Claudio R. Alarcón is an Associate Professor in Pharmacology at Yale University School of Medicine. His research focuses on RNA metabolism's role in development, health, and disease, particularly RNA modifications and non-coding RNAs. He joined Yale in 2017 after postdoctoral training at The Rockefeller University and holds a PhD from Cornell University (2009) and a BSc from Pontificia Universidad Católica de Chile (1999). Research Interests: Functional roles of m6A RNA modifications MicroRNA biogenesis and cancer progression Non-coding RNA regulation in metastasis Key Appointments: Primary Faculty, Yale Cancer Biology Institute Member, Yale Cancer Center Faculty, Yale Combined Program in Biological and Biomedical Sciences His lab integrates bioinformatics, molecular, and cellular approaches to study cancer metastasis mechanisms, including miRNA processing disruptions and SOX4/TMEM2 pathways linked to clinical outcomes.
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.
Lisa Wills serves as Assistant Professor of Computer Science at Duke University's Trinity College of Arts & Sciences and holds a joint appointment in Electrical and Computer Engineering at the Pratt School of Engineering since 2019. Her research bridges computer architecture and domain-specific applications, with a focus on hardware acceleration for computationally intensive fields. Dr. Wills earned her Ph.D. from Columbia University in 2014. Her academic journey reflects a deep commitment to advancing hardware-software co-design methodologies for real-world computational challenges. Her research centers on developing efficient hardware accelerators for big data analytics, particularly in genomics, graph processing, and database systems. She pioneers frameworks that simplify accelerator deployment while tackling critical bottlenecks in genomic data analysis, protein structure prediction, and privacy-preserving computing. Current work focuses on hardware-aware machine learning systems and energy-efficient architectures for emerging AI applications. Analysis of her publication record reveals a clear trajectory: from foundational work in database processing units (2014-2016) to specialized genomic accelerators (2019-2021), then evolving toward ML-enhanced design automation (2022-2023) and cutting-edge architectural abstractions (2024-2025). Her research consistently targets the intersection of hardware efficiency and domain-specific computational demands, with increasing emphasis on AI/ML workloads. Google ML and Systems Junior Faculty Award (2025) Dr. Wills actively mentors doctoral students including Chris Kjellqvist (lead architect of Beethoven accelerator framework), Mason Ma (PyTFHE FHE framework), and Mansi Choudhary (COCOSSim accelerator simulator). Her research is supported by significant grants including the NSF AI Institute: Athena ($20M, 2021-2027), Meta-funded ProSE accelerator project (2023-2026), and NSF CAREER award (2021-2026), totaling over $25M in active funding. She directs the APEX Lab (Application-driven Programmable Efficient Accelerated Systems), which develops open-source frameworks like Beethoven for FPGA/ASIC accelerator deployment and focuses on lowering barriers for non-hardware researchers to leverage custom acceleration in genomics, AI, and big data applications.
David Hong is an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Delaware. He holds a PhD from the University of Michigan, where he was an NSF Graduate Research Fellow, and previously served as an NSF Postdoctoral Research Fellow at the University of Pennsylvania. His research focuses on developing robust methods for analyzing heterogeneous and high-dimensional data, particularly through low-rank matrix and tensor techniques. Applications span medical imaging, radar systems, genomics, and astronomy. He emphasizes theoretical guarantees and practical algorithms for signal extraction and inverse problems. Education: PhD in Electrical Engineering and Computer Science (University of Michigan), NSF Postdoctoral Research Fellowship (University of Pennsylvania). Research Interests: Low-rank matrix/tensor methods, heterogeneous data analysis, unsupervised learning, and applications in healthcare, imaging, and sensor systems. His work addresses noise robustness, scalable algorithms, and real-world deployment challenges. Scientific Awards: Recipient of the NSF Postdoctoral Research Fellowship (2020) and NSF Graduate Research Fellowship (2015). Advising & Grants: Advisor to graduate students in machine learning and signal processing (no named advisees listed). Active NSF grant recipient for foundational and applied research in data science. Labs/Teams: Engaged in interdisciplinary collaborations through the University of Delaware's Center for Computational Research and Data Science initiatives.
Brian D. Gregory is a Professor of Biology at the University of Pennsylvania's School of Arts & Sciences. His research focuses on RNA modifications, computational biology, and plant genetics, particularly studying how RNA modifications regulate gene expression in plants and animals. He holds a Ph.D. from Harvard University (2005) and a B.S.A. from the University of Arizona (2000). Research Interests: RNA epitranscriptomics (e.g., m6A, NAD+ caps) RNA secondary structure and protein interactions Genomic approaches to study plant stress responses Development of high-throughput sequencing tools like PIP-seq Recent Work Highlights: Recent studies include analyzing pathogen-induced RNA modifications' role in plant immunity (Plant Cell 2023), global RNA structure/protein interaction mapping, and epitranscriptomic dynamics in drought tolerance. His lab's work bridges computational methods with molecular genetics to uncover post-transcriptional regulatory mechanisms. Lab & Collaborations: The Gregory Lab uses Arabidopsis thaliana as a primary model organism but also explores animal systems. They collaborate with institutions like Cornell University and have developed protocols published in Current Protocols in Molecular Biology. Teaching: BIOL 4231: Genome Sciences and Genomic Medicine BIOL 6010: Communication for Biologists
Paul R. Genssler is a Dr.-Ing. researcher at the Chair of AI Processor Design (AI-Pro) within the Technical University of Munich (TUM), actively advancing hardware solutions for artificial intelligence under Prof. Hussam Amrouch. His work bridges computer engineering and emerging technologies, focusing on overcoming fundamental limitations in conventional computing architectures through brain-inspired paradigms. His research spans critical domains in next-generation computing: Hyperdimensional Computing for robust pattern recognition and bioinformatics applications Neuromorphic and In-Memory Computing architectures for energy efficiency Reliability engineering for emerging memory technologies (FeFET, etc.) Quantum computing support systems including cryogenic embedded electronics Machine learning-driven transistor aging prediction and mitigation Analysis of his 15 most recent publications (2023-2024) reveals a dominant trend toward hyperdimensional computing as a unifying framework for addressing reliability challenges in emerging technologies. His work consistently integrates in-memory computing techniques to bypass von Neumann bottlenecks while targeting real-world applications like genome matching and unsupervised learning. A significant portion focuses on error-resilient implementations for unreliable nanoscale devices, demonstrating exceptional cross-stack expertise from transistor physics to algorithm design. As a core member of TUM's AI Processor Design group affiliated with the Munich Institute of Robotics and Machine Intelligence (MIRMI), Genssler collaborates extensively on projects spanning cryogenic quantum control systems, FPGA-based AI resilience, and monolithic 3D integration. The team operates at the intersection of semiconductor physics, computer architecture, and machine learning, with strong industry connections evident through publications at DATE, ASP-DAC, and ICCAD.
Prof. Dr. Jörg Hackermüller is a computational biologist with expertise in Omics data integration Toxicology Environmental risk assessment Non-coding RNA biology . He serves as Head of the Department of Computational Biology and Chemistry at the Helmholtz Centre for Environmental Research (UFZ) since 2024 and holds a Professorship at the Faculty of Mathematics and Computer Science at Leipzig University since 2021. His research focuses on Developing AI methods for chemical toxicity prediction Multi-omics integration for mechanistic toxicology Data standardization in environmental monitoring Non-coding RNAs as biomarkers in disease and toxicity and has produced 15+ recent publications spanning tools like multiGSEA and deepFPlearn+ . He collaborates with teams across UFZ Leipzig University Novartis Fraunhofer Institute and leads projects like InCeTo and SafePol , integrating exposome research with systems biology.
Nikolaus Rajewsky is a leading Professor at the Max Delbrück Center for Molecular Medicine (MDC) and Charité – Universitätsmedizin Berlin , where he founded and directs the Berlin Institute for Medical Systems Biology (BIMSB) . His lab integrates experimental (biochemistry, molecular biology) and computational (bioinformatics, physics) approaches to study RNA regulation in gene expression , with applications to developmental biology, regeneration, neurodegenerative diseases, and cancer . Using model systems like C. elegans , planaria, and human brain organoids, his team pioneers cutting-edge methods such as MirDeep , DistMap , and FLAM-seq for RNA analysis. His research focuses on single-cell transcriptomics , spatial RNA sequencing , and circular RNA (circRNA) regulation , revealing novel roles for circRNAs like CDR1as in neuropsychiatric disorders. Recent work includes 3D tumor microenvironment mapping and computational modeling of RNA metabolism in diseases. Scientific Awards : Gottfried Wilhelm Leibniz Prize (2012) EMBO Membership (2010) Honorary PhD, Sapienza University of Rome (2014) Berlin Science Award (2009) His team's recent articles highlight breakthroughs in 3D spatial transcriptomics , circRNA degradation mechanisms , and mitochondrial disease modeling using human brain organoids. The lab actively collaborates with clinical partners across Charité and European institutions, driving the LifeTime initiative for cell-based interceptive medicine.
James Manley is the Julian Clarence Levi Professor of the Life Sciences at Columbia University, with extensive research in gene expression regulation. His work spans transcription, RNA splicing, and polyadenylation mechanisms in human cells, connecting these processes to neurodegenerative diseases (ALS/FTD) and cancers. Affiliation: Columbia University, Department of Biological Sciences Contact: jlm2@columbia.edu Research Interests: Dr. Manley's laboratory investigates nuclear processes including: Transcriptional control via RNA polymerase II CTD modifications Alternative splicing regulation by hnRNP and SR proteins Polyadenylation dynamics in cell cycle and differentiation Disease mechanisms in spliceosome mutations (SF3B1, SRSF2) RNA-protein interactions in stress responses Publication Trends: Recent work focuses on disease-associated mutations affecting RNA processing, non-canonical RNA functions, and immune regulation via polyadenylation. Articles span molecular oncology, neurodegeneration, and RNA surveillance mechanisms. Scientific Recognition: Member, American Academy of Arts & Sciences Member, National Academy of Sciences Key Collaborations: Studies involve interdisciplinary work with neurology, cancer biology, and immunology teams. His lab employs biochemical assays, structural analysis, and genetic models to dissect RNA processing pathways.
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.
Julia V. Halo is an Associate Professor in the Department of Biological Sciences at Bowling Green State University (BGSU) , where she leads the Halo Lab . Her research focuses on the genomic impact of transposable elements , particularly endogenous retroviruses (ERVs) and SINE/LINE pairs , in human and non-human systems. She received her Ph.D. in Molecular Microbiology from Tufts University's Sackler School of Biomedical Sciences. Research Interests Genomic evolution driven by retrotransposon activity ERV-host interactions in disease and evolution Mechanisms of SINE/LINE retrotransposition Comparative genomics of mobile elements Publications & Grants 15+ peer-reviewed articles in journals like PNAS , Retrovirology , and PLoS Genetics Three consecutive NIH R15 AREA grants (2017, 2020, 2025) for ERV studies in domestic dogs Scientific Awards 2024 President’s Award for Collaborative & Creative Research 2021 Elliot L. Blinn Award for Faculty-Undergraduate Innovation 2020 Outstanding Early Career Award 2021 Sigma Phi Epsilon Faculty Fellow Mentoring & Lab Members Mentored students: Abigail Jarosz-DiPietro (Ph.D.), Maddie Altieri (M.S., now Ph.D. student), and Savanna Spitnale (M.S.) Undergraduate researchers: Abby Grady, Molly Buffenbarger, Genesis Pyles, and others
Professor Udo Oppermann serves as Professor of Molecular Biology and Director of Laboratory Sciences at the Institute of Musculoskeletal Sciences, Botnar Research Centre, University of Oxford. He is also Deputy Director of the Oxford Centre of Translational Myeloma Research and a fellow at St Catherine's College. His educational background includes a Diploma in Human Biology (1990) and PhD in Pharmacology and Toxicology (1994), both earned with distinctions from Philipps University Marburg. Prior academic appointments include Associate Professor at Karolinska Institutet (until 2004) and sabbatical work at Yale University. Research focuses on epigenetic mechanisms in disease through drug and target discovery using systems biology and single-cell approaches . Key disease targets include metabolic disorders, inflammatory conditions, and malignant diseases—particularly multiple myeloma and secondary bone cancers. His group pioneers chemical biology applications in primary tumor microenvironments. Current funding sources include Cancer Research UK, Innovate UK, EPSRC, Royal Society-Newton Fund, Bristol Myers Squibb, Bayer Healthcare, GlaxoSmithKline, Blood Cancer UK, and Leducq Foundation. Notable research trends show increasing emphasis on epigenetic regulation in immune cells (2020-2024), single-cell technologies for myeloma (2022-2024), and translational applications of chromatin modifiers (2016-2019). Recent work integrates metabolomics with epigenetic mechanisms in gynecological and hematological disorders. He supervises doctoral research including Singh K.'s 2024 thesis on sonodynamic therapy mechanisms. Leadership roles encompass directing Oxford's Molecular Laboratory Sciences division and co-leading translational myeloma research initiatives.
Norbert O. Reich is a Distinguished Professor in the Department of Chemistry & Biochemistry at the University of California, Santa Barbara (UCSB), affiliated with the College of Letters and Science. He joined UCSB in 1987 after completing his Ph.D. at UCSF in 1984 and an NIH postdoctoral fellowship there. His research focuses on enzyme mechanisms, particularly DNA methylation and telomerase, with applications in antibiotic and cancer therapy design. He also develops innovative chemical biology tools, including gold nanoshell-based drug delivery systems and fluorescence-based protein tracking methods. Education: Ph.D. in Chemistry from UCSF (1984). Awards: Regent's Junior Faculty Fellowship (1987), American Cancer Society Faculty Research Award (1991), UC President's Award for Excellence in Undergraduate Research (1994). Research Interests: Epigenetic regulation via DNA methylation in bacteria and mammals Enzyme mechanisms of DNA methyltransferases (e.g., DNMT3A, CcrM) Design of therapeutic inhibitors targeting epigenetic enzymes Light-controlled delivery of proteins/RNA via gold nanoshells Protein-DNA interaction analysis using microfluidic arrays Awards and Recognition: His honors reflect contributions to both research and education, emphasizing his dual impact in science and teaching. Lab and Collaborations: Leads the Reich Lab, collaborating with researchers like Tom Pettus (UCSB) and Erkki Ruoslahti. Projects include antibiotic development, cancer epigenetics, and nanotechnology-driven drug delivery. Future Work: Expanding applications of nanoshell technology for targeted gene silencing and exploring allosteric inhibitors of DNMT3A for cancer treatment.
Zixiang Xiong is a Professor and Associate Department Head in the Department of Electrical and Computer Engineering at Texas A&M University, holding the Robert M. Kennedy '26 Endowed Professorship II. He earned his Ph.D. in Electrical Engineering from the University of Illinois at Urbana-Champaign in 1996. His career includes roles at Princeton University, University of Hawaii, and Texas A&M since 1999. Education: Ph.D., Electrical Engineering, University of Illinois at Urbana-Champaign, 1996 Visiting Research Associate, Princeton University, 1995–1997 University of Hawaii, 1997–1999 Research Interests: Focuses on machine learning, image/video processing, federated learning, network information theory, biomedical engineering, and communications. His work spans distributed source coding, genomic signal processing, and energy-efficient systems. Publications & Awards: Over 200 publications, including seminal works on distributed video coding and network information theory. Notable awards include the NSF Career Award (1999), ONR Young Investigator Award (2001), IEEE Fellow (2006), and the ECE Outstanding Faculty Award (2024). His research has led to patents in video compression and multimedia systems. Grants & Advising: Active in NSF-funded projects on coding theory and energy-delay tradeoffs. Advises numerous PhD and MS students, with over 50 alumni in academia and industry. Collaborates on biomedical imaging, remote sensing, and federated learning initiatives. Labs & Teams: Leads a dynamic research group at Texas A&M, focusing on cutting-edge projects in signal processing and machine learning applications. Collaborates with industry and governmental agencies on applied research.
Guillaume Chanfreau is a Professor in the Department of Chemistry and Biochemistry within the College of Letters and Science at the University of California Los Angeles (UCLA). His research focuses on fundamental mechanisms of RNA metabolism, with particular emphasis on RNA splicing, decay pathways, and ribonuclease functions. His work spans molecular biology, biochemistry, and genetics, utilizing yeast as a primary model organism to investigate conserved RNA processing mechanisms. Professor Chanfreau's research interests center on understanding how RNA processing pathways regulate gene expression. His work examines transcription termination, RNA splicing fidelity, RNA decay mechanisms, and the role of ribonucleases in cellular RNA homeostasis. He investigates how these processes are interconnected and how they respond to cellular stress conditions. His laboratory has made significant contributions to understanding how RNA quality control mechanisms prevent the accumulation of aberrant transcripts and maintain cellular health. Analysis of Chanfreau's recent publications (2020-2025) reveals a strong focus on RNA splicing mechanisms, RNA decay pathways, and ribonuclease functions. His work frequently employs yeast genetics combined with advanced RNA sequencing techniques. A notable trend is the increasing use of long-read sequencing technologies to analyze RNA isoforms and decay intermediates. His research consistently bridges fundamental molecular mechanisms with potential implications for understanding human diseases related to RNA processing defects. Professor Chanfreau has been continuously funded by the National Institutes of Health, with his current grant R35GM130370 (2019-2023) titled 'The Control of Gene Expression by Eukaryotic Ribonucleases' and previous long-term funding through R01GM061518 (2000-2019). His research program has supported numerous graduate students and postdoctoral researchers who have contributed to his extensive publication record spanning over two decades.
