Kenneth Ross is a Professor in the Computer Science Department at Columbia University in New York City. His primary appointment is within the Department of Computer Science, with affiliations including the Foundations of Data Science Committee. His work bridges theoretical database research and practical system implementation. His research focuses on database systems with particular expertise in query processing, query language design, data warehousing, and architecture-sensitive database system design. Additional research spans computational biology, especially analysis of large genomic data sets. Current projects include Linear Algebra Operators in Databases for machine learning workloads and Repeats and Somatic Mutation analysis in genomics. His work consistently addresses the intersection of hardware capabilities and database system design. Ross leads the Database Research Lab at Columbia, which has produced significant work on query optimization, GPU database processing, and hardware-conscious database systems. His recent publications demonstrate strong focus on adapting database systems to modern hardware including GPUs, SIMD processors, and persistent memory. His scientific recognition includes: Packard Foundation Fellowship Sloan Foundation Fellowship NSF Young Investigator Award Distinguished Faculty Teaching Award (2008) Ross actively advises undergraduate engineering students (juniors with last names P-Z) and has taught foundational courses including Introduction to Databases and Programming and Problem Solving for over two decades. His teaching portfolio shows consistent engagement with both theoretical concepts and practical implementation challenges in computer science education.
Dr. Andre Kahles is a Lecturer in the Department of Computer Science at ETH Zürich, specializing in biomedical informatics. His research focuses on computational methods for analyzing large-scale genomic and transcriptomic data, with applications in cancer genomics, metagenomics, and precision medicine. He has contributed to the development of tools such as SplAdder for alternative splicing analysis, MetaGraph for petascale genomic data exploration, and SECEDO for subclone detection in cancer genomes. His work bridges algorithmic innovation with biological insights, addressing challenges in single-cell analysis, genome graph alignment, and multi-omics integration. Key research themes include: Developing scalable algorithms for processing nanopore sequencing and metagenomic data Characterizing somatic mutations and non-coding drivers in cancer genomes Advancing genome graph-based alignment and annotation methods Integrating multi-omics data for clinical decision-making and tumor profiling His publications span topics like RNA-seq analysis, chromothripsis in cancers, and global urban microbiome tracking through the MetaSUB consortium. Kahles has collaborated on landmark projects including the Pan-Cancer Analysis of Whole Genomes (PCAWG) and the Tumor Profiler Study.
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.
Dr. Brent Fogel is a Professor in the Departments of Neurology and Human Genetics at the David Geffen School of Medicine, UCLA. He directs the Neurogenetics Clinic and the UCLA Clinical Neurogenomics Research Center , focusing on diagnosing and managing genetic neurological disorders such as cerebellar ataxia , ataxia with oculomotor apraxia , spastic paraplegia , and leukodystrophies . His research integrates genomics , bioinformatics , and neuroimaging to improve precision medicine in prenatal counseling and rare disease diagnosis. Education: MD, PhD from Medical College of Wisconsin (2003) PhD in Genetics (2001) Internship in Internal Medicine (Northwestern University, 2004) Residency in Neurology (UCLA, 2007) Fellowship in Neurogenetics (UCLA, 2009) Board Certified in Neurology (2009) Research Focus: Dr. Fogel’s work spans neurogenetics , spinocerebellar ataxia , leukodystrophy , and genomic technologies . He has pioneered gene discovery in hereditary ataxias, developed transcriptional biomarkers , and contributed to diagnostic guidelines for rare disorders. His studies on lysosomal genes in Parkinson’s disease and exome sequencing disparities address critical gaps in neurogenetic research. Key Collaborations: He leads multicenter studies with the Ataxia Global Initiative , Undiagnosed Diseases Network , and Genomics England Research Consortium . His lab ( FogelLab ) develops tools like multiWGCNA for gene network analysis.
Prof. Dr. Susanne Foitzik is a Professor of Evolutionary Biology at Johannes Gutenberg University Mainz since 2010, where she leads the Evolution & Behavioral Ecology of Ants research group at the Institute of Organismic and Molecular Evolution (IOME). Previously, she was Professor in Behavioral Ecology at LMU Munich (2004-2010) and Assistant Professor in Zoology at the University of Regensburg (2000-2004). She earned her PhD in Biology from Julius Maximilian University, Würzburg in 1998. Her research integrates approaches from behavioral ecology through genomics to epigenetics, focusing on ants as model organisms to study complex social behaviors. Host-parasite coevolution and social parasitism in ants Molecular mechanisms underlying division of labor Reversal of the fecundity-longevity trade-off in social insects Gene regulation in phenotypic plasticity Evolution of chemical communication systems Analysis of her recent publications (2022-2025) reveals a strong focus on molecular mechanisms of social behavior, with particular emphasis on host-parasite interactions, epigenetic regulation of behavior, and genomic adaptations in social insects. Her work increasingly combines transcriptomic, proteomic, and functional genomic approaches to understand the molecular basis of social evolution. Among her notable scientific achievements: Speaker of Research Training Group 2626 GenEvo: Gene Regulation in Evolution (2019-present) Speaker of EES Master Program funded by VW foundation (2007-2010) DAAD Fellow at State University of New York (1992-93) Prof. Foitzik has supervised numerous PhD students and postdocs, including Maide Macit, Tom Sistermans, and Marcel Caminer. Her research is supported by multiple DFG-funded projects investigating host-parasite coevolution, the role of gene regulation in division of labor, and parasite interference in host gene expression. She serves as Handling Editor for Biology Letters and previously served on the editorial board of Insectes Sociaux. Her research group operates within the Institute of Organismic and Molecular Evolution (IOME) at Mainz, with laboratory facilities at the Biozentrum I. The group collaborates extensively with researchers across Germany and internationally, including partnerships with institutions in Frankfurt, Freiburg, Bristol, and Tel Aviv.
Ross Thyer is an Assistant Professor in the Department of Chemical and Biomolecular Engineering at Rice University. He holds a BSc (Hons) from the University of Western Australia and a PhD from the Harry Perkins Institute of Medical Research under Drs. Rackham and Filipovska. His postdoctoral training at the University of Texas at Austin with Prof. Andrew Ellington focused on engineered biosynthesis pathways and non-canonical amino acids. He co-founded GRO Biosciences, a Boston-based biotech startup, and leads the Thyer Lab at Rice. His research bridges synthetic biology, protein engineering, and molecular programming to address global challenges. Key areas include expanding genetic codes for therapeutics, engineering biosynthetic pathways via genetic circuitry, and developing microbial systems for environmental bioremediation. Core technologies include deep learning for protein design, modular DNA assembly, and high-throughput selections. The lab also develops tools like MutCompute for enzyme engineering and domesticates non-model bacteria for bioproduction. His work emphasizes technology innovation, with recent advances in selenocysteine incorporation, L-DOPA sensing systems, and actinobacteria toolkits. The Thyer Lab actively collaborates on biocatalyst development and translational applications in healthcare and industry.
Prof. Dr. Soeren Lienkamp is an Assistant Professor at the Institute of Anatomy , Faculty of Medicine , University of Zurich . His work bridges digital education and genetic research , focusing on enhancing medical teaching through innovative formats. Research Interests : Genetics, developmental biology, kidney disease modeling, CRISPR applications, digital medical education, and advanced microscopy. Methodologies : Combines Xenopus tropicalis models, deep learning , and bioengineering to study genetic kidney disorders and improve diagnostic tools. Publication Trends : His recent articles highlight predictable genome editing , 3D imaging technologies , and mechanistic insights into kidney and eye development. Earlier works focus on ciliary function , Wnt signaling , and metabolic stress in renal cells.
Philip Boone, MD, PhD, is an Attending Physician in the Division of Genetics and Genomics at Boston Children's Hospital and an Instructor of Pediatrics at Harvard Medical School. He specializes in medical genetics with particular expertise in rare disorders, medical mysteries, deletion and duplication syndromes, and Cornelia de Lange syndrome. Dr. Boone sees patients at Boston Children's Brookline location (2 Brookline Place, 7th Floor) and provides comprehensive genetic care including diagnostics, counseling, and individualized management. Stanford University (Undergraduate, 2006) Baylor College of Medicine (Graduate & Medical School, 2013-2014) Boston Combined Residency Program (Internship & Residency, 2016-2020) Harvard Medical School Genetics Training Program (Fellowship, 2020) Dr. Boone's research focuses on neurodevelopmental disorders, chromatin regulation, and genetic diagnostics. His work spans from fundamental genetic mechanisms to clinical applications, with particular emphasis on cohesinopathies including Cornelia de Lange syndrome. He has contributed significantly to understanding genetic variants associated with growth disorders, developmental features, and structural chromosomal abnormalities. His research combines advanced genomic technologies with clinical insights to improve diagnosis and management of rare genetic conditions. Analysis of Dr. Boone's publication record reveals a strong focus on medical genetics with emphasis on neurodevelopmental disorders, chromatin regulation, and genetic diagnostics. His work spans basic research on gene function and regulation to clinical applications in rare disease diagnosis. A notable trend is his investigation of cohesin complex disorders, particularly SMC3 variants and their relationship to Cornelia de Lange syndrome. His publications demonstrate expertise in both traditional genetic analysis and cutting-edge genomic technologies including long-read sequencing and telomere-to-telomere assembly. Dr. Boone actively contributes to medical education through publications on genetic diagnostics and distance learning resources for medical genetics. He has co-authored educational materials that help advance the field's knowledge base and training capabilities. As an attending physician in the Division of Genetics and Genomics at Boston Children's Hospital and a research fellow in the Center for Genomic Medicine at Massachusetts General Hospital, Dr. Boone works within one of the largest pediatric genetics practices in the country. The division includes over 30 board-certified clinical geneticists, genetic counselors, dieticians, and nursing staff who provide comprehensive care for patients with both common and extremely rare genetic conditions.
Katherine E. Varley, PhD is a Huntsman Cancer Institute Investigator and Associate Professor in the Department of Oncological Sciences at the University of Utah. She leads the Varley Lab and is a member of the Nuclear Control of Cell Growth and Differentiation Program, focusing on breast cancer genomics, epigenetics, and biomarker discovery. Her work bridges computational biology with clinical applications to improve breast cancer diagnosis and treatment. Dr. Varley earned her BS in Biology with a concentration in Computational Biology from Cornell University in 2003, followed by a PhD in Computational Biology from Washington University School of Medicine in 2009 under Dr. Robi Mitra. Her postdoctoral training was conducted in Dr. Richard M. Myers' laboratory at the HudsonAlpha Institute for Biotechnology, where she participated in the ENCODE Project Consortium. Her research focuses on using next-generation sequencing and computational analysis to study gene expression, transcription factor binding, and DNA methylation patterns in breast cancer. The Varley Lab investigates epigenetic gene regulation, develops novel molecular methods and bioinformatics approaches, and translates discoveries into clinical tools. Key research areas include Clinical Trial Genomics, Epigenome Engineering, Detecting Circulating Tumor DNA, and identifying Transcription Factors Driving Metastasis, with particular emphasis on triple-negative breast cancer. Analysis of Dr. Varley's publications reveals a consistent trajectory from fundamental genomic mechanisms to clinical translation, with recent work emphasizing biomarker discovery, tumor heterogeneity, and the development of genomic tools for precision oncology. Her research spans cancer biology, genomics, and computational analysis to address critical challenges in breast cancer treatment. Dr. Varley holds multiple patents related to cancer diagnostics and genomic technologies, including targeted sequencing methods, multigene assays for recurrence risk, and biomarkers for triple-negative breast cancer. These inventions reflect her commitment to translating basic research into clinical applications. She actively collaborates with clinical investigators in breast cancer trials and works closely with the Breast and Gynecologic Cancers Disease Center at Huntsman Cancer Institute. Her lab maintains four main research thrusts that collectively address breast cancer from molecular mechanisms to clinical applications, demonstrating a comprehensive approach to improving patient outcomes through genomic technologies.
Prof. Dr. med. Franz Lennard Ricklefs is a Senior Physician and Head of the Working Group at the Department of Neurosurgery, University of Hamburg Faculty of Medicine. He is a Medical Specialist in Neurosurgery with cross-disciplinary expertise in neuro-oncology, molecular pathology, and extracellular vesicle research. Affiliations: University Medical Center Hamburg-Eppendorf (UKE), European Liquid Biopsy Society (ELBS), International Consortium on Meningiomas (ICOM) Research Interests: His work focuses on neurosurgical oncology, particularly glioblastoma and meningioma pathobiology. He investigates DNA methylation patterns, extracellular vesicle biomarkers, and liquid biopsy implementation in clinical neuro-oncology. Additional interests include surgical outcomes for epilepsy and aneurysm management. Article Trends: Over the last decade, Dr. Ricklefs has published extensively on: Extracellular vesicle applications as liquid biopsy markers DNA methylation subclasses for glioblastoma and meningioma Multicenter surgical outcome benchmarking Immune evasion mechanisms in neuro-oncology Technological innovations in neurosurgical visualization Molecular characterization of rare CNS tumors Professional Contributions: He co-authored the MISEV2023 guidelines for extracellular vesicle studies and participates in international consensus reviews for meningioma classification. His collaborations span institutions across Europe and North America.
Professor David Taubman is a distinguished academic serving as Professor and Deputy Head of School (Research) at the School of Electrical Engineering and Telecommunications (EE&T) at the University of New South Wales (UNSW) in Sydney, Australia. He is also co-director of Kakadu Software Pty. Ltd. and its affiliates Kakadu R&D and Kakadu GPU. With a career spanning over three decades, Professor Taubman has made significant contributions to the field of image and video compression, most notably as the author of the EBCOT coding algorithm adopted in the JPEG2000 international standard. Professor Taubman earned his B.Sc. in Mathematics and Computer Science (1986) and B.E. (Medal) in Electrical Engineering (1988) from the University of Sydney, followed by an M.Sc. (1992) and Ph.D. (1994) in Electrical Engineering from the University of California at Berkeley. His professional journey includes engineering work at the Electricity Commission of N.S.W. (1988-1990), research positions at Hewlett-Packard Laboratories in Palo Alto (1994-1998), and an academic career at UNSW where he progressed from Senior Lecturer (1998-2003) to Associate Professor (2004-2009) and finally to Professor (2009-present). He has held various leadership roles including Head of the EE&T Telecommunications Research Group (2003-2014), Head of the EE&T Signal Processing Research Group (2014-present), Director of Research for the School of EE&T (2011-2016), and Deputy Head of School (Research) since 2017. Professor Taubman's research interests center on image and video compression, with particular expertise in JPEG2000 standards and implementations. His work spans signal processing, wavelet transforms, scalable video coding, motion modeling, and multimedia systems. He has pioneered numerous compression algorithms and frameworks, including the EBCOT coding algorithm that became central to the JPEG2000 standard. His recent research focuses on efficient motion modeling with cuboidal partitioning, learned lifting-based transform structures, and high-throughput implementations of JPEG2000 for video applications. His work bridges theoretical foundations with practical implementations, as evidenced by the commercially successful Kakadu Software tools that have garnered around 500 commercial licensees. Analysis of Professor Taubman's recent publications reveals a consistent focus on advancing compression technologies with particular emphasis on scalability, efficiency, and adaptability. His work spans traditional image compression (JPEG2000 extensions), video coding (cuboid-based partitioning for UHD/360-degree video), and emerging applications (nanopore sequencing data compression). A notable trend is the integration of machine learning techniques with traditional compression frameworks, as seen in his work on learned lifting-based transform structures. His research maintains strong connections to real-world applications across diverse domains including medical imaging, astronomical data processing, and genomic sequencing. IEEE Fellow Engineers Australia Fellow (by invitation) Professor Taubman has served as Associate Editor for the IEEE Transactions on Image Processing for two four-year appointments (2003-2005 and 2010-2013). He has been actively involved in numerous research grants focused on image and video compression technologies, particularly those related to the JPEG2000 standard and its extensions. His work has received significant industry support, reflected in his consultancy with various U.S., Japanese, and Australian corporations. He has also contributed to international standards development as a member of Standards Australia Technical Committee MS-065 (mirroring ISO TC42 on Digital Photography) and as a constitutional member of Standards Australia Technical Committee IT-029 (Coded Representation of Picture, Audio and Multimedia/Hypermedia Information). Professor Taubman co-directs Kakadu Software Pty. Ltd. and its research affiliates Kakadu R&D and Kakadu GPU, which have developed the commercially successful Kakadu Software tools for JPEG2000. His research group at UNSW focuses on advanced image and video compression techniques, with particular expertise in wavelet-based methods, scalable coding, and motion modeling. The group maintains strong industry connections and has contributed significantly to the development and standardization of image compression technologies worldwide.
Ben Raphael is a Professor in the Department of Computer Science at Princeton University, with affiliations at the Lewis-Sigler Institute for Integrative Genomics, Omenn-Darling Bioengineering Institute, and Center for Statistics and Machine Learning. He is also an Affiliate Faculty member at the Rutgers Cancer Institute of New Jersey, Irving Institute for Cancer Dynamics at Columbia University, and New York Genome Center. His research focuses on computational methods for analyzing large-scale biological data, emphasizing cancer evolution, network/pathway analysis, and structural variation in genomes. Research Trends: His recent work spans cancer lineage trees, spatial transcriptomics, optimal transport for developmental models, and network analysis of mutations. Articles highlight applications in prostate cancer, pancreatic cancer, and single-cell genomics. Scientific Awards: 2024 ACM Fellow 2023 RECOMB Test of Time Award 2022 RECOMB Test of Time Runner-Up 2021 ISCB Innovator Award 2021 RECOMB Best Paper Runner-Up 2020 ISCB Fellow 2020 AACR Team Science Award 2011 NSF CAREER Award 2013 RECOMB Best Paper 2010-2012 Sloan Research Fellowship Advising: He has mentored numerous Ph.D. students and postdoctoral fellows, many of whom have transitioned to academic and industry roles. Current advisees include Uthsav Chitra, Gillian Chu, and Alexander Strzalkowski. Labs & Teams: Raphael leads the Raphael Lab at Princeton, developing tools like HotNet2, CHISEL, and HATCHet for cancer genomics and network analysis.
Xihong Lin is a Professor of Statistics at Harvard University and a Professor of Biostatistics at the Harvard T.H. Chan School of Public Health. She is a distinguished academic, holding membership in both the National Academy of Sciences and the National Academy of Medicine. Her research focuses on scalable statistical inference for big data, statistical machine learning, causal inference, and integrative data analysis, with applications in genomics, public health, and precision medicine. Lin’s work addresses challenges in analyzing large-scale genomic and multi-ancestry data, including methods for rare variant association testing, ancestry-adjusted sample analysis, and scalable computing frameworks. Her contributions span biobank studies (e.g., UK Biobank, TOPMed) and clinical applications in lung cancer, cardiovascular health, and smoking cessation. Her scientific awards reflect her leadership in statistical genetics and public health. Key research trends include leveraging single-cell sequencing for functional genomics, developing ensemble machine learning methods for health subtyping, and enhancing polygenic risk prediction across diverse populations. Lin’s methodologies prioritize interpretability and scalability, enabling impactful analyses of complex observational and genomic datasets. Awards: Member, National Academy of Sciences; Member, National Academy of Medicine Her grants and advising efforts focus on interdisciplinary collaborations, bridging statistics, AI, and domain sciences. Lin leads initiatives to improve genomic data management and ethical use of federated data (e.g., FADI framework). She is affiliated with labs advancing statistical genetics and cloud-based workflows (e.g., STAAR workflow).
Prof. Dr. Sven Panke is a Full Professor and Head of the Department of Biosystems Science and Engineering at ETH Zürich. His research focuses on bioprocess engineering, synthetic biology, and enzymatic process development. Key areas include miniaturized bioreactor systems, microbial engineering for novel metabolite production, and high-throughput screening methodologies. Education: Studied Biotechnology at TU Braunschweig, with postgraduate research at the German National Research Center for Biotechnology and ETH Zurich. Transitioned from industry (DSM) to academia in 2001 as an Assistant Professor, progressing to Associate Professor (2007-2009) before leading the BSS department. Research interests emphasize directed evolution of enzymes, metabolic pathway engineering, and systems biology approaches to optimize microbial production systems. Current projects include bio-indigo synthesis, antimicrobial peptide discovery, and synthetic biology tools for cellular engineering. Labs/Teams: Leads the Bioprocess Engineering Lab at ETH Zurich, collaborating on projects like the E. coli import system design and γ-glutamyltransferase engineering. Active in developing microfluidics platforms for parallel reaction analysis. Grants/Advising: Funded by initiatives in sustainable biomanufacturing and synthetic biology. Supervises graduate students in bioprocess design and microbial systems engineering.
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.
