Find Academic Supervisors

• Orthodontics
• Osteoclastogenesis
• Bone Biology
• +7 more

Amy W Tasca is a Clinical Associate Professor in the Department of Orthodontics at the School of Dentistry, University of Minnesota. Her work integrates clinical orthodontics with molecular and cellular bone biology, focusing on osteoclastogenesis and skeletal site-specific differences in bone remodeling. She actively leads research projects and contributes to peer-reviewed literature in both dental and biomedical sciences. Research Interests: Osteoclast differentiation and function Skeletal site-specific myeloid cell behavior Gene expression in mandibular vs. femoral osteoclast precursors Single-cell RNA sequencing in bone biology Orthodontic treatment outcomes and patient comfort Molecular mechanisms of BMP/SMAD signaling in bone The recent articles highlight a strong trend in comparative osteoclast biology between jaw and long bones, using advanced genomic techniques. Her research bridges clinical orthodontics with fundamental bone biology, contributing to both patient care and mechanistic understanding of skeletal remodeling. Scientific Awards: No awards explicitly mentioned in the text. Advising and Grants: Amy W Tasca serves as Principal Investigator on multiple funded research projects. These include: Comparison of oral health and patient comfort outcomes for Phase I Invisalign and fixed appliance patients (ALIGN TECHNOLOGY, INC, 2022–2025) Where you originate from matters; A Comparison of Jaw and Long Bone Osteoclast Precursors Using Single Cell Analysis (American Association of Orthodontists Foundation, 2022–2023) The role of MyosinX in BMPs promotion of SMAD 1/5 in ost (NIH NIDCR, 2014–2016) She has not listed any formal advisees in the provided text. Labs and Teams: Dr. Tasca collaborates closely with Dr. Kenneth Mansky and other researchers in bone biology and myeloid cell research. Her work involves single-cell analysis and molecular techniques, likely conducted within a specialized bone biology or dental research laboratory at the University of Minnesota.

• Bioinformatics
• Metagenomics
• Pathogen Discovery
• +4 more

Thomas Bigot is a researcher at the Bioinformatics and Biostatistics HUB of Institut Pasteur in Paris, France. He joined the institution in 2016 and is actively involved in the PAGE expertise group and maintains a privileged partnership with the Pathogen Discovery Laboratory. His work focuses on developing bioinformatics methods for pathogen detection from metagenomic data. Dr. Bigot holds a PhD in Bioinformatics (2013) from the University of Lyon, France, where his research focused on detecting topological patterns in phylogenetic trees. He also earned a Master's degree in Health and Populations with a specialization in Bioinformatics, Biostatistics, and Genome from Université Lyon 1 in 2009. His doctoral work led to the development of a formalism for describing tree patterns and a software suite for executing queries on thousands of phylogenetic trees. His research interests span bioinformatics, metagenomics, pathogen discovery, phylogenetics, and viral detection. As a developer proficient in Python and C++, he focuses on optimizing laboratory prototypes and creating user-friendly tools for non-specialized users. His work is particularly crucial in pandemic contexts and rapid diagnosis, enabling the referencing of pathogen sequences and identification of new pathogen-disease combinations. Analysis of his recent publications reveals a strong focus on viral detection through metagenomic approaches, particularly for emerging pathogens. His research spans multiple vector systems including ticks, mosquitoes, and bats, with applications in public health surveillance and understanding viral evolution. The 2023 publication 'Virus Pop' demonstrates his innovative approach to expanding viral databases through protein sequence simulation, addressing the 'dark matter' problem in metagenomics. Dr. Bigot actively contributes to the Bioinformatics program for PhD students at Institut Pasteur, having participated in courses from 2020 through 2024. His collaborative work spans multiple international research groups, reflecting the interdisciplinary nature of modern pathogen discovery research.

Frédéric LemoineView profile

Researcher

• Bioinformatics
• Evolutionary Bioinformatics
• Phylogenetics
• +15 more

Frédéric Lemoine is a Bioinformatics Scientist at the Institut Pasteur, affiliated with the Bioinformatics and Biostatistics Hub. He has been actively contributing to the fields of evolutionary bioinformatics, phylogenetics, and viral genomics since joining in 2015. He leads multiple research and software development projects focused on phylodynamics, respiratory virus surveillance, and bioinformatics toolkits. His research interests include phylogenetics , phylodynamics , viral evolution , genomics , algorithm development , and reproducible research . He develops tools for phylogenetic analysis (e.g., NGPhylogeny.fr, Booster, Bboot, ConDor) and applies them to monitor epidemics of influenza, RSV, and SARS-CoV-2. His work integrates computational biology with public health applications. The recent publications highlight his expertise in phylogenetic methods , viral evolution , and bioinformatics software . Trends show a strong focus on methodological innovation (Bayesian bootstrap, convergent mutation detection) and real-world applications in viral surveillance and immune escape. His work bridges algorithmic development with epidemiological impact. Active member, French Reproducibility Network Involved in PEPR Santé Numérique ShareFAIR project promoting FAIR workflows Regular instructor in bioinformatics training programs at Institut Pasteur Frédéric Lemoine leads several ongoing projects including Monitor French respiratory virus epidemics using phylodynamics methods , Accounting for defective genomes in virus consensus reconstruction , and software tools like Bboot , ConDor , and Goalign/Gotree . He has co-developed widely used platforms such as NGPhylogeny.fr and Bioconvert . He teaches courses on molecular phylogenetics, NGS data analysis, and reproducible research, contributing significantly to bioinformatics education. He is part of collaborative teams including the National Reference Center for Respiratory Viruses , Computational Biology , and the Evolutionary Bioinformatics Unit . His work is highly interdisciplinary, involving close collaboration with virologists, epidemiologists, and software developers to translate genomic data into actionable public health insights.

• Bioinformatics
• Genomics
• Microbial Ecology
• +3 more

Damien COURTINE is a Staff Scientist and Bioinformatician at the Microorganisms: Genome and Environment Laboratory (LMGE) at Clermont Auvergne University, where he has held a permanent position since December 2021. His work spans two research teams (MEB and IHP), focusing on bioinformatics analysis of microbial communities and genome analysis. Dr. COURTINE earned his PhD in Microbiology from the University of Western Brittany (2017), an MSc in Bioinformatics from Blaise Pascal University (2014), a BSc in Biology (2012), and a Technical Diploma in Biology laboratory technician work (2011). Prior to his current position, he was a Post-doctoral Fellow at the Center d'Immunologie de Marseille-Luminy (2019-2021). His research interests include bioinformatics, genomics, microbial ecology, metagenomics, and comparative genomics. Dr. COURTINE specializes in analyzing high-throughput sequencing data from microbial communities, developing genome analysis tools, and providing technical support related to sequencing methods. He works extensively with metagenomic, metatranscriptomic, and metabarcoding approaches, particularly focused on lake microorganism communities in Lake Pavin. Dr. COURTINE's publication record demonstrates expertise in microbial ecology, particularly in extremophiles, microbial eukaryotes, and bacterial communities in meromictic lakes. His work often involves comparative genomics of archaea (particularly Thermococcales), metagenomic analysis of freshwater ecosystems, and development of bioinformatics tools. Recent publications span from 2021-2025, showing consistent productivity across multiple high-impact journals. Since 2024, Dr. COURTINE has been teaching in the bioinformatics master's course at the University of Clermont Auvergne, where he instructs students in algorithms for short-read alignments using Python and the Burrow-Wheeler transform method. His technical expertise includes Linux, high-performance computing (SLURM), version control with git, SnakeMake pipelines, Docker/Singularity containers, and programming in Python, R, and BASH.

Mikael BodenView profile

Professor

• Bioinformatics
• Artificial Intelligence
• Machine Learning
• +6 more

Professor Mikael Boden is a Professor in the School of Chemistry and Molecular Biosciences at the University of Queensland, where he has been since 2003 after holding academic positions at Swedish universities. With a PhD in Computer Science from the University of Exeter, he bridges computational methods with biological research through his work at the Institute for Molecular Bioscience. His research program applies artificial intelligence, machine learning, and data science to solve complex problems in genomics and molecular biology. Key areas include transcriptional and epigenetic regulation during mammalian development, protein evolutionary relationships, and computational tool development for biological data analysis. His group uses probabilistic modeling and data analytics to integrate massive biological datasets across multiple technologies including single-cell RNA-seq and ChIP-seq. Professor Boden's scientific impact is demonstrated through publications in high-impact journals such as Science, Nature Catalysis, and Nature Communications. His research is supported by multiple grants including NHMRC Ideas grants and ARC Discovery Projects focusing on drug design, central nervous system development, autism research, and antibiotic resistance. Associate Editor of Frontiers in Genetics/Computational Biology Docent in Computer Science at Halmstad University, Sweden Ramsay Visiting Scientist Award from University of Birmingham Gastprofessorenprogramm award from Bavarian State Ministry As an educator, he serves as convener of the Bioinformatics dual major and program director of the Master of Bioinformatics. He has supervised 7 postdocs, 11 PhD and 3 MPhil graduates, and currently mentors 6 PhD students including Samuel Davis, Sanjana Tule, and Oliver Hughes. His interdisciplinary collaborations span neuroscience, developmental biology, protein engineering, and bioeconomy research.

James S. LehnertView profile

Professor

• Wireless Communication Networks
• Spread Spectrum Communications
• Signal Processing
• +5 more

James S. Lehnert is a Professor at the School of Electrical and Computer Engineering , Purdue University, where he has been since 1984. He holds a B.S., M.S., and Ph.D. from the University of Illinois at Urbana-Champaign (1978, 1981, 1984). His research focuses on spectrum management , CDMA systems , channel estimation , and spread spectrum communications . He has led projects for DARPA, NSF, and the Air Force Office of Scientific Research, collaborating with institutions like the University of Michigan and Ohio State University. He has authored numerous articles in top journals like IEEE Transactions on Communications and IEEE Journal on Selected Areas in Communications . His awards include the IEEE MILCOM Lifetime Achievement Award (2009) and recognition as a Highly Cited Researcher (2000-2010). He is also a Fellow of the IEEE for contributions to spread-spectrum communications. Dr. Lehnert has advised over 30 graduate students, many of whom now hold prominent roles in academia and industry. He teaches advanced courses such as ECE544: Digital Communications and ECE639: Error Control Coding . His research group operates the Spread Spectrum and Satellite Communications Research Laboratory (S3CRL).

Sebastian WillView profile

Professor

• Computational RNA structure prediction
• RNA-RNA interactions
• Folding dynamics
• +3 more

Sebastian Will is a Full Professor of Bioinformatics at École Polytechnique IP Paris since 2020. Previously held positions include: Researcher with Ivo Hofacker at TBI, University of Vienna Researcher with Peter Stadler at Bioinformatics group, University of Leipzig Akademischer Rat at Bioinformatics group, University of Freiburg (2005-2012) Postdoc with Bonnie Berger at MIT's CSAIL (2010-2011) His research focuses on: RNA structure prediction algorithms Pseudoknot modeling RNA-RNA interaction analysis Structure design with Infrared framework Multi-target RNA design Integration of experimental data Ensemble-based sparsification Publication trends show concentrated research in: RNA structure prediction techniques Algorithm development Dynamic programming optimization Tree decomposition applications Stochastic sampling methods Multi-objective design Contributed extensively to software development including: LocARNA 2.0 Infrared framework SparseMFEFold BiAlign RNAPOND Pankov LocARNA-P

Laurence Mylène BrandenbergerView profile

Researcher

• Legislative Behavior
• Parliamentary Networks
• Social Influence in Politics
• +5 more

Laurence Mylène Brandenberger is a Postdoctoral Researcher at the Department of Political Science, University of Zurich, specializing in legislative behavior and parliamentary networks. Their research examines the intersection of social relations and political decision-making, with a focus on systemic spill-over effects in policy networks and enhancing democratic transparency through projects like the DemocraSci Knowledge Graph. Current focus on temporal reciprocity in congressional collaborations Developing computational tools (embed2discover, Data2neo) for policy network analysis Recipient of SNF and SDSC grants for political performance and advocacy studies Teaching course: The Politics of Influence: Interest Groups, Lobbying, and Political Advocacy (2025) Their work bridges network science and political decision-making, utilizing large-scale datasets spanning decades and multiple policy sectors. Laurence applies causal network analysis to unravel dependencies in political systems and advocates for citizen-oriented platforms to reverse electoral decline and enhance civic engagement. Prior research includes quantifying triadic closure in political networks, studying cross-continental policy networks, and analyzing conflict event data through relational event models. Their methodological contributions in dictionary-based content analysis and multi-edge network modeling have advanced empirical approaches in political science. SNF Grant (2024): Measuring Political Performance of Swiss MPs SDSC Grant (2025): Studying Political Advocacy As part of the Institute of Political Science at the Faculty of Philosophy, Laurence actively contributes to computational infrastructure development and open science initiatives aimed at improving policy transparency and reducing polarization in Western democracies.

Markus MaucherView profile

Researcher

• Computational Biology
• Bioinformatics
• Machine Learning
• +4 more

Markus Maucher is a Subject Advisor in the Department of Computer Science at the University of Ulm . He has taught exercises for courses like Einführung in die Informatik I (EidI 1) and Einführung in die Informatik II (EidI 2) across multiple semesters from 2004 to 2022. His research focuses on Computational Biology , Boolean Networks , and Ant Colony Optimization , with applications in Machine Learning , Gene Expression Analysis , and Evolutionary Algorithms . His publications span journals such as Bioinformatics , IEEE/ACM Transactions on Computational Biology and Bioinformatics , and Computational Statistics , as well as conferences like the Genetic and Evolutionary Computation Conference . He holds a PhD in Computer Science, evidenced by his 2009 dissertation and subsequent book on non-perfect randomness in probabilistic algorithms . Maucher has collaborated with researchers including H.A. Kestler , U. Schöning , and C. Müssel . The keywords from his recent work include Computational Biology , Boolean Networks , and Algorithm Design . His sub-fields encompass Probabilistic Algorithms , Correlation Analysis , and Feature Selection . Contact details: markus.maucher@uni-ulm.de

Shawn W. PolsonView profile

Professor

• Bioinformatics
• Computational Biology
• Viral Metagenomics
• +7 more

Shawn W. Polson is a Professor in the Department of Computer & Information Sciences, Department of Plant & Soil Sciences, and Department of Biological Sciences at the University of Delaware. He serves as Associate Director of the Center for Bioinformatics and Computational Biology (CBCB), Director of the Bioinformatics Data Science Core Facility, and Director of the Data Science Core for Delaware INBRE. He is also Co-director of the CBB T32 Predoctoral Training Program and affiliated with multiple institutes including the Data Science Institute and the Delaware Environmental Institute. Dr. Polson earned his B.S. in Biology (Cell & Molecular) and Computer Science from the University of South Carolina Aiken, followed by an M.S. in Microbiology & Molecular Medicine from Clemson University, and a Ph.D. in Molecular & Cellular Biology & Pathobiology from the Medical University of South Carolina. He completed postdoctoral training in viral metagenomics at the University of Delaware. His research lies at the intersection of genomics and microbial ecology, focusing on how microorganisms and viruses interact with their environments—especially marine, soil, and extreme environments like hydrothermal vents. His work specializes in bioinformatics solutions for analyzing complex microbial community data. Current projects include studying viral infection dynamics, connecting genotype to phenotype in microbial viruses, optimizing biopharma manufacturing using omics, and developing the VIROME and MgOl platforms for viral and metagenomic data analysis. His recent publications highlight a strong emphasis on marine virology, metagenomics, microbial ecology, and bioinformatics tool development. Themes include viral diversity, gene annotation, microbial community dynamics, and environmental genomics across marine, soil, and engineered systems. Scientific awards include: Delaware Biotechnology Institute Symposium, Best Scientific Talk (May 2010) Sigma Xi Research Award (November 2006) Estuarine Research Federation Travel Award (October 2005) NOAA National Ocean Service Certificate of Achievement (July 2004) Dr. Polson has advised numerous students and researchers, including Daniel Nasko, Rachel Keown, Jessica Chopyk, and Eric Sakowski. He has received significant grant funding from the National Science Foundation, Gordon and Betty Moore Foundation, USDA, and NIH for projects such as VIROME, which supports viral metagenome analysis. He is actively involved in professional societies including the American Society for Microbiology, Association of Biomolecular Resource Facilities, and Sigma Xi. He leads the CBCB Bioinformatics Core, which provides scientific expertise and infrastructure support in bioinformatics and computational biology for researchers across Delaware. He also co-developed the VIROME platform, a key resource for viral metagenome exploration that enables classification of unknown viral sequences and supports global research in viral dark matter.

Shannon StraubView profile

Associate Professor

• Plant Systematics
• Phylogenomics
• Genome Evolution
• +7 more

Shannon Straub is an Associate Professor of Biology at Hobart and William Smith Colleges, where she also serves as Co-Chair of the Biochemistry program and Chair of the Biology Department. She joined the faculty in 2014 and is based in Eaton Hall. She earned her Ph.D. from Cornell University and her B.A. from the University of Colorado. Institution: Hobart and William Smith Colleges School: School of Sciences Department: Department of Biology Position: Associate Professor, Co-Chair (Biochemistry), Chair (Biology) Her research lies at the intersection of plant systematics, phylogenomics, and genome evolution, with a primary focus on the milkweed and dogbane family (Apocynaceae). She investigates evolutionary relationships across multiple scales—from species diversification in Asclepias to deep phylogenetic patterns across the family—using hundreds of nuclear genes and whole chloroplast genomes. A key interest is the evolution of pyrrolizidine alkaloid biosynthesis, a chemical defense pathway, and how genomic data can inform ecological and evolutionary hypotheses such as defense de-escalation. Her recent publications highlight methodological innovations (e.g., Hyb-Seq, indel coding pipelines) and large-scale genomic resources (e.g., a draft genome for Asclepias syriaca ). These works span leading journals like American Journal of Botany , PeerJ , and New Phytologist , reflecting interdisciplinary contributions to molecular evolution, bioinformatics, and plant systematics. American Society of Plant Taxonomists Botanical Society of America Society of Systematic Biologists She teaches foundational and advanced courses including BIOL 167 (Plants & People), BIOL 220 (General Genetics), BIOL 228 (The Biology of Plants), BIOL 380 (Genomics), and BIOL 460 (Senior Seminar - Genome Collisions). Her teaching integrates molecular techniques with evolutionary theory and emphasizes student engagement in genomic research. There are no listed students or awards in the provided text, but her leadership roles suggest active mentorship and departmental service. Her research lab generates genomic and transcriptomic datasets that support both her own studies and collaborative efforts in plant evolutionary biology. She is actively involved in advancing phylogenomic methods and applying them to resolve complex evolutionary histories in plants.

Scott C. SchmidlerView profile

Associate Professor

• Computational Biology
• Bioinformatics
• Statistical Science
• +12 more

Scott C. Schmidler is an Associate Professor in the Department of Statistical Science and Computer Science at Duke University, affiliated with the Duke Center for Systems Biology. His research lies at the intersection of statistics, computer science, and molecular biology, focusing on the development of probabilistic and computational methods for understanding biological systems. Department of Statistical Science, Duke University Department of Computer Science, Duke University Duke Center for Systems Biology Dr. Schmidler's research interests include Monte Carlo simulation, Markov chain convergence, shape analysis, structural biology, and biophysics. He develops statistical models and algorithms to study protein folding, molecular simulation, and systems biology. His work integrates geometric and stochastic methods to model complex biological data, particularly in the context of structural alignment and evolutionary modeling. His recent publications and talks reflect a strong focus on convergence diagnostics in MCMC, adaptive sampling methods in molecular simulations, Bayesian inference, and the statistical challenges in modeling biomolecular systems. The articles span topics from theoretical foundations of Markov chains to practical applications in vaccine design and protein evolution. He has served as Associate Editor for the Annals of Applied Statistics and as Program Coordinator for the Master's program in Statistical Science at Duke. He has co-organized several major workshops, including events at BIRS and SAMSI, indicating active leadership in the statistical and computational biology communities. Co-organizer, BIRS Workshop on Advances in Scalable Bayesian Computation (2014) Co-organizer, SAMSI Workshop on Molecular Motors, Neuron Models, and Epidemics on Networks (2010) Associate Editor, Annals of Applied Statistics (2009–present) Program Coordinator, Master's in Statistical Science Dr. Schmidler advises students and postdoctoral researchers in computational biology and statistical science. While specific names are not listed, his group is involved in cutting-edge research at the interface of statistics and molecular biology. He has secured participation in major collaborative programs such as SAMSI’s Stochastic Dynamics program, reflecting external recognition and funding support for his work. He is involved in several research teams and centers, including the Duke Center for Systems Biology, and has contributed to interdisciplinary collaborations in enhanced sampling methods, Bayesian computation, and network-based biological modeling. His ongoing work continues to advance the statistical foundations of molecular simulation and systems biology.

Eric TorngView profile

Associate Professor

• Algorithms
• Online Algorithms
• Scheduling
• +4 more

Eric Torng is an Associate Professor in the Department of Computer Science and Engineering (CSE) at Michigan State University (MSU), serving as Associate Chair for Research and Faculty Development in CSE and Associate Dean of MSU's Graduate School. He holds a Ph.D. from Stanford University (1994) and has received awards including the NSF CAREER Award (1997) and multiple teaching excellence awards. His research focuses on algorithms, online algorithms, scheduling, perimeter defense strategies, and packet processing. Notable contributions include multi-vehicle perimeter defense systems, fast packet classification techniques (e.g., TupleMerge), and algorithmic approaches to resource optimization. Dr. Torng has authored over 100 publications and secured over $2 million in external grants. His work bridges theoretical computer science with practical applications in networking, robotics, and distributed systems.

• Computer Science
• Computational Linguistics
• Environmental Science
• +3 more

Weihong Zhong is an active researcher with dual expertise in Computer Science (particularly large language models and controllable text generation) and Environmental Science (focusing on biodegradation of industrial pollutants like phthalate esters and plastic waste). Their work includes methodological innovations in ACL and EMNLP venues, as well as biochemical studies in Applied and Environmental Microbiology and Synthetic and Systems Biotechnology . Key collaborators include Xiaocheng Feng , Lei Huang , and Bing Qin , with whom they co-author multiple papers across NLP and environmental research. Weihong Zhong’s computational research addresses LLM hallucinations (via frameworks like RHIO, Seal, and FRONT), context window extension (through positional encoding optimization), and controllable generation (using latent space probability density estimation). In environmental science, their work focuses on degrading phthalate esters (PAEs) and plastic pollutants using bacterial consortia and enzymatic engineering. Papers like the 2024 GroundBench study and 2023 MMHalSnowball framework highlight their contributions to multimodal hallucination mitigation. Scientific awards or honors are not explicitly documented in the provided materials. Their interdisciplinary approach bridges technical innovation in AI/ML with applied biological solutions for environmental remediation, as evidenced by publications in both top-tier computational conferences and environmental journals .

• School Libraries
• Instructional Design
• Information Literacy
• +6 more

Beatrice C. Baaden is an Associate Professor and Director of the School Library Media Program at the Palmer School of Library and Information Science, part of Long Island University’s College of Education, Information and Technology. With over 35 years of experience in education, including 27 years as a school library media specialist, she transitioned into higher education after retiring from Plainedge Public Schools in 2002. Her research and expertise lie in school libraries, instructional design, information literacy, and mentoring . She has designed and implemented a blended and fully online school library media program, contributing significantly to modern librarian education. Her work has been featured in publications such as Curriculum Partner and an ALA video on the future of school libraries. The publications and presentations of Dr. Baaden reflect a consistent focus on professional development, curriculum integration, and equitable access to information . Her work bridges theory and practice, emphasizing mentoring, technology integration in under-resourced environments, and alignment with national standards. Themes across her scholarship include 21st-century learning, differentiated instruction, and the evolving role of school librarians. Scientific Awards: David Newton Award for Teaching Excellence, Long Island University (2009) Advising and Grants: While specific advisees and grants are not listed, Dr. Baaden has guided the development of graduate-level resources, including a manual for the Content Specialty Test and a professional portfolio guide for library media specialists. She actively mentors future librarians through curriculum design and leadership in her program. Labs, Teams, and Affiliations: Dr. Baaden serves on the advisory boards of multiple BOCES School Library Systems (Nassau, Eastern Suffolk, Western Suffolk). She is a member of the New York Library Association, American Association of School Librarians, American Library Association, Association of Supervision and Curriculum Development, and the Governor’s Council for Universal Broadband Digital Literacy.