جست‌وجوی استاد و پژوهشگر

Moises A. Bernalمشاهده پروفایل

استادیار

• Fish Ecology
• Evolutionary Biology
• Marine Biology
• +۷ مورد دیگر

Moises A. Bernal is an Assistant Professor in the Department of Biological Sciences at Auburn University, where he leads the Fish Ecology and Evolution Lab. His research integrates ecological, evolutionary, and molecular approaches to study how marine fishes respond to environmental stressors such as climate change and ocean warming. Education: Postdoctoral Fellow – State University of New York at Buffalo (2018–2019) Postdoctoral Fellow – King Abdullah University of Science and Technology (2016–2018) Ph.D. in Marine Science – University of Texas, Austin (2009–2015) B.Sc. in Biology and Environmental Sciences – University of Panama (2003–2008) His research focuses on the metabolic, physiological, and epigenetic mechanisms underlying fish acclimation to climate change. He investigates transgenerational responses, thermal tolerance, and the role of environmental history in shaping population resilience. His work combines field studies with molecular tools such as transcriptomics and genomics. The recent publications highlight a strong trend in studying coral reef fishes under climate stress, particularly through molecular and genomic lenses. Key themes include thermal acclimation, gene expression changes during heatwaves, and evolutionary divergence in sympatric species. His work bridges organismal physiology with evolutionary genomics. He teaches courses such as BIOL 3040 (Biology of Marine Systems) and BIOL 5440/6440 (Climate Change Physiology and Evolution) at both undergraduate and graduate levels. He advises students in his lab and mentors research on fish responses to environmental change. The Fish Ecology and Evolution Lab conducts integrative research on marine fishes, focusing on stress response mechanisms and evolutionary adaptations. Lab activities include molecular analyses, experimental physiology, and fieldwork related to coral reef ecosystems.

Osbert Bastaniمشاهده پروفایل

دانشیار

• Machine Learning
• Neurosymbolic AI
• Program Synthesis
• +۱۰ مورد دیگر

Osbert Bastani is an Associate Professor at the Department of Computer and Information Science, University of Pennsylvania, leading the trustml@Penn research group. He is affiliated with the ASSET , PRECISE , and PRiML centers, and the PLClub research group. His research focuses on Trustworthy Neurosymbolic Systems , Synthesizing Neurosymbolic Programs , and Machine Learning for Programmer Productivity , with applications in verification, fairness, and human-AI collaboration. He received the NSF CAREER Award in 2023. His recent publications (2024-2025) emphasize AI Safety , LLM Robustness , and Algorithmic Fairness , including work on adversarial robustness, conformal prediction, and program synthesis. Students he has advised include Sagnik Anupam, Stephen Mell, Jason Ma, Shuo Li, and others. Awards: NSF CAREER Award (2023)

Martin T. Wellsمشاهده پروفایل

استاد

• Applied Statistics
• Theoretical Statistics
• Bayesian Statistics
• +۷ مورد دیگر

Martin T. Wells is the Charles A. Alexander Professor of Statistical Sciences at Cornell University, with joint appointments in the Department of Statistical Science, Department of Biological Statistics and Computational Biology, Department of Social Statistics, and as Professor of Clinical Epidemiology and Health Services Research at Weill Medical School. He serves as Editor-in-Chief of the ASA-SIAM Book Series and Co-Editor of the Journal of Empirical Legal Studies. Cornell University, Ithaca, NY Weill Cornell Medical College Research Interests span applied and theoretical statistics, Bayesian methods, biostatistics, clinical epidemiology, and computational biology. His work bridges disciplines like finance, legal studies, and health services research. Article Trends highlight advancements in Bayesian modeling, quantum cognition machine learning, tensor analysis, and misclassification correction, with applications in genomics, finance, and public health. Fellow of the American Statistical Association Fellow of the Royal Statistical Society Contributions include developing statistical software (e.g., rTensor), methodological innovations in clinical trials, and empirical legal studies on civil rights and the death penalty.

• Uncertainty Reasoning and Decision Making in Artificial Intelligence
• Electronic Business
• Systems Analysis and Design
• +۷ مورد دیگر

Liping Liu is a Professor in the Department of Management at The University of Akron's College of Business. He holds a Ph.D. in Business from the University of Kansas (1995), Master of Engineering in Systems Engineering (1991), and dual bachelor's degrees in Applied Mathematics (1986) and River Dynamics (1987). Ph.D., University of Kansas MS, Huazhong University of Science and Technology B.E., Wuhan University BS, Huazhong University of Science and Technology His research spans Artificial Intelligence , Electronic Business , Systems Analysis , Data Quality , and Belief Function Theory . He pioneered coarse utility theory and linear belief functions , now taught in top Ph.D. programs across multiple disciplines. Key trends in his publications include Belief Function Applications (2012-2024), Medical Data Systems (2003-2015), and Decision Theory (2004-2014). Recent works focus on Gamma Belief Functions (2024) and computational improvements in linear belief function operations (2019-2016). Scientific contributions recognized via: Microsoft Azure Educator Grant (2014-2016) Inclusion in Who's Who in America (2010-2013) and Who's Who in the World (2011-2013) As an editor and committee member for major conferences (INFORMS, AMCIS, Belief Functions conferences), he bridges academic research with practical systems implementation in e-business and healthcare domains.

Steven I-Jy Chienمشاهده پروفایل

استاد

• Transportation Engineering
• Urban Rail Transit
• Sustainable Transportation Systems
• +۴ مورد دیگر

Steven I-Jy Chien serves as Professor and Director of the Transportation Program within the Department of Civil and Environmental Engineering at the New Jersey Institute of Technology (NJIT). His career spans academia, government, and industry with significant contributions to transportation engineering research and practice. His educational credentials include: Ph.D. in Civil and Environmental Engineering from University of Maryland-College Park (1995) M.S. in Civil and Environmental Engineering from University of Maryland-College Park (1991) B.S. in Civil Engineering from Tamkang University (1983) Professor Chien's research focuses on transportation system resilience, sustainable transit operations, and advanced traffic modeling. His work addresses critical challenges in urban rail networks, demand-responsive transit services, and energy-efficient transportation systems. He employs sophisticated computational methods including genetic algorithms, machine learning, and Bayesian approaches to solve complex transportation problems involving network vulnerability, passenger behavior, and infrastructure optimization under uncertainty. Analysis of his recent publications reveals strong emphasis on transportation resilience against cascading failures, sustainable operations for electric transit systems, and pandemic-responsive aviation scheduling. His research spans diverse geographic contexts including major Chinese metropolitan areas and U.S. transportation networks, demonstrating global applicability of his methodologies. His professional recognition includes: 2024 Keynote Speaker at Union-Tech Lecture, National Taiwan Ocean University 2022 Keynote Speaker at International Conference of Chinese Institute of Transportation 2022 Best Poster Award from New Jersey Department of Transportation Professor Chien has secured research funding from federal agencies including the Federal Highway Administration (FHWA) where he contributed to CORSIM traffic simulation software development. His industry experience with China Engineering Consultants Inc. and Information Dynamic Inc. informs his practical approach to transportation challenges. As Transportation Program Director, he oversees curriculum development and industry partnerships that prepare students for transportation sector careers. He maintains active collaboration with transportation agencies globally, particularly through his leadership in the Transportation Program at NJIT which serves as a hub for innovation in urban mobility solutions.

• Synthetic Biology
• Systems Biology
• Quantitative Biology
• +۵ مورد دیگر

Ting Lu is an Associate Professor at the University of Illinois at Urbana-Champaign in the School of Biomedical and Translational Sciences, focusing on microbial synthetic biology and systems biology. Their research bridges biology, engineering, and physics to reprogram cellular functionalities through gene regulatory networks. Ph.D. in Biophysics, University of California at San Diego (2007) B.S. in Physics, Zhejiang University (2002) Ting Lu's work explores microbial ecosystems, synthetic gene circuits, and their applications in biotechnology and medicine. By combining experimental approaches with mathematical modeling, they investigate bacterial communication networks, metabolic pathways, and spatial dynamics in microbial communities. Selected research trends include microbial consortia engineering for bioremediation and bioproduction, complexity reduction in microbiomes, and predictive modeling of synthetic gene networks. Their publications span high-impact journals such as Nature Communications , Nature Chemical Biology , and eLife . Fellow, American Institute for Medical and Biological Engineering (2022) Future Insight Prize (2021) Donald Biggar Willett Faculty Scholar (UIUC) (2020) NIH Maximizing Investigators' Research Award (2019) NSF CAREER Award (2015) AHA National Scientist Development Grant (2012) Ting Lu's lab has received grants from NIH, NSF, ONR, and industry partners. They offer undergraduate research opportunities in synthetic and systems biology, and teach advanced courses such as BIOE 430 - Intro Synthetic Biology and BIOE 432 - Systems Biology .

Alexandre Bouchard-Côtéمشاهده پروفایل

استاد

• Computational Statistics
• Bayesian Inference
• Monte Carlo Methods
• +۴ مورد دیگر

Alexandre Bouchard-Côté is a Professor of Statistics at the University of British Columbia (UBC), affiliated with the Department of Statistics within the Faculty of Science. His research focuses on computational statistics, Bayesian methods, and Monte Carlo techniques, with applications in evolutionary biology, cancer genomics, and computational linguistics. Education : PhD in Computer Science (with Designated Emphasis in Statistics) from UC Berkeley (2010), BSc in Mathematics and Computer Science from McGill University (2005). Affiliations : Director of the Blang probabilistic programming project and leader of the Bouncy Particle Sampler research group. Research Interests : Bouchard-Côté develops scalable Bayesian computational methods, including non-reversible Monte Carlo algorithms like the Bouncy Particle Sampler, and applies these to problems in cancer phylogenetics, evolutionary dynamics, and historical linguistics. His work emphasizes bridging theoretical foundations with practical tools for data science. Publications Trends : Recent work spans distributed sampling frameworks (e.g., Pigeons.jl), variational phylogenetic inference, and cancer clonal evolution modeling. His articles often address algorithmic scalability and interdisciplinary applications in biology and astronomy. Awards : CRM-SSC Prize in Statistics (2024) PIMS-UBC Mathematical Sciences Young Faculty Award (2018) Tweedie New Researcher Award (2016) Advising & Grants : Supervises graduate students (e.g., Son Luu, Nikola Surjanovic) and leads funded projects on distributed MCMC and cancer genomics. Collaborates with institutions like the Simons Foundation and the Canadian Statistical Sciences Institute (CANSSI). Labs/Teams : Core member of the UBC Statistical Machine Learning group, contributing to open-source tools like Blang and the Bouncy Particle Sampler implementation.

Mark Lewisمشاهده پروفایل

استاد

• Mathematical Biology
• Spatial Ecology
• Animal Movement Modelling
• +۷ مورد دیگر

Mark Lewis is the Kennedy Chair in Mathematical Biology at the University of Victoria, holding joint appointments in the Departments of Mathematics and Statistics and Biology. His research focuses on spatial ecology and mathematical modeling, addressing ecological challenges such as animal movement, invasive species, and disease dynamics. Lewis earned his D.Phil. in Mathematical Biology from the University of Oxford and has been elected a Fellow of the Royal Society UK. His work integrates mathematical analysis, field studies, and interdisciplinary approaches to solve ecological problems. Current projects include modeling polar bear populations, cyanobacteria dynamics, and the impact of climate change on wildlife. Lewis supervises students across both UVic and his former University of Alberta lab. Education: D.Phil. in Mathematics (Mathematical Biology), University of Oxford Awards: Royal Society Fellowship, CRM-Fields-PIMS Prize, and Okubo Prize Key Research Areas: Animal movement modeling, aquatic ecology, wildlife disease, and invasive species management Publications highlight his contributions to understanding disease spread, parasite dynamics, and ecological responses to environmental changes. Lewis collaborates widely, applying mathematical tools to real-world conservation and health challenges.

Nina Gantertمشاهده پروفایل

استاد

• Probability Theory
• Stochastic Processes
• Large Deviations
• +۴ مورد دیگر

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.

• Pathogen Ecology
• Microbial Evolution
• Antibiotic Resistance
• +۴ مورد دیگر

Prof. Dr. Alex Hall is an Associate Professor at the Department of Environmental Systems Science and Head of the Institute of Integrative Biology at ETH Zürich , Switzerland. He holds a PhD from the University of Edinburgh (2008), followed by postdoctoral work at the University of Oxford and ETH Zürich, including prestigious SNSF Ambizione and Marie Curie Intra-European fellowships. Research Focus: The Hall lab investigates Microbial interactions in human microbiomes Antibiotic resistance evolution Horizontal gene transfer dynamics Computational and in vitro modeling of microbial communities Evolutionary medicine applications Scientific Contributions: His recent studies analyze probiotic treatments for Staphylococcus aureus decolonization, strain-specific ecological success in gut microbiomes, and CRISPR-Cas system roles in plasmid conflicts. The lab employs computational frameworks combined with experimental validations. Scientific Awards: SNSF Ambizione fellowship Marie Curie Intra-European fellowship He also serves on the SNSF PRIMA fellowship evaluation panel and the ETH Zürich Coordination Council Medicine .

• Human Evolutionary Genetics
• Population Genetics
• Ancestry Analysis
• +۳ مورد دیگر

Aylwyn Scally is a researcher at the Department of Genetics, University of Cambridge, specializing in human evolutionary genetics and ancestry. His work focuses on computational and mathematical models of genome evolution, leveraging population-scale datasets and archeogenetic evidence to explore ancient human populations and their spatial dynamics. University: University of Cambridge Department: Department of Genetics Fields of Interest: Human Evolutionary Genetics, Population Genetics, Ancestry Analysis, Paleobiology, Environmental Genomics, Genome Evolution Scally's research integrates spatial dynamics into genetic models, offering insights into demographic, social, and cultural factors in ancient populations. His methodologies have broader applications for studying other species as genomic data becomes available. Recent publications highlight his work on mutation rate analysis, historical migration patterns, and ancestral population structures. These studies often employ computational simulations and large-scale genomic datasets to address evolutionary questions. He is associated with the Cambridge NERC Doctoral Landscape Awards (CREATES) and C-CLEAR DTP, contributing to training and collaborative research in genetics and environmental genomics.

Karoline Faustمشاهده پروفایل

دانشیار

• Microbial community dynamics
• Microbial systems biology
• Bioinformatics
• +۶ مورد دیگر

Karoline Faust is an Associate Professor at KU Leuven, affiliated with the Laboratory of Molecular Bacteriology (Rega Institute) and the Faculty of Medicine . She contributes to the iSi Health and Leuven One Health institutes, and serves on senior academic councils. Her research spans microbial systems biology, focusing on community dynamics and network analysis. Education: PhD in bioinformatics (2010, KU Leuven) Affiliations: KU Leuven, ISME Journal editorial board, Belgian Society for Microbiology Her research investigates microbial community dynamics , systems biology approaches to microbiomes, and bioinformatics tool development . She specializes in modeling human gut microbiota , synthetic microbial communities , and environmental microbiomes (e.g., microplastic impacts on Daphnia microbiomes). Her work integrates metabolic modeling , network analysis , and experimental systems to understand microbial interactions. Recent publications highlight her contributions to microbial network inference , 16S rRNA sequencing protocols , microfluidics , and ecological modeling of microbiomes. She develops tools like manta , miaSim , and CoNet to analyze community structures. Teaching: Karoline co-teaches courses in microbiology, bioinformatics, and network analysis at KU Leuven, and has contributed to international workshops on microbial network inference. Scientific Engagement: She serves as Senior Editor at ISME Journal and Secretary of the Belgian Society for Microbiology .

Leslie Ann Goldbergمشاهده پروفایل

استاد

• Algorithms
• Complexity Theory
• Randomised Algorithms
• +۵ مورد دیگر

Leslie Ann Goldberg is a Senior Research Fellow at St Edmund Hall and Professor of Computer Science at the University of Oxford. She currently serves as Head of the Department of Computer Science (on sabbatical 2025-26) and focuses on foundational problems in Algorithms and Complexity Theory , particularly randomised algorithms for network communication, machine learning, and statistical physics models. Her research includes solving Aldous' 1987 conjecture on backoff protocol instability (with John Lapinskas), developing rigorous mathematical analysis frameworks for algorithmic efficiency, and advancing approximate counting techniques via Markov Chain Monte Carlo methods (with Andreas Galanis and collaborators). Key projects involve graph homomorphisms , Moran process dynamics , and #BIS complexity class analysis. Recent publications (2023-2024) span topics like Sybil defense mechanisms, low-temperature sampling on random graphs, and parameterised subgraph counting modulo 2. Her work demonstrates cross-disciplinary impact in computational biology, statistical physics, and database theory. Scientific Awards include Best Paper Prizes at ICALP 2016, ICALP 2010, and IPEC 2017. She supervises PhD student Paulina Smolarova and collaborates extensively with researchers in Oxford and beyond.

• Algorithmic Game Theory
• Concurrent Systems
• Formal Verification
• +۳ مورد دیگر

Dr. Rasmus Ibsen-Jensen is a Lecturer in Computer Science at the University of Liverpool. Previously, he held a Postdoctoral position at IST Austria under Krishnendu Chatterjee and completed his PhD under Peter Bro Miltersen. Research Focus: Algorithmic game theory, strategy complexity in two-player zero-sum games, control flow graph algorithms, edit distance for automata, and theoretical biology applications. Teaching: Module Coordinator for second-year courses in database development (COMP207), C++ programming (COMP282), and industrial placement (COMP299). His work bridges computational game theory and formal verification, with recent publications exploring memory constraints in partial-information games, algebraic path properties in concurrent systems, and evolutionary spatial dynamics. While no scientific awards are explicitly mentioned in the provided text, his contributions to algorithmic complexity and interdisciplinary research (e.g., theoretical biology) highlight his academic impact.

Nicholas Kortessisمشاهده پروفایل

استادیار

• Ecology
• Adaptation in Variable Environments
• Statistical Ecology
• +۷ مورد دیگر

Nicholas Kortessis is an Assistant Professor in the Department of Biology at Wake Forest University, within The Undergraduate College. His research lies at the intersection of ecology, evolution, and theoretical modeling, focusing on how environmental variability shapes biological diversity. Research Interests: His primary areas include statistical and theoretical ecology, adaptation in variable environments, population and community dynamics, and ecosystem modeling. He uses mathematical frameworks to simulate ecological processes across large spatial and temporal scales, bridging experimental data with predictive theory. Publication Trends: His recent work spans topics such as habitat fragmentation, disease in invasive species, character displacement, seed dormancy evolution, and pandemic transmission dynamics. These reflect a strong emphasis on theoretical and synthetic approaches to ecological problems, often involving collaboration across institutions. Scientific Awards: No awards are mentioned in the provided text. Advising and Grants: While no specific students or grants are listed, Dr. Kortessis leads an active research lab and collaborates widely, indicating ongoing mentorship and likely grant-supported research. His lab engages in theoretical and data-driven ecological studies, suggesting funding from agencies supporting environmental and theoretical biology. Labs and Teams: He runs the Kortessis Lab at Wake Forest University, which focuses on modeling ecological and evolutionary processes. The lab emphasizes mathematical and conceptual tools to explore biodiversity, coexistence, and ecosystem responses to environmental change.