Peter Brodersen is a Professor at the Department of Biology, University of Copenhagen , specializing in Bioinformatics and RNA Biology . His research focuses on RNA modification (m6A), YTHDF proteins, and small RNA pathways in plants. Recent research trends from his group include: (1) molecular mechanisms of ARGONAUTE-small RNA interactions, (2) m6A-YTHDF regulatory systems in plant development, and (3) RNAi-independent roles of DICER-LIKE proteins in antiviral defense. Collaborations span Denmark and international institutions. Publications highlight cross-disciplinary work bridging computational biology and experimental plant genetics. Key subfields include RNA structure, epigenetic regulation, and antiviral immunity.
Jennifer S. Thaler is a Professor in the Department of Ecology and Evolutionary Biology at Cornell University, affiliated with the College of Arts and Sciences. She holds a Ph.D. from the University of California, Davis (1999) and a B.A. from Wellesley College (1993). Her research focuses on tri-trophic interactions between plants, herbivores, and predators, with an emphasis on chemical ecology, plant defense mechanisms, and pest control strategies. She teaches courses such as Chemical Ecology and Insect Ecology, and her work bridges fundamental ecological theory with applied agricultural challenges. Dr. Thaler’s research investigates how plant traits, predator presence, and nutritional states influence herbivore behavior and population dynamics. Notable projects include studying non-consumptive predator effects, plant genotypic diversity’s impact on herbivores, and the evolutionary potential of antipredator plasticity. Her publications span journals like Ecology , Oecologia , and Proceedings of the Royal Society B . Her scientific contributions include winning the 2nd place Elton Prize (2015) for research on predator effects on aphids. She actively engages in departmental initiatives, including the Graduate Program and the Plant-Insect Interactions Seminar. Affiliated with the Cornell Stable Isotope Laboratory, she contributes to interdisciplinary efforts in ecological research and education.
Mikael Thollesson is a Senior Lecturer at Uppsala University, affiliated with the Department of Organismal Biology; Systematic Biology and Klubban’s Biological Station. His research focuses on evolutionary biology, phylogenetics, taxonomy, and molecular biology, particularly in marine and freshwater sponges (Porifera), bacterial pathogens, and computational methods in evolutionary analysis. Evolutionary Biology Marine Biology Taxonomy His recent publications highlight trends in sponge biodiversity, phylogeography, bacterial horizontal gene transfer, and mitochondrial gene evolution. Key articles include studies on Swedish demosponge faunas, Silene sect. Arenosae systematics, and computational tools like SPRIT for detecting gene transfers. No explicit awards or grants are mentioned.
Bernhard J. Berger is a Lecturer in the Department of Computer Engineering at the Institute of Embedded Systems, Hamburg University of Technology (TUHH). His research focuses on software security, static code analysis, machine learning, optimization, and research data management. He has held significant roles such as Program Committee member for ICPC 2025 and MSR 2025, and has received awards including the Best Reviewer Award (ICPC 2023) and Best Engineering Paper Award (SCAM 2019). His work spans interdisciplinary applications including maritime systems security, GPU-accelerated AI, and evolutionary algorithms. Recent studies emphasize AI-driven security tools (e.g., ML-SAST) and domain-specific language approaches to optimization (EvoAl). He has contributed to over 30 peer-reviewed publications, with notable work in IEEE Transactions on Software Engineering and Science of Computer Programming. Berger collaborates closely with industry through DAAD review committees and serves on artifact evaluation boards for ISSTA and ARES conferences. Education: Doctoral Thesis (2022), Diploma in Computer Science (2007) Key Projects: ArchSec tool suite, Threat Modeling Frameworks, Bauhaus static analysis methodology Lab Affiliation: Embedded Systems Design Group His advisory roles include Deputy of TUHH's Election Verification Committee and Session Chair at IEEE Congress on Evolutionary Computation 2023. Current research trends integrate machine learning with static analysis for automated vulnerability detection, while also exploring explainable AI techniques for neural network optimization.
Anna Gottard is an Associate Professor of Statistics at the University of Florence, where she leads the Department of Statistics, Computer Science, and Applications. She directs the Florence Center for Data Science (FDS) and participates in the Technical Scientific Committee of the Tuscan Center for Big Data, Data Science, and AI (CBDAI). Her research focuses on multivariate statistical models, particularly graphical models, and extends to statistical machine learning, fair models, and directional data analysis. She is an Associate Editor for the Journal of the Royal Statistical Society Series A (JRSSA) and Statistical Methods & Applications (SMA). Her recent work includes Bayesian approaches for mixed graphical models, uncertainty-aware classification trees, and methodological advancements in latent uncertainty models. Her contributions span theoretical developments and applied research in interdisciplinary areas like biostatistics and sustainability. Her research interests emphasize bridging statistical theory with practical applications, including fairness in machine learning, interpretable models, and tree-based methodologies. She has actively contributed to open-source software, notably the Mix3Trees R package for mixed-effect tree models. Her work addresses challenges in variable selection, graphical model inference, and ethical AI practices. Current projects explore Bayesian frameworks for complex data structures and methodological improvements in graphical model interpretability. Anna has advised on interdisciplinary collaborations, such as studies on GDPR compliance in biobanking and epidemiological modeling of the SARS-CoV-2 pandemic in Tuscany. She collaborates with institutions like the CBDAI to advance data science applications in regional policy and healthcare. Her research trajectory reflects a commitment to both foundational statistical theory and real-world problem-solving across diverse domains.
Jenny Ouyang is an Associate Professor in the Department of Biology at the University of Nevada, Reno , where she also serves as Director of the Ecology, Evolution and Conservation Biology graduate program. She earned her B.S. and B.A. from the University of California, Irvine (2007), followed by M.A. and Ph.D. in Ecology and Evolutionary Biology from Princeton University (2009, 2012). Her research focuses on the ecology and evolution of physiological systems , particularly how hormonally regulated traits enable organismal adaptation to environmental changes like urbanization , light pollution , and endocrine stress responses . Education: Ph.D., Ecology and Evolutionary Biology, Princeton University (2012) M.A., Ecology and Evolutionary Biology, Princeton University (2009) B.S., Biology, University of California, Irvine (2007) B.A., French, University of California, Irvine (2007) Her work integrates neuroendocrine mechanisms with ecological contexts to understand phenotypic flexibility and epigenetic adaptation in birds. Recent projects examine how artificial light at night disrupts circadian rhythms, hormonal profiles, and parental behaviors across urban-rural gradients. She has secured major grants including the NSF CAREER award (2022) for studying urbanization and NIH COBRE funding (2017) as part of a neuroscience team. Key collaborations include Dr. Maria Echeverry at Universidad Pontificia Javeriana in Colombia through her 2023 Fulbright award . The Ouyang Lab combines natural and laboratory experiments to investigate stress physiology, with recent papers analyzing glucocorticoid responses to urbanization, gene expression patterns under light pollution, and epigenetic reorganization in response to environmental stressors. Her publications span top journals like Proceedings of the Royal Society B , Biology Letters , and Ecology Applications , where her 2022 paper on lead pollution and reproduction was highlighted by ESA and Swedish Radio. Scientific Awards & Recognition: US Fulbright Scholars Award (2023) NSF CAREER grant (2022) NIH COBRE grant (2017) as team member Advising students like Valentina Alaasam (NSF GRFP awardee) and Ivan Celso Carvalho Provinciato (Dean's Merit Fellowship)
Qiaowei Pan is a Researcher at the University of Lausanne , focusing on Evolution and Ecology . They have held a Guest Researcher role at the Institute of Molecular Biology gGmbH (IMB) in Mainz, Germany since 2023, and a Postdoctoral Researcher position at the University of Lausanne since 2018. Education: PhD in Molecular and Evolutionary Biology (2014-2018), INRAe, University of Rennes II, France Erasmus Mundus Master in Evolutionary Biology (MEME) (2012-2014), University of Groningen (Netherlands) & University of Montpellier II (France) BSc in Biology (2008-2012), University of North Carolina-Chapel Hill, USA Research Interests: Qiaowei Pan's work centers on the intersection of molecular genetics , evolutionary biology , and developmental biology , particularly in sex determination mechanisms across diverse animal models. Their studies span non-coding RNA regulation , sex chromosome evolution , and signal transduction pathways like TGF-β in reproductive systems. Publication Trends: Recent articles highlight expertise in sex determination systems (5/12 publications), genomic approaches (6/12), and fish developmental evolution . Collaborative work includes computational methods ( RADSex workflow ) and comparative studies across ant , goldfish , catfish , and cavefish models. Labs & Teams: Currently affiliated with the Keller-Valsecchi group at IMB and the Department of Evolution and Ecology at the University of Lausanne.
Prof. Dr. Nina Gantert is a distinguished Professor of Probability Theory at the Technical University of Munich (TUM) , affiliated with the TUM School of Computation, Information and Technology . She has held faculty positions at Karlsruhe Institute of Technology and the University of Münster prior to joining TUM in 2011. Her research focuses on probability theory , particularly stochastic processes , large deviations , and random media . She investigates random walks in random environments as models for transport in disordered systems and explores applications in physics and biology . Recent publications highlight her work on branching random walks , mixing times , biased random walks , and large deviation principles for complex stochastic systems. She has co-authored studies on random walks in dynamical percolation , interacting edge-reinforced processes , and extremal point processes in branching models. Scientific Awards: Elected fellow of the IMS (2016) Her academic career spans institutions including ETH Zürich, University of Bonn, Technical University of Berlin, and TUM. She has supervised numerous Bachelor’s and Master’s theses on topics ranging from mixing time analysis to percolation theory , often collaborating with international co-authors.
Professor Daniel Segrè is a faculty member at Boston University, holding the title of Professor of Biology, Bioinformatics, and Biomedical Engineering. His research focuses on systems biology, microbial ecology, and metabolic engineering, with an emphasis on understanding complex biological networks and their applications in bioenergy and biomedicine. Segrè leads the Segre Lab ( segrelab.bu.edu ), where theoretical and computational approaches are applied to study metabolism, microbial interactions, and synthetic biology. Segrè earned his PhD from the Weizmann Institute of Science, Israel. His work bridges fundamental science and applied engineering, addressing topics such as microbial community dynamics, metabolic pathway design, and environmental microbiome applications. Research Interests: Systems biology of metabolism, evolution of biochemical networks, microbial interactions, bioinformatics, and environmental microbiome engineering. His lab develops computational models (e.g., COMETS) to simulate microbial ecosystems and design synthetic microbial communities for climate change mitigation and bioenergy production. Teaching: Courses include BE 777 (Computational Genomics), BF 821 (Bioinformatics Seminar), and BF 571 (Dynamics and Evolution of Biological Networks). These courses reflect his expertise in integrating computational methods with biological systems analysis.
Gabriel Birzu is an Assistant Professor in the Department of Physics at the University of Florida. He develops quantitative models of microbial ecology and evolution using statistical physics approaches. His research investigates fine-scale diversity in microbial communities, examining how spatial processes shape evolutionary trajectories. Recent work analyzes hybridization barriers in cyanobacteria and genealogical patterns during range expansions. Birzu's interdisciplinary approach combines theory, computation, and data analysis to understand microbial diversification mechanisms and community responses to environmental perturbations.
Dr. Ahmet Acar is an Associate Professor at the Department of Biological Sciences, Middle East Technical University (METU), Ankara, Turkey. He leads the Cancer Precision Medicine and Drug Resistance Laboratory, focusing on understanding mechanisms of drug resistance in cancer. His research integrates experimental models, next-generation sequencing, and deep learning to address clinical challenges in cancer therapy. Dr. Acar holds a B.Sc. from METU's Biological Sciences department and a Ph.D. from the Cancer Research UK Manchester Institute. He completed postdoctoral training at the Institute of Cancer Research, London, and the University of Manchester. Research Interests: Drug resistance mechanisms, precision oncology, tumor microenvironment modeling, patient-derived organoids, computational pathology, and evolutionary cancer biology. His lab develops 2D/3D co-culture systems, PDO biobanks, and AI-driven histopathology tools to improve treatment strategies. Recent Work Trends: Recent publications emphasize tumor evolution modeling, matrix mechanics in drug resistance, and AI applications in histopathology. Collaborations with hospitals in Turkey and Europe support PDO biobank initiatives. His team explores evolutionary steering strategies to exploit collateral drug sensitivities. Labs/Teams: Precision Medicine and Drug Resistance Lab at METU focuses on interdisciplinary approaches combining wet-lab experiments with computational methods. Current projects include ex vivo tumor modeling and AI-driven diagnostic tools for oncology.
Max Planck Institute for Biological IntelligenceGermany
Maude Baldwin is the Director of the Evolution of Sensory and Physiological Systems department at the Max Planck Institute for Biological Intelligence. Her research focuses on the molecular and physiological mechanisms underlying sensory receptor evolution in vertebrates, particularly in birds. Education : Ph.D. from Harvard University (Department of Organismic and Evolutionary Biology, 2007-2014); B.A. from New York University (Gallatin School of Individualized Study, 2005). Research Interests include: Evolution of taste receptors, such as the repurposing of savory receptors for sweet detection in hummingbirds. Convergent evolution in sensory systems across vertebrates. Integrative approaches combining molecular methods, cell culture, and behavioral studies. Impact of dietary shifts on ecological and physiological adaptations. Publication Trends reveal a focus on comparative genomics , protein evolution , and sensory system adaptation , with specific attention to bird taste receptors , gene loss , and echolocation genetics . Labs & Teams : Baldwin leads a multidisciplinary team at the Max Planck Institute, recruiting researchers in comparative genomics , organoid technology , and vertebrate natural history . The group investigates sensory-diet coevolution and physiological trade-offs.
Eduardo Azevedo is the John M. Bendheim and Thomas L. Bendheim Professor of Business Economics and Public Policy at the Wharton School , University of Pennsylvania. He holds a courtesy appointment as Professor of Economics and was awarded the 2016 Sloan Foundation Fellowship. His research integrates economic theory with practical applications across science and business domains. His research interests include: Market design Selection markets Social science genetics Experimental economics Game theory Recent publication trends focus on: Economic theory applications to healthcare and digital markets Empirical Bayes methods in A/B testing Adverse selection in insurance markets Strategic behavior in two-sided matching Evolutionary behavioral economics He serves as an instructor for BEPP2500 - Managerial Economics , emphasizing real-world application of microeconomic theory to business problems. His work also involves software development for economic research, including MATLAB-based empirical Bayes tools for analyzing treatment effects in large-scale experiments. Scientific awards : Sloan Foundation Fellow (2016)
Chang-Jun Liu is a Senior Scientist in the Plant Science Group of the Biology Department at Brookhaven National Laboratory, where he has conducted research on plant phenylpropanoid biosynthesis and lignin metabolism since joining in 2005. He also holds an Adjunct Professor position in the Biochemistry & Cell Biology Department at Stony Brook University and serves as Associate Editor for Plant Cell & Environment (2024-present) and Frontiers in Plant Sciences (2015-present). Dr. Liu's educational background includes: Ph.D. in Plant Biochemistry and Molecular Biology from the Shanghai Institute of Plant Physiology, Chinese Academy of Science (1999) Dr. Liu's research integrates approaches from biochemistry, molecular genetics, biophysics, protein engineering, metabolic engineering, and synthetic biology to investigate phenylpropanoid and lignin biosynthesis in plants. His laboratory addresses fundamental questions about how lignin and related compounds are synthesized and incorporated into cell walls, how regulatory networks govern metabolic activity, and how lignification influences cell wall structure and function. A central aim of his research is optimizing plant feedstocks for efficient lignocellulosic biomass utilization. Analysis of Dr. Liu's publication record reveals a consistent trajectory from fundamental biochemical mechanisms to applied bioenergy solutions. His recent work focuses on cytochrome b5 diversity, electron transfer mechanisms in phenolic biosynthesis, and metabolic engineering approaches to modify lignin composition. This research spans from evolutionary studies of lignin biosynthesis across plant lineages to practical applications in bioenergy crop improvement. Dr. Liu has received recognition for his contributions to science, including: Brookhaven National Laboratory Science and Technology Award (2018) Dr. Liu serves as Editorial Board Member for the Journal of Biological Chemistry (2020-present), PNAS Nexus (2024-present), and Plant Physiology Journal (2025-). He is Scientific Lead at the Joint BioEnergy Institute, Feedstocks Division, Lawrence Berkeley National Laboratory, and Project Lead at the Center for Bioenergy Innovation, Oak Ridge National Laboratory. His research is funded by the U.S. Department of Energy through multiple Bioenergy Research Centers. Dr. Liu leads a research group at Brookhaven National Laboratory focused on elucidating the posttranslational regulation and macromolecular organization of lignin biosynthesis, with applications toward developing designer lignins and reducing biomass recalcitrance for sustainable biofuel production. His work addresses the critical challenge of lignin's dual nature: while it impedes enzymatic access to polysaccharides in biofuel production, it also represents the most abundant renewable source of aromatic carbon for high-value bioproducts.
Dr. Eli Strauss is a behavioral ecologist and Assistant Professor in the Department of Integrative Biology at Michigan State University , where he is establishing a lab focused on the evolution and ecology of social behavior. He co-directs the Mara Hyena Project , a long-term study of hyena behavior and ecology in Kenya. His research spans dominance hierarchies, longitudinal studies of animal societies, and computational methods for analyzing social dynamics. He has developed tools like the DynaRankR R package for inferring longitudinal dominance hierarchies and DomArchive for compiling dominance data. His work addresses challenges such as mismatched timescales in behavioral studies and demographic drivers of hierarchy dynamics, often using spotted hyenas as a model species. Dr. Strauss is currently recruiting lab members for graduate student, postdoc, and technical roles, with lab establishment planned for late 2025–Fall 2026. His publications reflect interdisciplinary interests in behavioral ecology, animal societies, and data-driven approaches to understanding dominance and social networks.
