Enzo Palombo is a Professor and Acting Executive Dean at Swinburne University's School of Science, Computing and Emerging Technologies. His academic career began with a PhD from La Trobe University on bacterial conjugation genetics, followed by postdoctoral research at the Royal Children's Hospital on gastroenteritis viruses. He holds a Fellowship of the Australian Society for Microbiology (FASM) and served on its Victorian Branch committee (1996–2014). He is also an Executive Committee member of the Australian Council of Environmental Deans and Directors (ACEDD). Research focuses include food microbiology, bioactive compounds from plants/fungi, environmental microbiology, nanotechnology, and virology. He leads projects on antimicrobial coatings, microplastic biodegradation, and biofilm control. Over 60 HDR students have been supervised, with topics ranging from wound care applications of endophyte metabolites to microbially influenced corrosion. Notable achievements include the 2020 FASM Fellowship and 2011 Distinguished Service Award. He has secured grants totaling millions澳元, including ARC funding for biofilm research and industry collaborations on antimicrobial technologies. Key publications (2021–2025) address smart microalgae incubators, nanoparticle drug delivery, and computational discovery of biofilm inhibitors. Public engagement includes media commentary on bird flu outbreaks (2024) and food safety. His leadership extends to university administration while maintaining active roles in interdisciplinary research teams addressing global challenges like antimicrobial resistance and sustainable agriculture.
Dr. Chunming Qiao is a SUNY Distinguished Professor and Chair of the Department of Computer Science and Engineering at the University at Buffalo (SUNY) , leading the Lab for Advanced Network Design, Evaluation and Research (LANDR) since 1993. His work spans cyber-physical systems , optical networks , and Internet of Things (IoT) , with a focus on safety, reliability, and protocol design. Education: PhD in Computer Science from the University of Pittsburgh (1993) BS in Computer Science and Engineering from the University of Science and Technology of China (1985) Dr. Qiao’s research interests combine theoretical and applied network design, including autonomous vehicles , quantum computing , and cloud services . He pioneered optical burst switching (OBS) and iCAR systems for wireless convergence, cited in BusinessWeek and Wireless Europe . His recent publications emphasize quantum networking , federated learning , and autonomous driving security , with projects on entanglement routing , edge inference optimization , and LiDAR adversarial attacks . Articles span IEEE and ACM venues , and include best paper awards . Scientific Awards: TC-CSR Distinguished Technical Achievement Award (2015) SUNY Chancellor's Award for Excellence (2013) IEEE Fellow (2009) UB Exceptional Scholar-Sustained Achievement Award (2005) Dr. Qiao has secured over two dozen NSF grants and collaborations with Google , Cisco , and NEC Labs . His 7 US patents and consulting experience highlight his industry impact, while his editorial roles and conference leadership underscore academic influence. He actively contributes to multi-disciplinary research through the New York State Center of Excellence in Bioinformatics and Life Sciences and CEDAR , advancing high-performance computing and document analysis .
Dr. Devindri Perera is a Senior Lecturer at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences (EECMS) within the Faculty of Science and Engineering. He is also affiliated with the Office of the Provost, demonstrating administrative and academic leadership roles. His research focuses on interdisciplinary areas including biosecurity systems, veterinary epidemiology, statistical modeling, and genomics. Dr. Perera's work spans environmental science (biosecurity border management), veterinary medicine (equine health and endocrinology), and computational methods (data clustering, statistical algorithms). His biosecurity research emphasizes risk assessment and spatial-temporal analysis of non-indigenous species, while his veterinary studies investigate equine physiology and disease mechanisms. In genomics, he contributes to identifying genetic markers for neurological disorders like multiple sclerosis. His publications from 2006–2023 reflect a strong focus on statistical methodologies in interdisciplinary contexts, including genome-wide association studies, algorithm validation for genotyping, and applied econometric models. This demonstrates a blend of theoretical rigor and practical problem-solving across diverse domains. Though no specific awards or grants are listed in this profile, his prolific publication record and cross-disciplinary approach highlight sustained academic engagement. His research collaborations span institutions globally, addressing both environmental and biomedical challenges.
Dr. Gary Hon is an Assistant Professor at UT Southwestern Medical Center affiliated with the Cecil H. and Ida Green Center for Reproductive Biology Sciences and the Lyda Hill Department of Bioinformatics. He leads a research program focused on decoding the complexity of the human genome through two primary directions: understanding the molecular basis of cell state for regenerative medicine applications, and elucidating how non-coding variants contribute to development and disease. His lab employs integrative techniques at the interface of gene regulation, epigenetics, genome engineering, single-cell genomics, and bioinformatics. His research interests span genomics, epigenetics, bioinformatics, gene regulation, stem cell biology, and disease mechanisms. Dr. Hon earned his graduate degree from UC San Diego's Bioinformatics and Systems Biology Program and completed post-doctoral training in Dr. Bing Ren's lab before joining UT Southwestern in 2015. Dr. Hon has received significant recognition including the CPRIT Scholar award and NIH Director’s New Innovator Award. His recent publications demonstrate a focus on advanced genomic techniques including Perturb-Seq optimization, single-cell transcriptomics in cancer and reproductive biology, enhancer network mapping, and stem cell modeling of human development.
Mikko Hiltunen is a Professor of Tissue and Cell Biology at the Institute of Biomedicine, School of Medicine, University of Eastern Finland. His research focuses on molecular mechanisms of neurodegenerative disorders, particularly Alzheimer's disease and idiopathic normal pressure hydrocephalus (iNPH). He leads several research groups including the Molecular Genetics of Alzheimer's Disease (Hiltunen Lab) and participates in the Brain Research Unit and Genome Center of Eastern Finland. Research interests span Alzheimer's pathogenesis, neuroinflammation, genetic risk factors, biomarker discovery, and therapeutic development. His work integrates molecular biology, genetics, and clinical neuroscience to investigate microglial function, amyloid pathology, and cerebrospinal fluid biomarkers. Key areas include APOE genetics, PLCγ2-mediated neuroprotection, and machine learning applications in neurodegeneration. His recent publications demonstrate a strong focus on cerebrospinal fluid biomarkers, genetic association studies, neuroinflammation mechanisms, and therapeutic interventions. Article themes consistently emphasize microglial biology, genetic risk modifiers, and translational approaches for Alzheimer's and iNPH. Collaborative projects include Neuro-Innovation (2021-2026) and NOVEL MSCA Postdoctoral Programme (2024-2029). Hiltunen leads the Clinical Alzheimer Research group and co-directs the UEF Brain Research Unit. His team utilizes advanced models including iPSC-derived microglia and pericyte systems to study neurovascular interactions. Current work explores phospho-tau immunotherapy, lysosomal dysfunction, and polygenic risk score applications across diverse populations.
Mark T. W. Ebbert, PhD, is an Associate Professor at the University of Kentucky's Sanders-Brown Center on Aging, where he leads the Ebbert Lab. His work focuses on developing biomarkers for neurodegenerative diseases, particularly Alzheimer's disease (AD), leveraging cutting-edge genomic and transcriptomic techniques. He co-leads efforts in the Alzheimer's Disease Research Center's Biomarker Core, aiming to integrate neuroimaging, fluid biomarkers, and genomic data for precision medicine applications. Key research interests include analyzing genetic variants, long-read sequencing for disease resilience, and understanding inflammation's role in neurodegeneration. He has presented at high-profile venues like the Markesbery Symposium, discussing topics such as using long-read sequencing to identify AD biomarkers. His lab has produced over 55 publications, with a focus on resolving genomic 'dark regions' and improving biomarker accuracy through innovative methods like RNApysoforms visualization tools. Collaborating with interdisciplinary teams, Dr. Ebbert explores the interplay between genetics, epigenetics, and environmental factors in neurodegenerative diseases. His work bridges basic science and clinical translation, emphasizing the importance of genomic data integration for advancing AD diagnosis and treatment strategies.
Robert J. Doerksen is Professor of Medicinal Chemistry in the Department of BioMolecular Sciences at the University of Mississippi School of Pharmacy , Associate Dean of the Graduate School , and Research Professor in the Research Institute of Pharmaceutical Sciences . Since 2004 he has combined computational chemistry with experimental collaborations to advance drug discovery, particularly in glycoscience and cannabinoid research. Education: B.S. (Double First Class Honours) in Mathematics & Physics, University of New Brunswick, 1986 Graduate Diploma in Christian Studies, Regent College, Vancouver, 1996 Ph.D. in Chemistry, University of New Brunswick, 1998 (Advisor: Prof. Ajit Thakkar) Postdoctoral Fellow, UC Berkeley (with Prof. Martin Head-Gordon) Postdoctoral Fellow, University of Pennsylvania (with Prof. Michael Klein) Research Interests: Dr. Doerksen’s laboratory develops and applies computational medicinal chemistry approaches spanning chemoinformatics , molecular dynamics , virtual screening , and machine learning to understand how small molecules interact with proteins. Central themes include: Glycoscience : lectin–glycan interactions, glycosyltransferase regulation, glycomimetic design. Cannabinoids : CB1/CB2 receptor allosteric modulation, cannabidiol pharmacology, synthetic cannabinoid SAR. Neglected & Infectious Diseases : malaria, hepatitis B, tuberculosis, SARS-CoV-2, urinary-tract infections. Drug Delivery & Formulation : nanoparticle coatings, pharmacokinetic optimization, bioavailability enhancement. Publications Trend: Over 2023–2025 his 15 most recent papers reveal intense activity at the intersection of AI-driven discovery , glycobiology , and cannabinoid pharmacology , with emphasis on anti-infective, anticancer, and CNS-active agents. Key contributions include first-in-class MraY inhibitors for TB, cannabinoid-inspired antivirals against SARS-CoV-2, and glycomimetic antagonists of bacterial adhesins for UTI prevention. Scientific Awards & Honors: UM School of Pharmacy Faculty Service Award (2015–2016) UM School of Pharmacy Faculty Service Award (2010–2011) Editorial Boards: Molecules , AIMS Biophysics , Pharmaceutical Sciences , Perspectives in Medicinal Chemistry Repeated NIH, DoD, NSF, Wellcome Trust, and international grant-review panels (2010–present) Guest Editor for multiple special issues in Molecules and Frontiers journals Advising & Mentoring: As Associate Dean, Dr. Doerksen oversees University-wide graduate programs, chairs the Graduate Recruiting Fellowship and Scholarship Committee, and mentors students across disciplines. Faculty advisor for the UM chapters of the Christian Pharmacists Fellowship International (since 2005) and Taiwanese Student Association (2022–2025). He actively participates in PhD and MS thesis committees worldwide and has delivered NSF GRFP information sessions to support trainee funding. Laboratories & Teams: He directs research within the Computational Chemistry and Bioinformatics Research CORE (CCBRC) , fostering collaborative projects involving medicinal chemists, structural biologists, pharmacologists, and data scientists. The group leverages high-performance computing resources at the University of Mississippi to perform large-scale virtual screening, AI/ML model development, and integrative structural biology studies.
Joseph Ibrahim is an Alumni Distinguished Professor in the Department of Biostatistics at the Gillings School of Global Public Health, University of North Carolina at Chapel Hill, where he has served since 2002. He currently holds dual leadership roles as Director of Graduate Studies for the Department of Biostatistics and Director of the Biostatistics for Research in Genomics and Training Grant. His methodological innovations in Bayesian survival analysis and missing data methodologies have significantly advanced public health research, particularly in cancer genomics applications. Professor Ibrahim's research program centers on developing statistical frameworks for complex clinical and genomic data. His seminal contributions include Bayesian cure rate models, prior elicitation techniques, and diagnostic tools for high-dimensional survival analysis. Current work focuses on integrating multi-omics data with longitudinal tumor burden metrics and refining adaptive clinical trial designs for biomarker-driven populations. These methodologies directly address critical challenges in precision oncology and pharmacovigilance, enabling more robust inference from real-world evidence. His 2025 publications reveal three dominant trends: (1) Advancements in cure rate modeling for joint longitudinal-survival data with change points, (2) Computational innovations for high-dimensional penalized models using autoencoders and R packages like hdbayes, and (3) Methodological refinements for Bayesian trial design incorporating historical controls. These works consistently bridge theoretical statistics with cancer research applications, particularly in tumor phylogeny inference and signal detection for adverse events. Scientific awards include: Samuel S. Wilks Memorial Award (2024) from the American Statistical Association for distinguished contributions to biostatistics Professor Ibrahim has mentored 48 pre-doctoral students and 8 postdoctoral fellows, with exceptional thesis publication records in top statistical journals. As principal investigator of the T32 Cancer Genomics Training Grant since 2004, he has secured funding for 35 doctoral students. His curriculum leadership includes modernizing eight graduate courses and establishing new data science computing sequences since 2015. Current advising focuses on Bayesian methodology development for cancer genomics applications. He directs the department's Biostatistics for Research in Genomics initiative and leads the T32 Cancer Genomics Training Grant team, which integrates statistical methodology development with translational cancer research across UNC's Lineberger Comprehensive Cancer Center and clinical partners.
Max Staller is an Assistant Professor in the Department of Molecular and Cell Biology at the University of California, Berkeley, affiliated with the College of Letters & Science and the Center for Computational Biology. His lab focuses on understanding how transcriptional activation domains regulate gene expression through interdisciplinary approaches combining experimental, computational, and theoretical methods. Research Interests: Transcriptional regulation mechanisms in development and stress responses Functional analysis of intrinsically disordered protein domains Machine learning applications in protein sequence-function prediction Evolutionary dynamics of transcription factors Grants & Collaborations: Lead investigator on the NSF-funded PlantSynBio project (2021) for identifying transcriptional activation domains across plant species. Collaborates with the Cohen Lab (Washington University) on mutational scanning studies. Labs & Affiliations: Director of the Staller Lab, which integrates high-throughput experiments with computational modeling. Active in the Berkeley Bioscience community and the Center for Computational Biology.
Christopher M. Sassetti is a Professor in the Department of Microbiology at the University of Massachusetts Chan Medical School (UMass Chan Medical School) and T.H. Chan School of Medicine. His research focuses on the pathogenesis of Mycobacterium tuberculosis, specifically understanding how the bacterium adapts to host environments, acquires nutrients, regulates its cell wall physiology, and survives antibiotic treatment. He completed his BS in Biology at Santa Clara University and his PhD in Immunology at the University of California, San Francisco. Dr. Sassetti leads the Sassetti Lab, which employs genetic, biochemical, and systems biology approaches to study tuberculosis. His work has identified critical metabolic pathways and survival mechanisms in M. tuberculosis, including cholesterol utilization and cell wall synthesis regulation. He holds additional academic roles in the Morningside Graduate School of Biomedical Sciences, including the Immunology and Microbiology Program, MD/PhD Program, and Postbaccalaureate Research Education Program. Recent research highlights include studies on host immune responses to tuberculosis, antibiotic efficacy under infection conditions, and the role of genetic interactions in pathogen survival. His lab has discovered that host fatty acid metabolism and autophagy pathways play key roles in restricting bacterial growth. Dr. Sassetti has been recognized as a Damon Runyon Foundation Scholar and has contributed to high-impact publications in Immunity , Science , and Cell . Current projects include understanding nutrient acquisition in vivo, phosphosignaling regulation of cell wall synthesis, and metabolic mechanisms driving antibiotic tolerance. Collaborative efforts with institutions like the Morningside Graduate School and global networks drive translational research toward novel tuberculosis therapies and vaccines.
Gemma Atkinson is an Associate Professor at Lund University's Faculty of Medicine, leading the Atkinson Lab. She specializes in protein evolution and bioinformatics, focusing on antibiotic resistance, bacteriophages, and toxin-antitoxin systems. She manages LU-Fold, an infrastructure for high-throughput protein structure prediction using AlphaFold. Her research integrates computational tools with experimental methods to uncover microbial defense mechanisms. Key projects include developing bioinformatics tools (e.g., LoVis4u, webFlaGs) and investigating phage defense systems. She leads grants from the Swedish Research Council and the Knut and Alice Wallenberg Foundation. Her lab collaborates internationally, contributing to UN Sustainable Development Goals on health and innovation. Publications highlight advancements in toxin-antitoxin systems, antimicrobial peptides, and ribosome function. The lab's tools are widely used globally, aiding researchers in structural and functional genomics analysis.
Kangjoo Lee is an Associate Research Scientist in Psychiatry at Yale School of Medicine, specializing in neuroimaging and computational neuroscience. Their research focuses on understanding brain dynamics, particularly in mental health conditions like schizophrenia and mood disorders, using advanced neuroimaging techniques and AI-driven analysis. Education: PhD in Neuroscience from McGill University (2019), Postdoctoral Research Associate at Yale University (2023). Research interests include brain connectivity, sleep deprivation effects, and developing AI tools for neuroscience. Lee has contributed to studies on ketamine's neural mechanisms, sleep recovery networks, and large language models' predictive capabilities in neuroscience. Notable achievements include the Merit Abstract Award (2021) and leadership roles in the Organization for Human Brain Mapping's Diversity Committee. Their work bridges clinical neuroscience with computational methods, emphasizing reproducibility and inclusivity in scientific practices. Current roles include Guest Editor for Biological Psychiatry and committee memberships in neuroimaging and diversity initiatives. Lee collaborates across disciplines, advancing translational research in mental health biomarkers and neurotechnology.
JACKIE E. SHAY is an Assistant Teaching Professor in the Ecology, Evolution, and Marine Biology Department at the University of California, Santa Barbara. Her work bridges pedagogical innovation with ecological research, emphasizing joy-centered learning and collaborative approaches to STEM education. She previously served as Associate Director for the Center for Engaged Teaching and Learning at UC Merced, focusing on inclusive STEM course design. Shay holds a master's degree in Ecology, Evolution, and Conservation Biology from San Francisco State University, where she studied fungal evolution in Madagascar, and a Ph.D. in Quantitative and Systems Biology from UC Merced, exploring monkeyflower microbiomes under advisors Sexton and Frank. Her research spans microbial ecology, plant-microbe symbiosis, and climate resilience in biological systems. Her teaching portfolio includes courses on introductory biology, fungal biology, and pedagogy, with a focus on fostering student agency through course-based research experiences. Shay's interdisciplinary approach integrates qualitative and quantitative methods to study how collaborative learning environments enhance educational outcomes. Her lab and outreach efforts include the blog ShayShrooms , documenting fieldwork in Madagascar, and ongoing investigations into microbial community dynamics in response to environmental stressors. Current projects explore symbiotic relationships between plants and microbes, with implications for conservation biology and climate adaptation strategies.
Ivana Malenica is an Assistant Professor of Biostatistics at the University of North Carolina at Chapel Hill's Gillings School of Global Public Health. Previously, she was a HDSI Fellow at Harvard Data Science Initiative and Postdoctoral Fellow in Statistics at Harvard University. She holds a Ph.D. in Biostatistics from UC Berkeley and a B.S. in Mathematics from Arizona State University. Her research focuses on causal inference, machine learning, nonparametric statistics, efficiency theory, and precision health. She specializes in longitudinal and structured dependent settings including adaptive sequential experiments, online learning, and reinforcement learning applications in personalized health. Her recent publications demonstrate strong methodological contributions to causal inference and machine learning, with applications spanning clinical trials, public health, genomics, and reinforcement learning. Her work consistently develops novel statistical approaches for complex data structures. Awards include: Harvard Data Science Initiative Fellowship (2022) Berkeley Wellness Letter Fellowship (2020) Wellness Scholarship in Honor of Chin Long Chiang (2019) Berkeley Institute for Data Science Moore-Sloan Fellowship (2018) She teaches graduate courses including Advanced Probability and Statistical Inference I (BIOS 760). Her computational work includes contributions to the tlverse ecosystem for causal inference in R.
Professor Sarah Ennis is a leading figure in genomics and biomedical data science at the University of Southampton , affiliated with the School of Human Development and Health . As Professor of Genomics , she directs the Genomic Informatics Group and spearheads the Human Genetics & Genomic Medicine theme. Research interests focus on Inflammatory Bowel Disease (IBD) , Big Data Genomics , and AI-driven diagnostics . Her work includes Nature Communications publications on machine learning in retinal imaging, bioinformatics tools for ophthalmic analysis, and genomic studies on cardiomyopathies and neurodevelopmental disorders. External roles encompass Research Director at the Central & South Genomic Medicine Service Alliance , Genomics Lead for Wessex Health Partners , and leadership in national initiatives like the AGENDA project funded by EPSRC. Her educational contributions include founding the MSc in Genomic Medicine and creating the Primer in Genomic Medicine CPD course , now part of NHS Genomics Education. Her research integrates genomic, transcriptomic, and clinical data to advance personalized medicine.
