Find Academic Supervisors

• Assessment Practices
• Curriculum Design
• Work-Integrated Learning
• +2 more

Geraldine O'Neill is an Associate Professor in Educational Development at University College Dublin's Teaching and Learning unit, holding Principal Fellowship status with Advance HE. Her research focuses on assessment innovation, curriculum design, and work-integrated learning in higher education. Qualifications include a PhD in Occupational Therapy, Postgraduate Diploma in Professional Studies in Higher Education, and Diploma in Statistics. She coordinates Ireland's National Forum for Teaching and Learning assessment enhancement theme, emphasizing student-centered approaches. Research examines diversifying assessment methods, program-focused curriculum sequencing, and reflective practices in professional education. Awarded the 2020 National Teaching Fellowship for work on assessing work-integrated learning. Recent publications explore authentic assessment barriers and curriculum engagement strategies. Leadership roles include directing UCD's Professional Diploma in University Teaching and developing Ireland's National Professional Development Framework. She serves on multiple national committees including UMT EDI Group and Academic Integrity Working Group.

• Genetics
• Molecular Biology
• Cancer Research
• +3 more

Chih-Lin Hsieh is a Professor of Urology and holds the Catherine and Joseph Aresty Chair in Urologic Research at the University of Southern California. His research focuses on molecular mechanisms underlying cancer, particularly prostate cancer, and epigenetic regulation involving DNA methylation, chromosomal instability, and genetic recombination. He leads studies on immunoglobulin class switch recombination, R-loop formation, and the role of CpG dinucleotides in genomic stability. Hsieh has contributed to international consortia analyzing prostate cancer genetics and developing computational tools like REVEL for pathogenic variant prediction. His work bridges basic molecular biology with clinical applications in cancer and immunology. Research interests include: Genetic and epigenetic drivers of cancer Prostate cancer susceptibility genes Immune system regulation via DNA/RNA interactions Chromosomal translocation mechanisms Publications highlight his expertise in Molecular Cell Biology , Genetics , and Prostate Cancer Research , with a focus on translating molecular findings into diagnostic and therapeutic strategies.

Knut ReinertView profile

Professor

• Algorithmic Bioinformatics
• Genomics
• Proteomics
• +3 more

Prof. Knut Reinert is a Professor of Algorithmic Bioinformatics at the Freie Universität Berlin (FU) and a Max Planck Fellow at the Max Planck Institute for Molecular Genetics (MPI). He leads the Algorithmic Bioinformatics (ABI) group at FU and the Efficient Algorithms for Omics Data group at MPI. His research focuses on developing mathematical models and algorithms for analyzing biomedical mass data, including sequence analysis, proteomics, and omics data. Reinert is a key contributor to the SeqAn C++ library, a widely used bioinformatics software tool, and has led initiatives such as the Intel® Parallel Computing Center to accelerate NGS data analysis. Education: Diploma in Computer Science (1994, Max Planck Institute for Computer Science & Universität des Saarlandes), PhD (1999, Dr. Ing., Universität des Saarlandes). Postdoctoral research at Celera Genomics (1999–2002). Research interests include algorithm engineering for genome comparison, high-throughput sequencing data analysis, and bioinformatics software development. His work emphasizes scalable solutions for omics data interpretation, with applications in metagenomics, proteomics, and computational biology. Key achievements include leadership in de.NBI (German Network for Bioinformatics Infrastructure), the development of tools like SeqAn, Lambda, Fiona, and Ganon, and collaborations with institutions like the Max Planck Society and international partners. Awards include Max Planck Fellow status and Intel® PCC leadership. Grants and collaborations: German-Turkish research initiatives, DFG-funded RNA research projects, and leadership in EU-funded projects like Predict-IV. His lab actively engages in teaching at undergraduate and graduate levels, emphasizing innovative methods like e-learning and inverted classrooms.

Matt PennellView profile

Associate Professor

• Macroevolution
• Phylogenetics
• Computational Biology
• +3 more

Matt Pennell is an Associate Professor at the University of Southern California (USC) in the Department of Quantitative and Computational Biology and Biological Sciences, affiliated with the USC Dornsife College of Letters, Arts and Sciences. His research focuses on macroevolutionary processes, phylogenetic methods, and computational biology. Pennell holds a B.Sc. in Biological Sciences from Simon Fraser University (2010). He has made significant contributions to understanding evolutionary diversification, genomic innovation, and the integration of phylogenetic and functional data. Key research themes include the evolution of gene families, genomic architecture, and the application of statistical methods to phylogenetics and macroevolution. His work bridges theoretical models with empirical genomic datasets, addressing questions about biodiversity patterns and the drivers of evolutionary change. Notable contributions include tools like CloseRead for genomic assembly analysis and foundational studies on yeast metabolic innovation. Pennell has been recognized with the Joseph Felsenstein Award (2014) for contributions to phylogenetic methodology. His recent research emphasizes the interplay between genomic evolution and ecological adaptation, particularly in vertebrates and microbial systems. Collaborative efforts, such as the ruminant genome consortium, highlight his commitment to large-scale genomic projects. His publications reflect expertise in phylogenetic comparative methods, diversification rate analyses, and the application of computational tools to evolutionary problems. Current work explores macroevolutionary dynamics, functional trait evolution, and the scalability of phylogenetic models to large datasets.

Gaël RichardView profile

Professor

• Audio Signal Processing
• Speech Synthesis
• Source Separation
• +5 more

Gaël Richard is a Professor at Télécom Paris, part of the Institut polytechnique de Paris. He leads the Signal, Statistics and Learning (S²A) research group within the LTCI laboratory and is the Executive Director of Hi! Paris, a hub for AI and data science. His primary research focuses on audio signal processing, including speech synthesis, source separation, and non-negative matrix factorization techniques. He has contributed significantly to applications in automotive and music industries, and his work has been recognized with the 2020 IMT-Académie des Sciences Grand Prix and a 2022 ERC Advanced Grant for the HI-Audio project. Education and Career: Gaël Richard transitioned from classical music to applied mathematics, earning a PhD in speech synthesis. His academic journey blends technical expertise with creative problem-solving, leading to impactful contributions in machine learning and audio technologies. Research Interests: His work spans machine learning for audio signals, including speech synthesis, sound separation, and music information retrieval. He emphasizes reproducibility, publishing tools like YAAFE and databases widely used in the field. Key Projects: The HI-Audio project explores AI-driven audio processing, while his ERC grant supports advancements in hybrid deep learning for audio. He co-supervises PhD students in areas like intelligibility in noisy environments and EEG-based source separation. Awards and Recognition: In addition to major grants and the IMT-Académie des Sciences prize, his work on source separation and audio indexing has earned international acclaim. He actively contributes to academic conferences and serves on editorial boards. Labs and Teams: He leads the S²A team at LTCI, fostering collaborations between academia and industry partners like Thales and Deezer. His research bridges theoretical advancements with practical applications in audio technology.

• Music Psychology
• Well-being
• Music Education
• +4 more

Amanda E. Krause is a researcher at James Cook University , with a focus on music psychology , well-being , and educational practices . Her work explores how music influences self-compassion , identity construction , and mental health , particularly in maternal care and aging populations . She collaborates extensively with scholars in psychology , music education , and cross-cultural studies . Research Interests : Musical identity and self-concept Music listening and well-being Statistics pedagogy in higher education Perinatal maternal health through music Music and social-emotional development Radio as a social surrogate for older adults Recent Article Trends : 2025 studies examine identity theory , cross-cultural music engagement , and podcasting for maternal well-being . 2024 work includes analyses of pandemic playlists , choral singing in asylum contexts , and statistics teaching innovations . Her research often employs qualitative methods and behavioral analysis to understand music's role in emotional regulation and social connection . Collaborations : Key partnerships with Jane W. Davidson , Katrina Skewes McFerran , and Adrian C. North . Contributions to Music & Science , Psychology of Music , and interdisciplinary conferences like ICMPC and ESCOM . Participation in Public Communication of Science and Technology and TropiQ Research Symposium .

Yiorgos-Sokratis SmyrlisView profile

Professor

• Conservation Laws
• Numerical methods for elliptic boundary value problems
• Density results with linear combinations of particular solutions of elliptic equations
• +2 more

Yiorgos-Sokratis Smyrlis is a Professor in the Department of Mathematics and Statistics at the University of Cyprus, where he has served since 1993, progressing from Assistant Professor to Associate Professor (2003) and finally to Professor (2010). His academic career includes prior positions as Research Assistant Professor at UCLA (1989-91) and Lecturer at the University of Manchester (1991-93). Professor Smyrlis received his secondary education at Model School of Anavruta, Kifissia, Greece (1977-1980), followed by undergraduate studies at the University of Athens, Department of Mathematics (1980-84), where he ranked 1st with a grade of 9.7/10.0. He earned his MS (1986) and Ph.D. (1989) in Mathematics from the Courant Institute, New York University, with a dissertation titled "Existence and stability of stationary profiles of the LW scheme" under Peter D. Lax. His research focuses on Conservation Laws, Numerical methods for elliptic boundary value problems, Density results with linear combinations of particular solutions of elliptic equations, Dissipative and dispersive–dissipative dynamical systems, and Development of linearly implicit schemes for nonlinear parabolic equations. His work often centers on the Method of Fundamental Solutions (MFS) and its theoretical foundations and practical applications. Analysis of his publication record reveals a strong emphasis on developing and analyzing numerical methods, particularly the MFS, for solving partial differential equations across diverse physical contexts. His research spans theoretical mathematical analysis to practical computational implementations, with significant contributions to understanding the Kuramoto-Sivashinsky equation and related dynamical systems. Professor Smyrlis has maintained extensive collaborations, particularly with A. Karageorghis, G. Akrivis, and D.T. Papageorgiou, resulting in publications in prestigious journals including Mathematics of Computation, Numerische Mathematik, and SIAM Journal on Scientific Computing.

Shira VielView profile

Associate Professor

• Mathematics Education
• STEM Education
• Diversity and Inclusion in STEM
• +3 more

Shira Viel is an Associate Professor of the Practice of Mathematics at Duke University since 2025. Her work focuses on introductory undergraduate mathematics education , with emphasis on classroom community dynamics , graduate teaching training , and equitable assessment policies . She serves on the Math Teaching Committee and Math Diversity, Equity, and Inclusion Team at Duke. Research Interests include: Undergraduate STEM student sense of belonging Diversity, Equity, and Inclusion in calculus sequences Graduate student teaching professional development Algebraic combinatorics (prior work) Recent Publications explore classroom community in quantitative courses, DEI implementation challenges, and assessment reform. Articles span 2016-2025 with focus areas in STEM education , inclusive pedagogy , and algebraic structures . Awards & Grants : NSF Award #2201486 (2023-0069 IRB Protocol) David L. Paletz Innovative Course Enhancements Grant (2024) Teaching for Equity Fellowship (2020-2021) Active Learning Faculty Fellowship (2019) Mentoring Activities include: Serving as SPIRE mentor (2020-present) AWM mentor (2019-present) Math Alliance Undergraduate Mentor (2020-present) Outreach initiatives involve organizing Duke Math Circles , speaking at Math Invitational for Girls , and leading workshops at FEMMES Capstone and Sonia Kovalevsky Day events.

Niraj KhareView profile

Academic

• Graph Theory
• Hypergraphs
• Combinatorics
• +4 more

Niraj Khare is an Associate Teaching Professor in the Department of Mathematics at Carnegie Mellon University Qatar, part of the Mellon College of Science. He holds a Ph.D. from Ohio State University. His research focuses on graph theory, hypergraphs, combinatorics, and permutation statistics, with emphasis on matching theory, extremal graph properties, and combinatorial enumeration. His work includes studies on Erdős–Gallai edge bounds, Gončarov polynomials, and structural analysis of hypergraphs. Khare's academic contributions span theoretical and applied combinatorics, with notable publications on permutation statistics, hypergraph size analysis, and edge partitioning in graphs. His teaching role emphasizes mathematics education at the university level. He can be contacted at nkhare@cmu.edu and is located in Office 2194 at CMU Qatar's Education City campus.

Mario dos ReisView profile

Associate Professor

• Phylogenetics
• Molecular Evolution
• Genomics
• +2 more

Mario dos Reis is Reader in Statistical Phylogenetics at Queen Mary University of London's School of Biological and Behavioural Sciences. He develops Bayesian methods for molecular dating, phylogenomics, and protein evolution analysis. His research integrates genomic data to reconstruct evolutionary timelines and measure natural selection. Dr. dos Reis maintains the bppr R package for phylogenetic analysis and leads projects on mammal evolution timelines and mutation rate estimation. Current research explores phylogenomic dating methods using multi-locus datasets and Bayesian approaches.

Andres MasegosaView profile

Associate Professor

• Machine Learning
• Bayesian Networks
• Data Streaming
• +4 more

Andres Masegosa is an Associate Professor at the Department of Computer Science, Aalborg University (AAU), within The Technical Faculty of IT and Design. He is actively involved in the DarkScience project (2022–present), focusing on metagenomic binning and microbial dark matter analysis. His research interests span Bayesian networks, machine learning, probabilistic graphical models, and educational methodologies in computer science instruction. Key research contributions include advancements in PAC-Bayes theory, genome representation learning, and cold posterior effects in Bayesian models. He has published extensively in top venues like Advances in Neural Information Processing Systems and Transactions on Machine Learning Research. His work often bridges theoretical contributions with practical applications in genomics and education. Masegosa leads the development of tools like InferPy for probabilistic modeling and has contributed to open-source projects such as the AMIDST toolbox. His educational research explores learning styles and active learning strategies, emphasizing live coding and programming exercises. Collaborations include interdisciplinary projects with microbiologists and data scientists, reflecting his expertise in computational methods for complex biological systems. His research portfolio demonstrates a strong focus on scalable probabilistic methods and their real-world applications.

Heather ReadView profile

Professor

• Sensory Neuroscience
• Sound Perception
• Auditory Processing
• +3 more

Heather Read is a Professor at the University of Connecticut's Department of Psychological Sciences, where she leads research in sensory neuroscience and auditory processing. Her work investigates how mammals perceive sound frequency, shape, and rhythm, with implications for understanding cortical developmental disorders like dyslexia and autism. She directs the Read Lab, focusing on neural mechanisms from single neurons to behavior, aiming to develop innovative diagnostic tools and prosthetic hearing devices. Research spans neurobiology of sound perception, including: Neural circuit anatomy underlying auditory processing Perceptual deficits in developmental disorders Computational models of natural sound encoding Novel neurotechnologies for auditory rehabilitation Her publications (2018-2024) demonstrate evolving focus: earlier work established thalamocortical auditory pathways and neural coding principles, while recent research emphasizes closed-loop neuromodulation systems, wearable EEG technology, and translational applications for hearing disorders. Studies consistently integrate neurophysiological recordings, computational modeling, and behavioral analysis across species. Awards and honors include: Kavli Frontiers Fellow (National Academy of Science) Schmitt Dissertation Award Marine Biological Laboratories Undergraduate Fellowship Graduate Merit Fellowship She teaches undergraduate courses in Sensation/Perception (PSYC 3501) and Sensory Neuroscience Lab (PSYC 3253). Contact: heather.read@uconn.edu | Office: Bousfield 114, Storrs Campus.

• Statistical Physics
• Critical Phenomena
• Combinatorics
• +3 more

Jesus Salas Martinez is an Associate Professor and Deputy Director of the Gregorio Millan Barbany Institute in the Department of Mathematics at Carlos III University of Madrid. His research focuses on statistical mechanics, critical phenomena, and combinatorial algorithms. Dr. Salas Martinez investigates phase transitions in lattice models including Potts and Ising systems, develops Monte Carlo algorithms, and analyzes universality classes in critical systems. His work bridges mathematical physics, combinatorics, and computational methods. His publications demonstrate consistent focus on finite-size scaling corrections, ergodicity properties of algorithms, and exact solutions in statistical mechanical models.

James YorkeView profile

Professor

• Chaos Theory
• Nonlinear Dynamics
• Fractal Structures
• +3 more

James Yorke is a Distinguished University Research Professor at the University of Maryland College Park, affiliated with the Department of Mathematics and the Institute for Physical Science and Technology (IPST). His academic career spans over five decades, during which he co-founded Chaos Theory and made seminal contributions to nonlinear dynamics and complex systems. Education: Ph.D. from the University of Maryland in 1969. Leadership: Director of IPST (1985–2001), Chair of the Mathematics Department (2007–2013). Yorke’s research focuses on Chaos Theory, nonlinear dynamics, fractal structures, and genome assembly. His work has profoundly impacted mathematics, physics, and computational biology. His publications include foundational papers on chaos control, embedding theory, and genomic data assimilation, with high citations in both pure and applied sciences. Notable scientific awards include the 2003 Japan Prize (shared with Benoit Mandelbrot), SIAM’s Jurgen Moser Award (2011), and Fellowships from the American Mathematical Society and SIAM. He has supervised 50 Ph.D. students and collaborated extensively with European researchers.

• Molecular genetics
• Genetics of psychiatric diseases
• Genomic medicine
• +3 more

Markus Nöthen is a distinguished German geneticist serving as Full Professor and Director of the Institute of Human Genetics at the University Hospital Bonn, University of Bonn since 2008. Previously, he held professorships at the University of Bonn (2004-2008) and University of Antwerp in Belgium (2001-2004). His academic career spans over three decades with significant contributions to medical genetics. Nöthen's research focuses on the genetic mechanisms of multifactorial diseases, with particular emphasis on psychiatric disorders, hair development disorders, and congenital malformations. His work integrates formal genetic studies with large-scale molecular genetic approaches to identify disease-associated genes at the molecular level. This has led to the discovery of numerous disease-associated genes and a more comprehensive understanding of complex genetic architectures. His research group employs bioinformatic and functional methods to further characterize disease mechanisms following gene identification. His publication record is exceptionally prolific, with over 800 scientific publications including numerous milestone papers in elucidating the genetic basis of diseases. In the 2018 Laborjournal ranking for Human Genetics researchers in Germany/Austria/Switzerland, Nöthen was ranked #1. His research has been supported by diverse funding bodies including the EU, DFG, BMBF, and FWO. Nöthen has received several prestigious honors including membership in the German National Academy of Sciences Leopoldina since 2009, the Hermann Emminghausen-Price (2009), Bennigsen-Foerder-Price of North Rhine-Westphalia (1999), and Weitbrecht-Price for Research in Psychiatry (1993). His work demonstrates a consistent trajectory of advancing genetic understanding of complex diseases through innovative methodologies and large-scale collaborative studies, with particular impact in the fields of psychiatric genetics, dermatogenetics, and craniofacial development disorders.