange.

• Immunology
• Systems Biology
• Genomics
• +4 more

Dr. Masahiro Ono is a Reader in Immunology at Imperial College London's Department of Life Sciences, within the Faculty of Natural Sciences. He leads research on T-cell regulation, focusing on autoimmunity, infections, and cancer. His lab pioneered the Tocky system, using Fluorescent Timer proteins to study T-cell activity dynamics in vivo. Dr. Ono holds affiliations with the CRUK Convergence Science Centre, Infection and Immunity, and Integrative Systems Biology. His academic journey includes an MD from Kyoto University (1993-1999) and a PhD in regulatory T cells (2002-2006). He was awarded a HFSP Fellowship (2009) and BBSRC David Phillips Fellowship (2012), establishing his UCL lab before joining Imperial in 2015. Research Interests : Dr. Ono's work bridges immunology, genomics, and systems biology. His lab explores T-cell activation mechanisms, tumor immunology, and bioinformatics tools for single-cell analysis. Key innovations include the Tocky system for real-time cell kinetics tracking and integrative approaches like GatingTree for cytometry data analysis. Awards : HFSP Fellowship (2009) BBSRC David Phillips Fellowship (2012) Grants & Advising : Dr. Ono's grants have supported projects on viral latency, tumor microenvironment modulation, and immune checkpoint therapies. His lab actively collaborates on translational research, though specific grant details are not listed here. Labs & Teams : His lab at Imperial focuses on Tocky-based technologies and interdisciplinary convergence science through the CRUK Centre. Collaborations span virology, oncology, and bioengineering to address unmet clinical needs in immunotherapy.

• Biomedical Engineering
• Tissue Engineering
• 3D Printing
• +5 more

Neil Lin is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at the University of California, Los Angeles (UCLA), with a joint appointment in Bioengineering. His research focuses on developing 3D-printed tissues that replicate the structure, mechanics, and functionality of human organs, with applications in drug screening and regenerative medicine. Lin leads the Lin Lab - Living Soft Material Engineering , advancing soft and living material engineering through interdisciplinary approaches. Lin holds a Ph.D. and M.S. in Engineering from Cornell University (2016 and 2013) and a B.S. in Engineering from National Tsing Hua University, Taiwan (2008). His work spans biomaterials mechanics, quantitative imaging, and AI-driven biological analysis. Research interests include the structure and dynamics of soft biomaterials, image-based force measurements, and quantitative imaging techniques for material characterization. Recent work explores cell morphology regulation, AI applications in microscopy, and mechanical heterogeneity in live tissues. Lin’s publications highlight advancements in cell trapping, AI-based image translation, and prostate cancer metabolism modeling. He has received prestigious awards, including the Young Investigator Award (2022), Hellman Fellowship, and NIH Maximizing Investigators' Research Award (2022). His lab integrates engineering and biology to address challenges in tissue engineering, with ongoing projects on 3D kidney models, drug response assays, and AI-driven phenotyping of senescent cells.

Pengyi YangView profile

Associate Professor

• Computational Systems Biology
• Stem Cell Biology
• Bioinformatics
• +4 more

Pengyi Yang is an Associate Professor and University of Sydney Robinson Fellow at the School of Mathematics & Statistics, University of Sydney. He leads the Computational Systems Biology group at the Charles Perkins Centre and holds a conjoint appointment as Unit Head of Computational Systems Biology at the Children's Medical Research Institute (CMRI). His research focuses on computational approaches to understand trans-regulatory networks in stem cells and their applications in regenerative medicine. Yang holds a Ph.D. and has been recognized with awards such as the National Stem Cell Foundation Metcalf Prize (2021). His research spans computational systems biology, machine learning for bioinformatics, and spatial/single-cell omics analysis. Key projects include modeling pluripotency transitions, developing stem cell-derived organoids, and creating computational tools for phosphoproteomics and multi-omics integration. Collaborations include international initiatives like the Laboratory of Data Discovery for Health (InnoHK). Yang advises multiple PhD students and leads grants on topics like stem cell-derived brain organoids and embryonic development modeling. His lab develops tools like Cepo, PhosR, and CiteFuse for omics data analysis. He teaches data science and molecular systems biology at the University of Sydney.

Heike KrebberView profile

Professor

• mRNA Quality Control
• ncRNA Functions
• Molecular Biology
• +3 more

Prof. Heike Krebber is a Professor for Molecular Genetics at Georg-August University Göttingen, Germany. Her research focuses on mRNA quality control and non-coding RNA functions, using the model organism Saccharomyces cerevisiae. She has held positions at the DKFZ (Heidelberg), Harvard Medical School, and Philipps-Universität Marburg. Her work addresses how mRNA processing defects contribute to diseases like cancer and neurodegeneration. Education & Positions: PhD (1996), Deutsches Krebsforschungszentrum Heisenberg Fellow (2006) Habilitation in Molecular Biology (2005) Professor since 2010 at Georg-August University Research Interests: Her lab investigates: RNA quality control mechanisms ensuring proper mRNA maturation and export Functions of non-coding RNAs (e.g., lncRNAs in iron metabolism and telomerase) Ribosome assembly and translation termination pathways Stress-induced bypass of mRNA quality control Awards: Heisenberg Fellowship (2006) Grants & Teams: Leads the Molecular Genetics group at the Institute for Microbiology and Genetics. Collaborates with the IMPRS Molecular Biology and GZMB (Molecular Biology of Cells) programs. Labs & Affiliations: Her group is part of the GGNB network, focusing on Microbiology and Biochemistry. The lab’s work spans fundamental molecular mechanisms with translational disease relevance.

Shahar KovalskyView profile

Assistant Professor

• Optimization
• Geometry
• Computer Graphics
• +4 more

Shahar Kovalsky is an Assistant Professor of Mathematics at the University of North Carolina at Chapel Hill (UNC-CH), with secondary appointments in the School of Data Science and Society and an adjunct role in the Department of Computer Science (both within the College of Arts and Sciences). He holds a Ph.D. in Computer Science and Applied Mathematics from the Weizmann Institute of Science, and B.Sc./M.Sc. degrees in Mathematics and Electrical Engineering from Ben-Gurion University. His research bridges optimization, geometry, computer graphics, machine learning, and their applications in biology and medicine. Kovalsky's work includes advancements in geometric modeling, medical imaging diagnostics, and evolutionary biology analysis. He has been recognized with awards such as the Günter Enderle Best Paper Award (Eurographics 2016) and the SGP 2015 Best Paper Award. Education: Ph.D., Computer Science & Applied Mathematics, Weizmann Institute of Science, Israel B.Sc./M.Sc., Mathematics & Electrical Engineering, Ben-Gurion University, Israel Research Interests: His work focuses on geometric optimization, machine learning for medical diagnostics (e.g., thyroid cytopathology), and computational methods in evolutionary biology. He develops algorithms for injectivity-preserving parameterizations, medical image analysis, and Gaussian process landmarking for morphometric studies. Key Contributions: Deep learning models for thyroid cancer prediction from smartphone images Geometric algorithms for surface parameterization and injectivity Applications of Gaussian processes in evolutionary shape analysis Awards: Günter Enderle Best Paper Award (Eurographics 2016) SGP 2015 Best Paper Award Teaching & Mentoring: Kovalsky advises graduate and undergraduate students (e.g., Fengyu Yang, Maddy Vinal) and teaches courses like Optimization in Machine Learning at UNC-CH. He also co-advises students in interdisciplinary projects with Caroline Moosmüller and Jeremy Marzuola. Labs & Affiliations: Member of the Carolina Center for Interdisciplinary Applied Mathematics (CCIAM) and previously a Phillip Griffiths Assistant Research Professor at Duke University (2017-2020).

Azhar ZamView profile

Associate Professor

• Biomedical Optics
• Optical Coherence Tomography (OCT)
• Photoacoustics
• +5 more

Azhar Zam is an Associate Professor of Bioengineering at NYU Abu Dhabi (NYUAD) and associated faculty at NYU Tandon School of Engineering's Biomedical and Electrical Engineering departments. He holds a B.Sc. from University of Indonesia, M.Sc. from University of Luebeck (Germany), and Ph.D. from Friedrich-Alexander-University Erlangen-Nuremberg (Germany). His research focuses on developing smart optical devices for medical imaging/diagnostics, including laser surgery, OCT, photoacoustics, and AI-driven imaging systems. He leads the Laboratory for Advanced Bio-Photonics and Imaging (LAB-π) at NYUAD and has authored 85+ publications/patents. Education: Bachelor of Science, University of Indonesia M.Sc. Biomedical Engineering, University of Luebeck Ph.D. Engineering, Friedrich-Alexander-University Erlangen-Nuremberg Research Interests: Innovations in biomedical optics, optical-based smart sensors, AI-enhanced diagnostics, and miniaturized medical imaging systems. His work integrates advanced optical technologies with surgical robotics and clinical applications. Professional Contributions: Associate Editor for Frontiers in Photonics Biophotonics section; Reviews Editor for Frontiers in Ophthalmology Retina section. Previously held positions at University of Basel (Assistant Professor), University of Waterloo, and other institutions globally. Labs & Teams: Directs NYUAD's LAB-π lab focusing on bio-photonics innovations. Collaborates across NYU's global network and international partners.

Svetlana YanushkevichView profile

Professor

• Biometric Technologies
• Machine Learning
• Signal Processing
• +3 more

Dr. Svetlana Yanushkevich is a Professor in the Department of Electrical and Software Engineering at the Schulich School of Engineering, University of Calgary. She is also a Full Member of the Hotchkiss Brain Institute and the Mathison Centre for Mental Health Research and Education. Her research focuses on biometric technologies, decision support systems, biomedical applications, and computational intelligence. She leads the Biometric Technologies Laboratory, developing strategies for risk assessment in biometric systems and healthcare monitoring through machine reasoning and signal processing. Education : BSc/MSc in Electrical Engineering (1989), State University of Informatics and Radioelectronics, Minsk PhD in Electrical Engineering (1992), same institution Dr. Habilitated in Technical Sciences (1999), Warsaw University of Technology Research Interests : Dr. Yanushkevich’s work spans biometric system design (e.g., gait analysis, facial attributes), decision support via probabilistic models (Bayesian networks, causal inference), biomedical applications (stroke rehabilitation, wearable sensors), and computational intelligence for data science. She emphasizes fairness, bias mitigation, and trustworthiness in AI systems, particularly in healthcare and accessibility contexts. Recent Research Trends : Her recent publications address causal modeling for accessibility barriers, UAV operator cognitive workload, and medical device optimization in radiation therapy. She explores AI ethics, stress contagion in human-robot teams, and cross-spectral biometric systems. Awards & Recognition : 2024 FEIC Fellow (Engineering Institute of Canada) 2019 Research Excellence Award (Schulich School of Engineering) 2001 Senior IEEE Membership Advising & Grants : She coordinates courses like ENCM 509 (Biometric Systems Design) and ENEL 610 (Biometric Technologies). Her research is supported by grants focusing on healthcare AI, accessibility technologies, and computational epidemiology. Labs & Collaborations : Her Biometric Technologies Lab collaborates with institutions like Hokkaido University and the IEEE Computational Intelligence Society. Projects include wearable health monitoring, decision support platforms, and AI-driven epidemiological modeling.

• Game Theory
• Reputation
• Law
• +7 more

Marco Celentani is an Associate Professor at Universidad Carlos III de Madrid and currently serves as Director of the PhD School. He holds a Ph.D. in Economics from the University of California, Los Angeles (UCLA). His research focuses on Game Theory, Reputation, Law, Contract Theory, Corporate Governance, and Political Economy, with recent emphasis on economic voting, trust dynamics, debtor protection, and legal aid. Key contributions include analyses of bankruptcy regimes, executive compensation mechanisms, corruption dynamics in public procurement, and inflation in open economies. His work bridges theoretical frameworks with applied policy analysis, particularly in legal and institutional contexts. Celentani has published extensively in top journals like Economic Theory , Review of Economic Dynamics , and European Economic Review . His research often addresses real-world challenges in market efficiency, institutional design, and public policy.

Marina VannucciView profile

Professor

• Bayesian statistics
• Variable selection
• Graphical models
• +5 more

Marina Vannucci is the Noah Harding Professor of Statistics at Rice University, with an adjunct appointment at the UT MD Anderson Cancer Center. She holds a Ph.D. and Laurea in Mathematics from the University of Florence, Italy. Her research focuses on Bayesian statistical methods for complex problems in genomics, neuroimaging, and engineering. She has supervised 31 Ph.D. students and 13 postdocs, published over 185 papers, and received prestigious awards including the Mitchell Prize, Zellner Medal, and Don Owen Award. She has served as Editor-in-Chief of Bayesian Analysis and co-Editor of the Journal of the American Statistical Association. Education: Ph.D. in Statistics (University of Florence, 1996), Laurea in Mathematics (University of Florence, 1992). Research Interests: Bayesian statistics, variable selection, graphical models, statistical computing, applications in genomics, neuroscience, and engineering. Awards: Includes Fellowships from ASA, IMS, AAAS, ISBA, and the 2020 Zellner Medal. Recent recognitions include the 2025 Don Owen Award for excellence in research and contributions to the statistical community. Grants/Advising: Over 30 Ph.D. students and 13 postdocs trained. Key roles include Department Chair (2014–2019) and President of the International Society for Bayesian Analysis (2018). Labs/Teams: Affiliated with Rice Neuroengineering, Ken Kennedy Institute, and the W.M. Keck Center for Interdisciplinary Bioscience Research.

Yang KuangView profile

Professor

• Mathematical Biology
• Mathematical Oncology
• Population Dynamics
• +3 more

Yang Kuang is Professor of Mathematics at Arizona State University's School of Mathematical and Statistical Sciences, with joint affiliations with the CRESMET and Mathematical Computational Modeling Sciences Center. His research bridges mathematical biology, oncology, population dynamics, and delay differential equations. His cancer modeling investigates glioblastoma growth mechanisms, tumor-immune interactions, and prostate cancer treatment optimization. Ecological work pioneers stoichiometric modeling of producer-grazer systems and virus-host-environment interactions. He directs NSF-funded projects including 'Mathematical Classification of Complexity in Population Dynamics' and 'Predictive Modeling of Pattern Formation'. Publications demonstrate recurring themes: reaction-diffusion tumor models, wastewater-based epidemiology during pandemics, and ecological stoichiometry. His textbook Introduction to Mathematical Oncology establishes core frameworks for cancer modeling.

• Optimization Algorithms
• Smart Grids
• Renewable Energy Systems
• +3 more

Silvia Jiménez Fernández is an Associate Professor in the Department of Signal Theory and Communications at Universidad Autónoma de Madrid. Her research focuses on optimization algorithms, smart grids, renewable energy systems, telemedicine, and machine learning applications. She holds a Ph.D. from Universidad Politécnica de Madrid (2009), supervised by Dr. Francisco del Pozo Guerrero and Dr. Paula de Toledo Heras. Her work integrates interdisciplinary approaches, such as combining evolutionary algorithms with engineering challenges in energy systems and healthcare. Key contributions include advancements in coral reefs optimization algorithms for energy management, machine learning for battery health estimation, and telemedicine systems for chronic disease monitoring. Recent research trends emphasize hybrid learning models in education, multi-objective optimization in renewable energy systems, and risk analysis in smart grids with electric vehicles. She is affiliated with the GHEODE Research Group (Modern Heuristics and Network Design).

Kim O'SullivanView profile

Research Fellow

• Immunology
• Autoimmune Diseases
• Kidney Disease
• +13 more

Dr. Kim O'Sullivan is a Senior Research Fellow and head of the Translational Kidney Therapies Group at the Centre for Inflammatory Diseases (CID), Monash Health Translational Precinct, affiliated with Monash University’s Faculty of Medicine, Nursing and Health Sciences. She holds a PhD in Immunology from Monash University and completed her undergraduate and Master’s studies in Anatomy and Structural Biology at the University of Otago, New Zealand. Her work is centered on developing novel therapies for autoimmune kidney diseases, particularly ANCA-associated vasculitis (AAV), glomerulonephritis, and lupus nephritis. Her research focuses on: Neutrophil Extracellular Traps (NETs) and their role in inflammation Gene therapy using adeno-associated viral vectors to deliver DNase I Therapeutic potential of bacterial exosomes Gut microbiome interactions, especially Muribaculaceae and SCFAs Immune tolerance and host defense preservation Her recent publications (2023–2024) reflect a strong trend in translational immunology, with emphasis on microbiome-immune crosstalk, novel biologics, and gene-based interventions. She has published in high-impact journals such as Frontiers in Immunology , International Journal of Molecular Sciences , and Journal of Immunology . Her scientific contributions have been recognized through several awards: Australian and New Zealand Society of Nephrology Young Investigator Award (Winner, 2016) ANZSN Basic Science Award (Finalist, 2020) Multiple ANZSN Travel Awards (2014, 2016, 2017) Kim O'Sullivan actively supervises Honours and PhD students and leads multiple research projects funded by NHMRC and MRFF. She serves on the ANZSN Scientific Programme and Awards Committee (SPARC), is a Review Editor for Frontiers in Immunology , and sits on the editorial boards of International Journal of Molecular Sciences and Journal of Integrated Medicine in Nephrology and Andrology . She is also a peer reviewer for top journals including Journal of Clinical Investigation and Kidney International . She leads the CID weekly seminar series and chaired the ImmuMON21 symposium. Her commitment to equity in STEM includes mentoring through BrainSTEM and past involvement in the ANZSN Equity, Diversity and Inclusion Committee.