Dr. Beibei Ren is an Assistant Professor in the Department of Mechanical Engineering at Texas Tech University. She earned her Ph.D. in Electrical and Computer Engineering from the National University of Singapore (NUS) in 2010, followed by postdoctoral work at UCSD and a research fellowship at NUS. Education: Ph.D. in Electrical and Computer Engineering (NUS, 2010) Previous Positions: Postdoctoral Scholar (UCSD, 2010-2013), Research Fellow (NUS, 2009-2010) Her research focuses on dynamic systems and control with applications in renewable energy integration, microgrids, UAVs, MEMS, marine systems, and manufacturing. At Texas Tech, she directs the Dynamic Intelligent Systems, Control and Optimization (DISCO) Group , emphasizing robust control strategies for uncertain systems. The 15 most recent publications highlight her expertise in uncertainty and disturbance estimator (UDE)-based control , with applications in smart grid technologies, wind and solar energy systems, quadrotor robotics, and power electronics. Her work bridges theoretical control theory with practical implementations in renewable energy and autonomous systems. STEM Outreach: Actively promotes diversity in engineering through Texas Tech's STEM CORE programs.
Dr. Thomas A. Hughes is an Associate Professor of Cancer Biology at the University of Leeds and Professor of Biosciences at York St John University. As a Group Leader at the Leeds Institute of Medical Research, he focuses on gene regulation, tumour microenvironment, and nanomedicine approaches to improve cancer outcomes. Specializes in breast cancer, colorectal cancer, and rare diseases Develops therapeutic strategies using microRNAs and biomarkers Collaborates with clinicians, engineers, and chemists for translational research His research integrates molecular pathology with clinical data through partnerships with Leeds NHS Trusts, aiming to identify novel biomarkers and targets for therapy. Recent work emphasizes cholesterol metabolism, oxysterol signaling, and nanomedicine-based drug delivery systems. Key contributions include: Over 80 peer-reviewed publications in cancer biology and molecular therapeutics Leadership in MSc programs in Molecular Medicine and Cancer Biology and Therapy Extensive experience in grant review, editorial work, and doctoral supervision Scientific awards include Fellowship of the Higher Education Academy. His lab has mentored 26 doctoral students and numerous alumni in academia, clinical practice, and industry.
Memorial Sloan Kettering Cancer CenterUnited States
Dr. Christina Leslie is a Research Professor and Member of the Computational & Systems Biology Program at Memorial Sloan Kettering Cancer Center (MSK). She leads an active research laboratory focused on developing computational approaches to understand complex biological systems. Dr. Leslie earned her PhD from the University of California, Berkeley and has established herself as a leading computational biologist in cancer research and immunology. Computational & Systems Biology Program, Memorial Sloan Kettering Cancer Center Gerstner Sloan Kettering Graduate School of Biomedical Sciences Dr. Leslie's research focuses on developing novel computational methods to study cellular biological systems from a global and data-driven perspective. Her lab exploits diverse high-throughput functional and genomic data to understand molecular networks underlying fundamental cellular processes, including transcription regulation, pre-mRNA processing, signaling, and post-transcriptional gene silencing. Her algorithmic methods draw heavily on machine learning to build accurate predictive models from noisy and high-dimensional biological data. Key areas of interest include modeling cell-type specific transcriptional programs and dissecting co- and post-transcriptional regulation, particularly microRNA-mediated gene regulation. Analysis of Dr. Leslie's publication record over the last five years reveals a strong focus on computational approaches to cancer genomics, immunology, and epigenetics. Her work bridges multiple disciplines, with a particular emphasis on developing machine learning methods to interpret complex biological data. The publications demonstrate increasing sophistication in integrating multiple data types (genomic, transcriptomic, epigenomic) to understand cancer biology and immune responses. Recent work shows a growing emphasis on single-cell technologies and spatial analysis of tumor microenvironments. Introduction of string kernel methodology for SVM classification of biological sequences Development of algorithms for predictive modeling of gene regulation First systems-level analyses of competition between microRNAs and between target transcripts Dr. Leslie actively mentors numerous graduate students and research associates, with current lab members including Vianne Gao, Alireza Karbalaghareh, Erik Ladewig, and several others. Her lab has received significant research funding to support their work on computational approaches to cancer biology and immunology. The Leslie Lab maintains close collaborations with multiple experimental groups at MSK, facilitating the translation of computational insights into biological understanding. The Leslie Lab operates within the Computational & Systems Biology Program at MSK, with strong ties to both the research and clinical missions of the institution. The lab maintains state-of-the-art computational infrastructure for analyzing large-scale genomic and proteomic datasets and collaborates extensively with wet-lab researchers to validate computational predictions experimentally.
Ramesh Shanmughom Pillai is a Full Professor at the Department of Molecular Biology, University of Geneva, Switzerland. He holds additional roles as a Visiting Professor at the University of Kumamoto, Japan, and has been a Group Leader at EMBL Grenoble and a postdoctoral fellow at the Friedrich Miescher Institute. His research focuses on RNA modifications, epigenetics, and piRNA pathways in germline biology. Pillai has received prestigious awards including the ERC Consolidator Grant and The RNA Society Scaringe Award. Education: BSc Botany (University of Kerala, India) MSc Biotechnology (IIT Roorkee, India) PhD in Cell Biology (University of Bern, Switzerland) Research Interests: Pillai’s work centers on RNA biology, particularly the role of RNA modifications (e.g., m6A, m6Am) in development and fertility. He investigates piRNA biogenesis, transposon silencing, and the molecular mechanisms of RNA-protein interactions. His studies bridge biochemistry, genetics, and structural biology to elucidate how RNA molecules regulate critical biological processes. Teaching & Service: At the University of Geneva, he teaches Molecular Biology courses (BSc/MSc levels) and advises 5 PhD students and 4 postdocs. He chairs the ERC Consolidator Grant Review Panel and organizes major conferences like the PIWI/piRNAs Meeting and Swiss RNA Workshop. Pillai also serves on editorial boards for Nucleic Acids Research and RNA . Awards: ERC Consolidator Grant (2015) Best PhD Thesis Award (2003) RNA Society Scaringe Award (2005) Grants & Labs: Funded by ERC Starting and Consolidator Grants, his lab explores RNA modification networks in germ cells. Former trainees include Professors Simon Conn (Flinders University) and Hao Wu (CAS, China).
Igor Jurisica is a Professor at the University of Toronto and a Senior Scientist at the Krembil Research Institute’s Data Science Discovery Centre for Chronic Diseases. He also serves as Visiting Scientist at IBM CAS, Scientific Director of the World Community Grid, and Chief Scientist at the Creative Destruction Lab (Rotman School of Management). His research focuses on integrative computational biology, data mining, and AI-driven models for cancer mechanisms, drug discovery, and chronic disease management. Key affiliations include the Osteoarthritis Research Program, Schroeder Arthritis Institute, and leadership roles in open science initiatives like the World Community Grid, a global distributed computing platform with 810,000+ volunteers. Jurisica’s work bridges computational tools (e.g., NAViGaTOR visualization platform, MirDIP databases) and clinical applications, emphasizing explainable AI in healthcare. Research interests span proteomics, microRNA regulation, systems vaccinology, and multi-omics integration for disease stratification. Notable contributions include identifying prognostic signatures in cancer and osteoarthritis, machine learning models for drug repurposing, and sportomics analyses of athletic biomarkers. He has been recognized as a Thomson Reuters Highly Cited Researcher (2014-2016) and ranked among the Top 100 AI Leaders in Oncology (2023). His labs develop open-access tools like PathDIP, OsteoDIP, and miRAnno to advance translational research.
Pingfu Fu, PhD, is a Professor in the Department of Population and Quantitative Health Sciences at Case Western Reserve University's School of Medicine. He is also a member of the Developmental Therapeutics Program at the Case Comprehensive Cancer Center. His expertise spans biostatistics, mathematics, and computer science, with a focus on cancer research and HIV/AIDS. Dr. Fu advises researchers on study design and statistical methodology for clinical and pre-clinical studies. He teaches courses in survival data analysis and clinical trials, and was recognized as 'Professor of the Year' in 2010 by the Department of Epidemiology and Biostatistics. Education: PhD in Biostatistics (Case Western Reserve University, 2001), MS in Statistics (Case Western Reserve University, 1996), MS in Mathematics (Xiangtan University, 1988), and BS in Mathematics (Jiangxi Normal University, 1984). His research interests include survival analysis, tree-based methods, clinical trials, and statistical applications in medical research. He has co-authored numerous peer-reviewed articles, focusing on cancer disparities, radiomics, and computational pathology. Professional memberships include the American Statistical Association, American Mathematical Society, and American Cancer Society. Dr. Fu holds editorial roles at Reviews on Recent Clinical Trials , Journal of Clinical Oncology , and Journal of the National Cancer Center . His work has addressed mathematical challenges in stochastic processes and resolved statistical issues in study design and tree-based models. Notable contributions include developing risk prediction models for cancer outcomes and advancing interdisciplinary collaborations across oncology, biostatistics, and computer science. His lab focuses on integrating computational methods with clinical data to improve patient outcomes.
Catherine Mooney is a Professor in the School of Computer Science at University College Dublin (UCD), leading the Life Science Data Analytics Group (LiSDA). Her research focuses on applying machine learning to healthcare challenges, including biomarker development, clinical decision support systems, and addressing ethical and technical barriers in healthcare AI. Education: BSc in [field unspecified] from Trinity College Dublin PhD in Computer Science from UCD Prof Dip University Teaching & Learning from UCD Research Interests: Machine Learning applications in healthcare Biomarker discovery for neurological and metabolic conditions Explainable AI for clinical decision support Promoting diversity and inclusion in STEM education Her work bridges computational methods with medical challenges, emphasizing ethical AI and translational research. Notable Awards: Best Paper Award in Applied Biosciences (2023) UCD Long-Service Award (2022) Best Poster Award at ITiCSE ’20 (2020) Her research has led to impactful tools like LiSDA’s clinical decision support systems for epilepsy and pregnancy care. She also advocates for gender diversity in computing, serving in leadership roles like Vice Principal for EDI in UCD’s College of Science (2022–2024).
Massachusetts Institute of TechnologyUnited States
J. Christopher Love is the Raymond A. (1921) and Helen E. St. Laurent Professor of Chemical Engineering at MIT, with affiliations to the Koch Institute for Integrative Cancer Research, Broad Institute, and Ragon Institute. He earned a BS in Chemistry from the University of Virginia and a PhD in Physical Chemistry from Harvard University under George Whitesides, followed by postdoctoral work under Hidde Ploegh at Harvard Medical School. His research focuses on single-cell analysis, precision medicine, and biomanufacturing. The Love Lab develops technologies for drug discovery, vaccine development, and equitable biologic medicine production. Notable successes include pioneering single-cell analysis platforms, advancing metastatic cancer diagnostics via liquid biopsies, and engineering yeast-based vaccine manufacturing. Recent articles highlight innovations in liquid biopsy sensitivity, AI-driven ECG diagnostics, and CAR T-cell therapies. Awards include the Keck Young Scholar (2009), Dana Scholar (2009), and Camille Dreyfus Teacher-Scholar. He co-founded OneCyte, HoneyComb, and Sunflower Therapeutics, and advises multiple biotech companies. His lab emphasizes translational research, integrating chemical and biological engineering principles to address global healthcare challenges. Current work explores manufacturability-by-design for vaccines, tumor immunology, and mucosal vaccine delivery systems.
Michael Boutros is a Full Professor at Heidelberg University and Head of Division at the German Cancer Research Center (DKFZ). He currently serves as Dean of the Medical Faculty at Heidelberg University (since 2023) and Director of the Marsilius Kolleg (since 2020). He has held leadership roles including Coordinator of the Functional and Structural Genomics Program at DKFZ (2014–2023) and Acting Scientific Director (2015–2016). His academic base is within the Medical Faculty, focusing on molecular oncology and functional genomics. PhD, Witten/Herdecke University (1993–1996) Postdoctoral Research, Harvard Medical School (1999–2003) MPA, John F. Kennedy School of Government, Harvard University (1999–2001) Additional training: Cold Spring Harbor Laboratory, SUNY Stony Brook His research centers on Wnt signaling, functional genomics, and cancer pathways. He leads major research initiatives such as CRC 1324 on Wnt signaling and the ERC Synergy Grant DECODE. His work integrates high-throughput screening, CRISPR, and systems biology to dissect signaling networks in cancer and development. He has pioneered genome-wide RNAi and CRISPR screens to identify novel regulators of Wnt signaling across models. The 15 most recent articles reflect a strong focus on Wnt pathway regulation using functional genomics in both Drosophila and mammalian systems. Themes include high-throughput screening, CRISPR-based validation, cross-species conservation, and therapeutic targeting. Keywords span Cancer Biology, Systems Biology, and Signal Transduction, with subfields like RNAi, ubiquitination, stem cell regulation, and machine learning in image analysis. Michael Boutros has received numerous scientific honors: Elected member, Leopoldina National Academy of Sciences (2022) Elected member, Heidelberg Academy of Sciences (2022) EMBO Member (2013) ERC Advanced Grant (2012) Johann-Georg Zimmermann Research Award (2007) EMBO Young Investigator (2005) Member, 'Die Junge Akademie' (2003) He has been a recipient of the Emmy-Noether Program, McCloy Fellowship, Boehringer Ingelheim PhD Fellowship, Studienstiftung Fellowship, and Fulbright Fellowship. As a mentor and research leader, he has supervised numerous early-career scientists and coordinated large collaborative grants including the FP7 'CancerPathways' project. He currently serves as Speaker of the Research and Strategy Commission at Heidelberg University and Managing Director of the Health and Life Science Alliance Heidelberg Mannheim. He leads the CRC 1324 on Wnt signaling and is Coordinating PI of the ERC Synergy Grant DECODE. He is also Spokesperson of DFG Research Group 1036 and Coordinator of the former FP7 Coordinated Project 'CancerPathways'. His lab employs cutting-edge functional genomics tools to decode signaling networks in cancer and development.
Miler T. Lee is an Associate Professor at the University of Pittsburgh , focusing on gene regulation during early embryonic development through high-throughput experimental and computational genomics. He earned his Ph.D. in Genomics and Computational Biology in 2009 from the University of Pennsylvania under Dr. Junhyong Kim, followed by postdoctoral work with Dr. Antonio Giraldez at Yale University. Joining the university in 2016, his research spans maternal-to-zygotic transition (MZT), RNA stability, pluripotency networks, and evolutionary developmental biology, utilizing model organisms like zebrafish, Xenopus, and Hydractinia symbiolongicarpus. Key Research Themes: Maternally inherited RNA dynamics during embryogenesis Mechanisms of RNA degradation and transcriptome remodeling Evolution of pluripotency networks in hybrid species Role of zinc signaling in fertilization barriers Computational tools for RNA regulation and sensing Scientific Awards: Pan-American Society for Evolutionary Developmental Biology Junior Faculty Award (2024) Outstanding New Investigator – International Xenopus Board (2023) Basil O'Connor Scholar – March of Dimes (2017-2019) Recent publications highlight his work on enhancer classification, RNA degradation mechanisms, and cross-species MZT comparisons. His lab develops innovative methods like RESA for regulatory sequence analysis and studies evolutionary divergence in RNA localization patterns. While the articles span computational and experimental approaches, they consistently address RNA's role in cellular identity, developmental timing, and evolutionary adaptation. Applications include understanding pluripotency, designing RNA biosensors, and elucidating fertilization barriers. Prospective Ph.D. students are encouraged to contact him for opportunities in gene regulation, development, evo-devo, and computational genomics.
Alexander Nikitin is a Professor of Pathology at Cornell University's College of Veterinary Medicine, Department of Biomedical Sciences. His research focuses on molecular mechanisms linking tissue homeostasis to cancer development using autochthonous mouse models. Key Affiliation: Cornell University, Ithaca, NY Research Niche: Cancer-prone stem cell niches in female reproductive tract and prostate Research Interests Dr. Nikitin investigates how aberrations in p53/miR-34/MET and Rb networks drive malignant transformation of adult stem cells. His work includes: Identification of ovarian surface epithelium stem cell niche Technology-oriented cross-disciplinary collaborations Characterization of cancer initiation mechanisms in reproductive tissues Article Trends His publications span 2003–2025, emphasizing: Mouse models for epithelial cancers Role of tumor suppressor genes (p53, Rb) in cancer miR-34 family's tumor suppression functions Stem cell niche mapping in reproductive tract cancers Genetic drivers of high-grade serous carcinomas Translational research applications Lab Members Current lab personnel include: Andrea Flesken-Nikitin (Assistant Research Professor) Christopher Ashe (Research Support Specialist) Technicians and student researchers
Noelia Fernández Castillo is a Lecturer at the University of Barcelona's Faculty of Biology, affiliated with the Department of Genetics, Microbiology, and Statistics. She leads the Human Molecular Genetics research group and holds roles in academia spanning education and research. Education: Bachelor's/Master's in Genetics (University of Barcelona, 2004) Experimental Biology Master's (2006) Teaching Certification (2005) PhD in Biology (2011) Research focuses on genetic mechanisms underlying psychiatric disorders, addiction, and neurodevelopmental conditions. Key areas include epigenetic influences on ADHD, genetic contributions to aggression, and molecular pathways in substance use disorders. Uses animal models (zebrafish, mice) and human genomic data to explore these topics. Notable projects include studying nutrition's impact on impulsive behaviors (Eat2beNICE project, 2017-2022) and investigating shared genetic susceptibility between addictions and aggression. Current work emphasizes genetic pleiotropy in ADHD and psychiatric comorbidity. Has led/co-led grants from the European Union, Spanish Ministry of Health, and Ministry of Science. Active in collaborative research with institutions across Europe and North America.
Dr. Juan Pablo Lopez is an Assistant Professor at the Department of Neuroscience, Karolinska Institutet (Sweden) , leading research on stress-related psychiatric disorders. He earned undergraduate degrees in Psychology and Biology (Florida International University), a PhD in Psychiatry (McGill University), and postdoctoral training at the Max Planck Institute of Psychiatry in Munich. His work combines single-cell transcriptomics behavioral mouse models automated behavioral tracking viral-mediated gene manipulations to study stress susceptibility, resilience, and antidepressant mechanisms. Research interests include: Neurobiology of stress and trauma Molecular mechanisms in psychiatric disorders Developmental neuroendocrinology Sex differences in stress response Neural circuits of depression His recent work analyzes how stress exposure during development influences lifelong mental health and treatment outcomes. Scientific accolades include 2023 ECNP Rising Star Award ERC Starting Grant (2023) Swedish Research Council Starting Grant (VR, MH-12) StratNeuro Startup Funding He leads the Lopez Lab, which collaborates with international groups through the NeSTED network (Neuropharmacology and Stress/Trauma Exposure during Development).
Olga Kovalchuk is a Professor in the Department of Biological Sciences at the University of Lethbridge. She leads the Epigenetics of Health and Disease research laboratory, which is affiliated with the Southern Alberta Cancer Research Institute (SACRI) and Alberta Health Services/Alberta Cancer Foundation (AHS/ACF). Her research program has received significant funding including a $3.2 million Canada Foundation for Innovation (CFI) start-up grant and NSERC Discovery Grants. Dr. Kovalchuk's research focuses on the role of epigenetic mechanisms in health and disease, particularly in the context of radiation exposure and cancer. Her primary areas of investigation include epigenetic dysregulation in carcinogenesis, radiation epigenetics, DNA damage and repair mechanisms, and transgenerational effects of radiation exposure. She has made significant contributions to understanding how radiation-induced epigenetic changes affect genome stability, cancer development, and treatment responses. Analysis of her recent publications reveals a strong focus on microRNA regulation in cancer, sex-specific radiation responses, and the epigenetic basis of radiation-induced bystander effects. Her work demonstrates how epigenetic changes, particularly DNA methylation and microRNA expression patterns, mediate radiation responses in various tissues and can be transmitted across generations. Much of her research utilizes mouse models to investigate these mechanisms in vivo. Board of Governors Research Chair at University of Lethbridge CIHR Institute of Gender and Health Research Chair in New Perspectives in Gender, Sex and Health Canada Foundation for Innovation Start-up Funding ($3.2 Million) NSERC Discovery Grant recipient Editor's Choice Paper Award for research on radiation-induced bystander effects Cover Page feature for transgenerational radiation effects research Dr. Kovalchuk actively mentors numerous graduate students and postdoctoral fellows, with a research team comprising PhD students, MSc students, research assistants, and postdoctoral associates. Her laboratory collaborates extensively with researchers at MIT, Harvard University, and other institutions. She has secured significant grant funding including NSERC Discovery Grants and CFI start-up funds to support her research program investigating epigenetic mechanisms in radiation biology and cancer. Her laboratory, the Epigenetics of Health and Disease research group, maintains strong collaborations with the Southern Alberta Cancer Research Institute and has established partnerships with researchers across North America. Dr. Kovalchuk's work has important implications for understanding radiation risks, improving cancer therapies, and developing strategies to mitigate radiation damage.
Raymond T. Ng is a Professor of Computer Science at the University of British Columbia (UBC) and serves as Director of the Data Science Institute . In addition, he is the part-time Chief Informatics Officer at the PROOF Centre of Excellence for the Prevention of Organ Failures located at St Paul’s Hospital. Since 2016 he has held the prestigious Canada Research Chair in Data Science and Analytics. Education B.Sc. (Hons.) Computer Science, University of British Columbia, 1986 M.Math. Computer Science, University of Waterloo, 1988 Ph.D. Computer Science, University of Maryland, College Park, 1992 Research Interests Professor Ng’s research lies at the intersection of data mining , text mining , health informatics , sensor analytics , and databases . Over the past decade he has focused on two major domains: Genomics & Biomarker Discovery: Developing multi-omics biomarker panels for heart, lung and kidney transplant rejection and COPD exacerbations using transcriptomics, proteomics and metabolomics data. Natural Language Processing: Mining and summarizing conversational text such as emails, blogs and meeting transcripts to generate structured metadata and actionable insights. Scientific Awards Canada Research Chair in Data Science and Analytics (2016-2026) Best Paper Award, ACM SIGMOD 2004 Best Paper Award, ACM SIGKDD 2001 Selected among Best Papers of VLDB ’99 & ’98 Governor General’s Gold Medal, UBC (1986) Research Funding & Leadership Since joining UBC in 1992, Professor Ng has continuously secured major peer-reviewed funding from NSERC, CIHR, Genome Canada, CFI, MITACS and industry partners (Google, IBM, SAP). He leads or co-leads several large-scale initiatives: HEARTBiT multi-marker blood test for cardiac transplant rejection (CIHR 2018-2021) MERIDIAN ocean acoustic data infrastructure (CFI 2018-2021) Pan-Canadian Early Detection of Lung Cancer (Terry Fox 2018-2021) Business Intelligence Network (NSERC 2009-2014) Multiple Genome Canada programs on biomarker translation (2004-2018) Laboratories & Teams Professor Ng directs the Data Science Institute and works closely with the Natural Language Processing Research Group . At the PROOF Centre he heads a multidisciplinary team of statisticians, computer scientists and clinicians advancing computational biomarker pipelines from discovery to clinical implementation.
