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Dr. Satrya Fajri Pratama is a Senior Lecturer in Computer Science at the University of Hertfordshire , affiliated with the School of Physics, Engineering & Computer Science and the Department of Computer Science . With professional certifications from Oracle, Microsoft, Google, AWS, Cisco, and other industry leaders, he combines academic expertise with practical industry recognition. His research focuses on software development, internet of things (IoT), cloud computing, and computational approaches to drug classification. Doctor of Philosophy (ICT) – Universiti Teknikal Malaysia Melaka Master of Science in ICT – Universiti Teknikal Malaysia Melaka Bachelor of Computer Science (Software Development) – Universiti Teknikal Malaysia Melaka His research involves descriptor selection for drug classification using advanced algorithms like the Whale Optimization Algorithm and Particle Swarm Optimization , particularly in combating Amphetamine-Type Stimulants (ATS) . Collaborative work includes ncRNA identification and QSAR modeling for biodegradation studies. Key scientific awards include certification as a Professional Technologist with the Malaysia Board of Technologists (MBOT) and recognition as an Apple Teacher with Swift Playgrounds Recognition . He holds numerous industry certifications and is a certified educator/trainer for Microsoft, Google, AWS, Oracle, and other major tech companies.

• Software Development
• Internet of Things
• Cloud Computing
• +6 more

Harry Hochheiser is an Associate Professor at the University of Pittsburgh School of Medicine, affiliated with the Department of Biomedical Informatics and the Intelligent Systems Program. He serves as Director of the Biomedical Informatics Training Program and is a Pitt Cyber Affiliate Scholar, focusing on interdisciplinary research at the intersection of computer science and healthcare. Education: MS and BS in Electrical Engineering and Computer Science from MIT (1991) His research spans human-computer interaction, information visualization, bioinformatics, universal usability, security, privacy, and public policy implications of computing systems. He emphasizes user-centered design for biomedical data exploration, including electronic health records and clinical informatics. His recent work includes NSF-funded projects on computer security education and computational thinking, alongside teaching courses in algorithms, human-computer interaction, and information visualization. Analysis of his publications reveals a focus on biomedical informatics, machine learning in healthcare, clinical data modeling, and natural language processing applications. Collaborative efforts include projects on gene networks, drug interactions, and clinical decision support systems. His current projects aim to develop interactive systems for biomedical data exploration, with applications in cancer informatics, pharmacogenomics, and clinical workflow optimization. He actively contributes to evaluation frameworks for visual analytics in healthcare and participates in policy discussions through roles like the Association of Computing Machinery's US Public Policy Committee.

• Biomedical Informatics
• Bioinformatics
• Clinical Informatics
• +7 more

Håvard Kauserud is a Professor at the Department of Genetics and Evolutionary Biology, University of Oslo. His research spans molecular ecology, evolutionary biology, and fungal genetics with a focus on mycorrhizal and endophytic fungi, climate change impacts, and habitat fragmentation effects. Section of Genetics and Evolutionary Biology Teaches advanced courses in fungal evolution and bioinformatics Research projects include: Molecular ecology of mycorrhizal fungi Speciation mechanisms in forest fungi Climate change effects on mushroom phenology Comparative genomics of Serpulaceae Endophytic fungi in boreal mosses Recent work explores fungal community dynamics across boreal forests, indoor mycobiomes, and genome expansion patterns in Mycena . Collaborative studies investigate arthropod dispersal of fungal spores, climate adaptation signatures, and trait-based fungal ecology databases.

• Molecular ecology
• Evolutionary biology
• Fungal genetics
• +5 more

Ron C Anafi serves as Associate Professor of Medicine (Sleep Medicine) at the Hospital of the University of Pennsylvania and holds key affiliations as Faculty Scholar at the Penn Institute for Bioinformatics, Co-Investigator at the Center for Subcellular Genomics, and member of both the Chronobiology and Sleep Institute and ITMAT. His work bridges computational biology with clinical sleep medicine within the Perelman School of Medicine. His educational trajectory includes a B.S.E. in Biomedical Engineering and Philosophy from Tulane University (1995), followed by a Ph.D. in Applied Mechanics (2002) and M.D. (2004) from the University of Minnesota. This dual training underpins his unique approach to circadian research. Dr. Anafi's laboratory pioneers computational methods to decode sleep and circadian influences on human physiology, focusing on neurodegeneration and cancer. By applying machine learning and systems biology to large-scale omics data, his team reconstructs molecular rhythms from cross-sectional human tissue databases—overcoming the critical barrier of limited longitudinal sampling in patients. His research demonstrates how circadian disruptions in ribosomal function link to Alzheimer's pathology and how tumor clock strength predicts breast cancer outcomes. Analysis of his 15 most recent publications (2022-2025) reveals intensifying focus on cell-type-specific circadian disruptions in neurodegenerative diseases, with significant expansion into cancer chronobiology and contactless sleep monitoring technologies. His methodological innovations like CYCLOPS enable rhythmic signal extraction across diverse tissues—from brain to skin—while increasingly integrating multi-omics layers to identify therapeutic targets. As mentor in the Genomics and Computational Biology and Neuroscience graduate groups, he guides students through rotation projects at his Translational Research Laboratories facility (Suite 2100, 125 South 31st Street). His research is supported by NIH grants investigating circadian mechanisms in Alzheimer's disease and cancer progression, with recent work exploring sex-specific metabolic impacts of circadian genes and non-invasive sleep monitoring.

• Sleep
• Circadian rhythms
• Bioinformatics
• +4 more

Lukas Edward Dow is a Professor of Biochemistry and Biophysics at Weill Cornell Medical College (2025-present) and holds a secondary appointment in Medicine. His research spans genetic and non-genetic resistance mechanisms in KRAS-driven cancers, WNT signaling, and CRISPR-based cancer modeling. Ph.D. and B.Sc. from University of Melbourne Focus on CRC, pancreatic, breast, and prostate cancers Research interests include genetic resistance mechanisms , CRISPR applications , WNT pathway dependencies , and tumor microenvironment dynamics . Key publications reveal trends in mutant-specific therapies , epithelial plasticity , and precision genome editing . Current research projects funded by National Cancer Institute and Department of Defense investigate KRAS allelic imbalance, R-Spondin sensitization, and WNT pathway alterations. External collaborations include scientific advisory roles at Mirimus, Inc. and consulting at Revolution Medicines, Inc. His lab develops genetically engineered mouse models and organoid systems for studying cancer progression, with emphasis on metastasis , drug resistance , and epigenetic adaptations . The work has significant implications for improving cancer therapies through context-dependent targeting .

• Cancer Biology
• Genetics
• Molecular Biology
• +5 more

Dana Carroll is a Distinguished Professor in the Department of Biochemistry at the University of Utah's Spencer Fox Eccles School of Medicine, renowned as the "father of the gene-editing revolution" for pioneering zinc-finger nucleases that enabled CRISPR technology. With a 48-year career at the institution, he has shaped genome editing across medicine, agriculture, and basic science. Education: Bachelor's degree from Swarthmore College, Pennsylvania PhD from the University of California, Berkeley Postdoctoral research at Beatson Institute for Cancer Research, Glasgow Postdoctoral research at Carnegie Institution Department of Embryology, Baltimore Research Focus: Carroll's work centers on targetable nucleases (zinc-finger, TALENs, CRISPR/Cas) for precise genome editing in over 200 organisms. His lab optimizes these tools for clinical trials targeting genetic diseases and agricultural improvements in crop nutrition and animal welfare, while actively addressing ethical implications through public discourse and international policy development. Scientific Recognition: National Academy of Sciences membership American Academy of Arts and Sciences Fellowship Novitski Prize (2012) and Sober Lectureship Award (2014) University of Utah Distinguished Innovation Award (2017) Utah Governor’s Medal (2018) and Rosenblatt Prize (2023) Mentorship & Leadership: Carroll supervised 31 graduate/postdoctoral students and served on 125 thesis committees. As Biochemistry Department co-chair (1980s) and sole chair (1998-2009), he recruited Nobel laureates and revitalized the department. His committee service spans 26 university-wide, 50 School of Medicine, and 20 NIH panels, alongside innovating graduate courses on recombinant DNA technology and gene therapy ethics. Current Initiatives: As a Huntsman Cancer Institute member in the Nuclear Control Program, Carroll advances clinical genome editing applications while co-authoring the 2020 international report on heritable human genome editing for the U.S. National Academies and UK Royal Society.

• Genome Editing
• Gene Therapy
• Zinc-Finger Nucleases
• +5 more

Kadeem Jamal Gilbert is an Assistant Professor at Michigan State University (MSU) affiliated with multiple programs and institutes: Plant Biology, Kellogg Biological Station, Molecular Plant Sciences Program, Plant Resilience Institute, and Ecology, Evolution & Behavior Program. His research focuses on plant-animal/microbe interactions, symbiosis, physiological regulation of leaf microenvironments, and carnivorous plants. Education: Ph.D. from Harvard University Dr. Gilbert's work integrates ecological and physiological approaches to study plant interactions with insects, microbes, and environmental gradients. His lab employs transcriptomics, chemical ecology, and community ecology frameworks to investigate carnivorous plant adaptations, phylloplane regulation, and global change impacts on species interactions. Recent publications highlight his research trajectory across plant physiology, microbial ecology, and evolutionary biology. These include studies on anthocyanin-mediated plant-insect interactions, fluid regulation in Nepenthes pitcher plants, and landscape-scale transcriptomic responses to environmental stressors. His work reveals fundamental insights about ecological filters in plant microhabitats and evolutionary tradeoffs in carnivorous species. Current research themes include plant volatile signaling in herbivore specialization, pH-mediated microbial community assembly, and ecological transcriptomics across environmental gradients. The Gilbert Lab maintains active outreach and press engagement while maintaining field sites at the Kellogg Biological Station.

• Plant-animal interactions
• Plant-microbe symbiosis
• Physiological ecology of plants
• +3 more

Hosna Jabbari serves as Associate Professor in Biomedical Engineering and cross-appointed in Electrical and Computer Engineering at the University of Alberta's Faculty of Engineering, directing the Computational Biology Research and Analytics Laboratory (COBRA Lab) focused on RNA-centric diagnostics and therapeutics development. Education: BSc in Computer Science, University of Victoria MSc in Computer Science - Bioinformatics, University of British Columbia PhD in Computer Science - Bioinformatics, University of British Columbia Research Focus: Dr. Jabbari pioneers RNA structure-function characterization through computational biology to decode disease mechanisms. Her work integrates transcriptomics , RNA-RNA/protein interaction analysis , and aging research with advanced machine learning and quantum computing approaches, emphasizing explainable AI for medical applications in RNA therapy development. Publication Trends: Recent work (2018-2024) demonstrates sustained innovation in RNA pseudoknot prediction algorithms applied to viral pathogenesis (notably SARS-CoV-2) and therapeutic design, with increasing integration of quantum computing and AI methodologies reflecting her interdisciplinary trajectory in computational genomics. Advising & Grants: Actively recruiting undergraduate researchers for funded projects including non-DNA life research, AI-driven vaccine development (comparative analysis and self-amplifying RNA platforms), and aging studies. She instructs BME 415/615 (Bioinformatics Algorithms) and MED 621 (Grant Writing), providing hands-on research training and grant preparation mentorship. Laboratory: As COBRA Lab Director, she leads a globally connected research network advancing RNA bioinformatics through algorithm development, fostering collaborations across virology, aging research, and therapeutic design domains.

• Computational Biology
• Bioinformatics
• RNA Bioinformatics
• +4 more

Dr. Gajender Aleti serves as an Assistant Professor in the Department of Agricultural and Environmental Sciences within the College of Agriculture at Tennessee State University (TSU), having joined the institution in August 2022. His academic appointment bridges agricultural sciences, environmental health, and biomedical research through interdisciplinary microbiome studies. His educational credentials include a PhD in Microbial Ecology from the Austrian Institute of Technology & The University of Natural Resources and Life Sciences, Vienna; an MSc in Bioinformatics from the University of Abertay Dundee; an MSc in Biotechnology from Osmania University, India; and a BSc in Botany, Zoology, and Chemistry from Osmania University. Dr. Aleti's research program investigates critical interactions between diet, the gut microbiome, and host health, with three core pillars: Understanding diet-microbiome-gut health interactions Characterizing bioactive small molecules produced by gut microbiota Elucidating gut microbiome-nervous system communication (Gut-Brain Axis) Analysis of his 15 recent publications (2016-2022) reveals a strong translational focus spanning human health contexts (salivary/gut microbiomes in depression, obesity, OCD, and oral cancer) and agricultural applications (rhizosphere microbiomes, bioremediation). His work predominantly employs mass spectrometry-based metabolomics and genomic data mining within large collaborative frameworks, demonstrating methodological innovation in multi-omics integration. While no specific scientific awards are documented in the provided materials, his publication record in journals like Nature Communications , Nature Methods , and BMC Microbiology reflects significant scholarly impact. His research is supported by active grants enabling investigations into microbiome-host dynamics across diverse physiological systems. Dr. Aleti actively mentors graduate researchers within TSU's Department of Agricultural and Environmental Sciences, contributing to the university's research infrastructure through laboratory-based investigations of microbial community dynamics and molecular mechanisms in health and disease contexts.

• Microbiome
• Gut Health
• Gut-Brain Axis
• +4 more

Georgi Ganev is a PhD Researcher at University College London (UCL) and Principal Research Scientist at SAS, following the acquisition of Hazy, a synthetic data company. He is part of UCL's Information Security Research Group under Professors Emiliano De Cristofaro and David Barber. His research focuses on advancing privacy-preserving synthetic data techniques, particularly in machine learning and differential privacy. Key areas include developing DP generative models, auditing privacy mechanisms, and addressing legal implications of synthetic data. Education: MSc in Computational Statistics and Machine Learning (UCL, supervised by Prof. Sebastian Riedel) and BSc in Business Mathematics and Statistics (LSE, supervised by Prof. Wicher Bergsma). Research Interests: Privacy-preserving synthetic data, differential privacy, privacy auditing, generative models, and regulatory compliance. His work has led to 25+ discovered privacy bugs in open-source libraries and vulnerabilities in deployed systems, with publications in top-tier conferences like IEEE S&P, USENIX Security, and ICML. Notable Achievements: Distinguished Paper Award at IEEE S&P 2025. His research has been integrated into SAS's synthetic data products, impacting industry adoption. Open-source contributions include dpmm and dpart libraries for DP synthetic data generation. Publications: Over 15 peer-reviewed articles, including works on privacy metrics inadequacy, PATE-GAN benchmarking, and synthetic data regulatory challenges. Active in workshops on generative AI and law, and deployment challenges in enterprise settings.

• Machine Learning
• Privacy-Preserving Technologies
• Data Synthesis
• +3 more

Fan Lam is an Associate Professor in the Department of Bioengineering at the University of Illinois Urbana-Champaign (UIUC), affiliated with the Grainger College of Engineering. He also directs the MS in Biomedical Image Computing (MS-BIC) program. His primary research focuses on developing advanced imaging techniques such as biomedical imaging, MRI, molecular imaging, and image reconstruction to study brain function and diseases. Lam holds a Ph.D. in Electrical and Computer Engineering from UIUC (2015), an M.S. in the same field from UIUC (2011), and a B.S. in Biomedical Engineering from Tsinghua University (2008). He is affiliated with multiple institutes, including the Carle-Illinois College of Medicine, the Carl R. Woese Institute for Genomic Biology, and the Beckman Institute for Advanced Science and Technology. Lam serves as a journal editor for Frontiers in Physics , Medical Physics , and IEEE Transactions on Medical Imaging . His work bridges engineering and neuroscience, with grants from NIH and other agencies supporting Alzheimer’s research and imaging innovations. Research highlights include epigenetic MRI, high-resolution volumetric MRI, and integrating AI with imaging methods. Lam’s team collaborates across disciplines to address challenges in medical imaging and brain mapping. His lab, the Quantitative Multiscale Imaging Group, develops tools for molecular and biochemical analysis of the brain.

• Biomedical Imaging
• MRI
• Molecular Imaging
• +5 more

Dr. Tuan Van Nguyen is a Distinguished Professor of Predictive Medicine at the School of Biomedical Engineering, University of Technology Sydney (UTS), and holds an Adjunct Professorship in Epidemiology at UNSW Medicine. He is a Theme Lead of the UTS Ageing Research Collaborative (UARC) and Director of the Centre for Health Technologies. His research focuses on osteoporosis genetics, digital health tools like BONEcheck, and epidemiological studies such as the Dubbo and Vietnam Osteoporosis Studies. Key contributions include the 'Osteogenomic Profile' and 'Skeletal Age' metrics for fracture risk assessment. Research interests span genetic and environmental factors in osteoporosis, AI-driven precision medicine, and digital epidemiology of chronic diseases. Collaborations include global institutions like UCSF, Harvard, and Johns Hopkins. Awards include NHMRC Leadership Fellow and recognition as a top-cited scientist. Grants include projects on clinico-genetic profiling and osteoporosis prevention. Awards: NHMRC Leadership Fellow, Most-Cited Scientist (PLoS Biology 2020), Fellow of the Academy of Health and Medical Sciences. Grants: Includes NHMRC Investigator Grant for fracture prediction and HCF-funded projects on cardiac arrhythmia monitoring. Teams: Leads a multidisciplinary group spanning Australia and Vietnam, focusing on clinical, genetic, and data science approaches to bone health.

• Osteoporosis
• Genetics
• Epidemiology
• +4 more

Dong-Hyun Kim, PhD, is a Professor at the Feinberg School of Medicine and McCormick School of Engineering at Northwestern University. His research focuses on developing therapeutic micro/nanoparticles for cancer treatment, including drug delivery, hyperthermia, immunotherapy, and molecular imaging. He collaborates with clinicians, biologists, and imaging professionals to translate multifunctional carriers into clinical applications. Education: PhD: Yonsei University College of Medicine, Korea (2006) Postdoctoral Fellow: University of Alabama, Chemical & Biological Engineering (2008) Postdoctoral Fellow: Argonne National Laboratory, Materials Science Division (2011) Research Interests: Therapeutic carriers for cancer treatment (e.g., nanoparticles, microspheres) Interventional oncology and targeted drug delivery Immunotherapy integration with nanotechnology Diagnostic imaging (MRI, CT, ultrasound) for treatment monitoring Translational research bridging lab and clinical applications Key Trends in Publications: Recent work emphasizes CRISPR-mediated genome editing, ferroptosis-inducing nanoparticles, cryo-immunotherapy, and radiomics for tumor assessment. Articles highlight synergy between nanotechnology and immunotherapy, with a focus on liver, prostate, and pancreatic cancers. Affiliations: Northwestern University Clinical and Translational Sciences Institute (NUCATS) Robert H. Lurie Comprehensive Cancer Center Labs/Teams: Active in multidisciplinary teams developing nanomedicine and interventional oncology therapies, leveraging Northwestern’s clinical and engineering resources.

• Therapeutic Carriers
• Nanotechnology
• Cancer Therapy
• +9 more

Dr. Mei-Ling Ting Lee is a Professor in the Department of Epidemiology and Biostatistics at the University of Maryland, College Park. She specializes in developing statistical models, notably the first hitting-time based threshold regression (TR) for analyzing time-to-event survival data, which has been extended to machine learning applications. As the Founding Editor and Editor-in-Chief of the Lifetime Data Analysis journal, she has significantly contributed to the field of time-to-event data methodologies. Her research encompasses genomic data analysis, statistical distribution theory, nonparametric methods, and applications in epidemiology. Dr. Lee has authored over 150 peer-reviewed articles and a seminal monograph, Analysis of Microarray Gene Expression Data (2004), widely used in genomic research. She has also co-edited influential books, including Lifetime Data Models in Reliability and Survival Analysis (1995) and Risk Assessment and Evaluation of Prediction (2013). Education: BS in Mathematics (National Taiwan University), MS (National Tsing Hua University), MA and PhD in Mathematics/Statistics (University of Pittsburgh). Her work focuses on integrating statistical theory with practical applications, including clinical trials, genomic studies, and public health research. She leads initiatives in statistical software development (e.g., R packages like clusrank ) and advocates for rigorous methodological standards in survival analysis.

• Time-to-event data modeling
• Genomic data analysis
• Statistical distribution theory
• +3 more

Dr. Yian Yin is an Assistant Professor of Information Science at Cornell University within the Cornell Bowers College of Computing and Information Science. His research focuses on computational social science, data science, and network science to study scientific progress, innovation, and complex social processes. He has affiliations with Northwestern University’s Northwestern Institute on Complex Systems (NICO) and Kellogg Center for Science of Science and Innovation (CSSI). Education: Ph.D. in Industrial Engineering and Management Sciences from Northwestern University Bachelor's degrees in Statistics and Economics from Peking University Research Interests: Computational tools for understanding scientific collaboration and innovation Analysis of policy impacts on scientific output during crises Quantitative frameworks for studying failure in scientific endeavors Cross-disciplinary applications in art, economics, and public health Awards: Forbes 30 Under 30 in Science (2023) Emerging Researcher Award from Complex Systems Society (2023) Advancement Activities: Organized Summer Institute in Computational Social Science (SICSS) Chicago Program Co-Chair for International Conference on Science of Science and Innovation Labs/Teams: Leads computational social science research groups at Cornell, focusing on science-of-science methodologies and innovation ecosystems.

• Computational Social Science
• Data Science
• Network Science
• +5 more