Louis Narens is a Professor at the University of California, Irvine (UCI), holding dual affiliations in the Department of Cognitive Sciences and the Department of Logic and the Philosophy of Science. His work bridges mathematical rigor with psychological and philosophical inquiry, focusing on foundational issues in measurement theory, probability, and metacognition. Narens is renowned for his contributions to abstract measurement theory, as seen in his influential books like Abstract Measurement Theory (1985) and Theories of Meaningfulness (2002). His research explores how quantitative frameworks can be applied to subjective phenomena such as perception, belief systems, and cognitive processes. Key areas of investigation include: Foundations of probability and support theory Psychophysical laws and perceptual scaling Metamemory mechanisms and judgment accuracy Philosophical implications of measurement invariance His articles analyze topics like evolutionary color categorization, scientific belief systems, and the theoretical underpinnings of psychological measurement. Narens collaborates across disciplines, engaging with cognitive scientists, philosophers, and mathematicians to advance interdisciplinary understanding. Despite his prolific output, he has not been explicitly noted for receiving major scientific awards in the provided materials.
Andrea Sottoriva is the Head of the Computational Biology Research Centre at Human Technopole , Milan, Italy, and holds the title of Professor of Cancer Genomics and Evolution . His work bridges computational biology, evolutionary theory, and clinical oncology to predict cancer progression and design adaptive treatment strategies. University of Bologna – BSc in Computer Science (2006) University of Amsterdam – MSc in Computational Sciences (2008) University of Cambridge – PhD in Computational Biology (2012) Dr. Sottoriva's research focuses on cancer evolution , applying machine learning and population genetics to decode tumor heterogeneity through multi-omics data. His lab integrates patient-derived organoids and spatial genomics to understand how genetic and epigenetic factors drive cancer progression. The 15 most recent publications demonstrate a consistent emphasis on subclonal dynamics (7/15), computational methods (6/15), and evolutionary modeling (5/15). Key themes include adaptive mutability in colorectal cancer , immune editing in post-transplantation relapses, and deep learning applications for tumor heterogeneity. Scientific recognition includes: Cancer Research UK Future Leaders in Cancer Research Prize (2016) His lab currently trains PhD students and postdoctoral researchers in computational oncology, maintaining a living biobank of patient-derived models while pioneering AI-mechanistic hybrid models for clinical translation.
Dr Sheryl Chang is a Research Associate in the Modelling and Simulation Research Group at the School of Computer Science, University of Sydney. She holds a PhD in computational epidemiology (2021) and specializes in modeling infectious disease transmission and intervention strategies, integrating social and behavioral factors. Her work has been validated in multiple epidemic scenarios and recognized by global health organizations like the WHO and Lancet COVID-19 Commission. Teaching: She instructs courses such as System Dynamics Modelling for Project Management (PMGT5886) and Social Network Analysis Principles (OLET2346) . Her research focuses on pandemic dynamics, pathogen evolution, and the impact of human behavior on disease spread. Awards: Recipient of the prestigious Lord Robert May Prize (2019-2020) for best paper in Journal of Biological Dynamics , and 2023 Dean’s commendation for teaching excellence in the Faculty of Engineering. Research Grants: Lead investigator on the 2022 Sydney Institute for Infectious Diseases grant Modelling the impact of opinion dynamics on the COVID-19 pandemic in Australia . Labs/Teams: Active member of the Modelling and Simulation Research Group, collaborating on agent-based models for public health policy design and genomic epidemiology of pathogens like Salmonella and SARS-CoV-2.
Pier Palamara is an Associate Professor of Statistical and Population Genetics at the University of Oxford's Department of Statistics, affiliated with the Centre for Human Genetics. He holds a PhD in Computer Science from Columbia University (2014) and completed postdoctoral training at Harvard Chan School of Public Health and the Broad Institute of MIT and Harvard. His research integrates statistics, computer science, and genetics to develop methods for analyzing large genomic datasets, focusing on evolutionary parameters, demographic history, complex trait genetics, and disease variation. Key research interests include reconstructing population movements via genetic data, studying natural selection and mutation rates in human genomes, and developing scalable algorithms for genomic analysis. He leads the Palamara Lab, which collaborates on projects like the Genomics England haplotype reference panel and the UK Biobank imputation. His lab's work is supported by grants and partnerships, and they develop software tools such as ASMC, Quickdraws, and Threads. Recent publications highlight contributions to Indo-European genetic origins, scalable mixed-model association methods, and ancient DNA analysis of European farmers. He advises graduate students and has mentored researchers in computational biology and statistical genetics.
Josie Clowney is an Associate Professor in the Department of Molecular, Cellular, and Developmental Biology at the University of Michigan, where she has held faculty position since 2017. Her research investigates the genomic algorithms that construct neural circuits during development, using Drosophila as a model to study how chemosensory systems drive both instinctual behaviors and learning. She teaches Bio 172 and an upper-level seminar on cellular diversity and scientific writing, and mentors graduate students through MCDB, CMB, NGP, and BIOINF PhD programs. Her educational background includes: Ph.D. in Biomedical Sciences (2012) from the University of California, San Francisco B.S. in Cellular and Molecular Biology (2005) from the University of Michigan, where she conducted research with Cunming Duan Clowney's research centers on understanding how definitive neuronal parameters are encoded in genomic information and translated into cellular architectures. Her lab hypothesizes that developmental algorithms for learning circuits versus instinctual circuits differ fundamentally in their genomic requirements, with chemosensory circuits serving as key models. Using fruit flies for their tractable brain organization, her work bridges computational principles and biological implementation to uncover universal brain organization rules. Analysis of her 15 most recent publications (2016-2025) reveals consistent focus on Drosophila mushroom body development, neural sexual differentiation, and spatial constraints in circuit formation. Key themes include non-deterministic mechanisms diversifying cell surface expression, chromatin dynamics in circadian regulation, and how input density tunes sensory responses. Her work integrates genomics, neuroanatomy, and behavior to model how compact genomic information generates complex neural architectures. No scientific awards were mentioned in the provided text. Dr. Clowney advises graduate students through multiple PhD programs at the University of Michigan, though specific student names and grant details are not provided in the source material. Her teaching includes foundational undergraduate coursework and advanced seminars emphasizing scientific writing. The active publication record spanning 2016-2025 indicates sustained research funding supporting her lab's investigations into neural circuit development. The Clowney Lab, housed in the Biological Sciences Building (4218 BSB), employs Drosophila genetics and neuroanatomical techniques to dissect developmental algorithms of brain wiring. Current projects explore how spatial constraints structure learning circuits, mechanisms of neural sexual differentiation, and the genomic encoding of circuit diversity. The lab collaborates within Michigan's neuroscience community through the Program in Biology and participates in interdisciplinary initiatives studying brain evolution and function.
Erik Sperling is an Associate Professor of Earth and Planetary Sciences at Stanford University, affiliated with the Stanford Doerr School of Sustainability. He is also a Senior Fellow at the Woods Institute for the Environment and holds a courtesy appointment as Associate Professor in the Department of Oceans. His research focuses on Earth’s environmental and biological evolution, particularly the interplay between atmospheric oxygen levels, marine redox conditions, and the emergence of complex life during the Neoproterozoic and Paleozoic eras. Research interests include paleoceanography, geochemical analysis of sedimentary records, early animal evolution, and the biogeochemical drivers of mass extinctions. He integrates fieldwork, laboratory geochemistry, and computational modeling to explore topics such as Ediacaran-Cambrian transitions, the role of oxygenation in metazoan diversification, and modern organismal responses to environmental stressors. His work spans geological time scales, from studying Precambrian shales and stromatolites to analyzing the physiological limits of marine organisms under deoxygenation scenarios. Recent studies emphasize the long-term oxygenation history of oceans, the ecological consequences of hypoxia-temperature interactions, and the application of novel geochemical proxies to reconstruct ancient environments. Laboratory activities include the Sperling Lab, which develops innovative methods for trace element analysis and integrates multi-proxy datasets to address questions in Earth’s history. Collaborations with institutions worldwide focus on global sedimentary geochemical databases and field projects in regions like the Yukon, Brazil, and Australia.
Eduardo Eyras is a Professor at the Australian National University (ANU) and EMBL Australia Group Leader, leading research in computational RNA biology and cancer genomics. He directs the Centre for Computational Biomedical Sciences and is part of the Shine-Dalgarno Centre for RNA Innovation. His work focuses on transcriptome and epitranscriptome analysis using long-read sequencing, machine learning, and computational methods to study cancer mechanisms. Eyras holds a PhD in Mathematics from the University of Groningen (1999) and previously led research at the Sanger Institute and Pompeu Fabra University. Affiliations: Director, Centre for Computational Biomedical Sciences Researcher, Shine-Dalgarno Centre for RNA Innovation Member, Division of Genome Sciences and Cancer Leader, The Eyras Group - Computational RNA Biology Research Interests: Development of algorithms for long-read sequencing Machine learning applications in RNA biology Epitranscriptomic modifications and cancer Therapeutic mRNA platform steering Key Projects: Novel algorithms for transcriptome variation analysis Predictive models of RNA modifications in disease Ribosomal DNA variation analysis Advisees & Grants: Supervises PhD students (e.g., Favour Oyelami, Stefan Prodic) and leads ARC-funded projects on mRNA diagnostics and epitranscriptomic therapies. Collaborates with global teams on forensic genomics, cancer drug resistance, and AI-driven translational research. Labs/Teams: Leads the Eyras Group, collaborating with the Hannan Group (Cancer Therapeutics) and Shirokikh Group (Protein Biosynthesis).
Dr. Michael Wollenberg is an Associate Professor of Biology and Department Chair at Kalamazoo College. He holds a PhD from the University of Wisconsin-Madison and a BA from Swarthmore College. His research focuses on molecular mechanisms of bioluminescence in Photorhabdus luminescens , including its interactions with nematodes and insect hosts. He investigates bacterial symbiosis, microbial ecology, and the regulation of light production genes. Dr. Wollenberg teaches courses in microbiology, molecular biology, and evolutionary biology. Education: PhD in Medical Microbiology and Immunology, University of Wisconsin-Madison BA in Biology, Swarthmore College Research Interests: Photorhabdus luminescens bioluminescence evolution, Photorhabdus -nematode symbiosis, bacterial competition dynamics, and microbial community ecology. His lab uses interdisciplinary approaches including genetics, biochemistry, and computational biology. Grants & Awards: NSF ISO 1755230 (2018–2022) NSF Graduate Research Fellowship (2005–2008) NIH Traineeships in Oral Health & Microbial Disease (2010–2013) Teaching: Courses include BIOL 322 General and Medical Microbiology , BIOL 295 Computational Tools for Biologists , and BIOL 112 Evolution and Genetics . He emphasizes growth mindset and active learning in his pedagogy. Lab & Outreach: The Wollenberg Lab actively involves undergraduates in research. Current projects explore bioluminescence regulation and host-microbe interactions. His work has been featured in Proceedings of the National Academy of Sciences and Applied and Environmental Microbiology .
Mehdi Sadi is an Assistant Professor of Electrical and Computer Engineering at Auburn University's College of Engineering. He holds a Ph.D. from the University of Florida, an M.S. from the University of California-Riverside, and a B.S. from Bangladesh University of Engineering and Technology. His research focuses on secure and reliable system-on-chip design, AI/ML-driven VLSI CAD/EDA, neuromorphic hardware, and emerging post-CMOS computing technologies. Notable achievements include earning the NSF CAREER Award for chiplet-based design optimization and a $175k NSF grant for magnetic RAM research. His work integrates machine learning with hardware co-design to enhance AI accelerators' performance, energy efficiency, and security. Recent projects include adversarial attack mitigation on AI hardware and reliability analysis of neuromorphic systems. Dr. Sadi's contributions span chiplet architecture, memory systems (e.g., STT-MRAM/SOT-MRAM), and fault-tolerant computing. He actively publishes on topics like skyrmion logic gates and TRNG implementations using MRAM. His work bridges theoretical machine learning advancements with practical hardware implementations, addressing critical challenges in next-generation computing systems.
Lu Cheng is a Visiting Professor in the Department of Computer Science at the University of Helsinki, affiliated with the Vehtari Aki Professorship. He holds a Doctor of Philosophy in Natural Sciences from the University of Helsinki (2013). His research focuses on computational genomics, bioinformatics, and microbial genetics, with emphasis on DNA sequence analysis, nanopore sequencing technologies, and systems biology. He leads projects on alternative splicing in cancer and the impact of microbiota on human health. Notable contributions include the NanoBaseLib benchmark dataset and methods for RNA modification analysis. His work addresses UN Sustainable Development Goals related to good health and innovations in data science. Education: Doctor of Philosophy in Natural Sciences (2013), University of Helsinki; Doctoral degree in Natural Sciences (2013), University of Helsinki. Research Interests: Genomics, computational biology, microbial ecology, RNA sequencing technologies, and bioinformatics tool development. His projects explore bacterial population dynamics, host-pathogen interactions, and applications of machine learning in genomics. Advising: Supervises doctoral researchers including Guangzhao Cheng and Chengbo Fu. Active in grants such as the Academy of Finland Research Fellowship (2023-2025). Labs/Teams: Leads research groups focused on single-cell genomics and computational methods for biological systems.
Teresa Lynch is an Assistant Professor at The Ohio State University, affiliated with the School of Communication and directing the Chronos Laboratory. She holds a Ph.D. and M.A. in Mass Communication from Indiana University (2017, 2013) and a B.A. in Communications from Armstrong State University (2008). Ph.D., Indiana University, Bloomington (2017) M.A., Indiana University, Bloomington (2013) B.A., Armstrong State University, Savannah (2008) Her research examines emotion in video games, focusing on how digital environments convey social information that shapes emotion, cognition, and behavior. Key areas include gender representation in games, player processing of media messages, and emotional engagement with interactive content. She employs mixed methods (experimental, survey, content analysis) and interdisciplinary frameworks (gender studies, evolutionary biology). Recent publications address themes like female character design , ambivalent sexism , player-avatar bonds , and mental health perception . Awards include recognition as a Distinguished Reviewer in 2021. She has taught courses on gender in media , communication technology , and electronic media advertising . Service roles include chairing the 2016 ICA Game Studies Division preconference and leadership roles since 2011.
Lee Spector is a Professor of Computer Science at Amherst College and an Adjunct Professor at the University of Massachusetts, Amherst . Previously, he taught at Hampshire College from 1992 to 2019, where he held roles including Dean of the School of Cognitive Science and Director of the Computational Intelligence Laboratory . He earned a B.A. in Philosophy from Oberlin College (1984) and a Ph.D. in Computer Science from the University of Maryland (1992). His research focuses on artificial intelligence, artificial life, evolutionary computation, and intersections with cognitive science, physics, and the arts. Notable contributions include work on genetic programming for music generation (e.g., GenBebop ), quantum computing algorithms, and evolutionary robotics. He serves as Editor-in-Chief of Genetic Programming and Evolvable Machines and has authored over 100 publications, including the book Automatic Quantum Computer Programming: A Genetic Programming Approach (2004). Spector has received prestigious awards such as the NSF Director's Award for Distinguished Teaching Scholars and gold medals in the GECCO Human Competitive Results contest. He also engages in public outreach, including an op-ed in The Boston Globe on digital evolution (2005).
Karl Schmid is a W3 Professor of Crop Plant Biodiversity and Breeding Informatics at the University of Hohenheim's Institute of Plant Breeding, Seed Science and Population Genetics within the College of Agricultural Sciences. His research integrates evolutionary genetics, population genomics, and machine learning to address agricultural challenges. Ph.D. in Biology, University of Munich (1996) Postdoctoral Research, Cornell University (1997-1999) Emmy-Noether Research Group, Max Planck Institute of Chemical Ecology (2000-2006) Group Leader, Leibniz Institute of Plant Genetics (2006-2008) Professor of Genetics, Swedish Agricultural University (2008) His research focuses on crop biodiversity conservation, evolutionary genetics of plant pathogens, and breeding informatics applications. Current work leverages deep learning for phenotyping (quinoa panicles, barley genomics) and analyzes pathogen evolution (Exserohilum turcicum in maize). His team actively develops computational tools like GGoutlieR for geo-genetic pattern detection. Recent publications demonstrate strong trends in applying AI to agricultural genomics, particularly in quinoa improvement and pathogen surveillance. His group leads the EU H2020 INVITE project on molecular markers in plant variety protection and organizes international symposia like the 2024 Quinoa Symposium at Hohenheim. Head of Crop Biodiversity and Breeding Informatics Group Principal Investigator, EU H2020 INVITE project Organizer, International Quinoa Symposium 2024
Dr. Richard Molyet is a Senior Lecturer and Undergraduate Director in the Department of Electrical Engineering and Computer Science at the University of Toledo's College of Engineering. After retiring as Associate Professor in 2002, he returned to academia in 2005 as Visiting Professor and transitioned to Associate Lecturer in 2008. Education: Ph.D. in Engineering Science (1981) from University of Toledo His research spans Automatic Control , Robotics , Smart-Grid Systems , and Biomedical Applications . Recent publications focus on deep learning for medical diagnostics and hybrid power network optimization , while earlier work explored repetitive control algorithms and microprocessor-based motion analysis . Scientific Recognition: IEEE Third Millennium Medal (2000) IEEE-USA Professional Achievement Award (2002) University of Toledo Outstanding Teacher Award (2016) Currently advising 3 PhD students and multiple Master’s candidates, Dr. Molyet has served on numerous academic committees since the 1980s. He maintains an active role in IEEE Toledo Section's executive board for 39 years .
Ernst Strüngmann Institute for Neuroscience in Cooperation with Max Planck Society (associated institute)Germany
Dr. Rosanne Rademaker is a Research Professor and Group Leader at the Rademaker Lab, part of the Ernst Strüngmann Institute (ESI) in Frankfurt, Germany, affiliated with Goethe University’s Department of Psychology. Her research focuses on understanding how sensation and cognition interact to shape human perception, particularly in visual working memory, attention, and physiological arousal states. Her lab employs behavioral, computational, and neuroimaging techniques (fMRI, M/EEG) to explore how the brain balances perceptual input with stored memories. In addition to foundational work on memory and attention, the lab investigates context effects on perception, motor-output impacts on visual processing, and computational neural principles. Rosanne emphasizes collaborative, fun science, fostering an inclusive environment through outreach and international collaborations. Key recent work includes studies on categorical representations in the visual hierarchy and neural dynamics during memory recall. Lab Members: Giuliana Giorjiani (PhD), Noa Noelle Krause (MSc), Amit Rawal (PhD), Maria Servetnik (PhD), Nursima Ünver Aydingül (PhD). Grants & Collaborations: Mishal Qubad’s “Junior Clinician Scientist” grant on schizophrenia visual maps, international collaborations with Toronto and the Max Planck School of Cognition. Teaching: Lectures on “Introduction to Cognitive Psychology” at Goethe University. Publications highlight her work in Nature Neuroscience , eLife , and Journal of Cognitive Neuroscience , with over 30 peer-reviewed articles. The lab actively engages in conferences (VSS, ECVP) and hosts annual retreats to promote scientific exchange.
