Find Academic Supervisors

Steven M. GoodreauView profile

Professor

• Biocultural Anthropology
• Global Health
• Medical Anthropology
• +10 more

Steven M. Goodreau is a Professor in the Department of Anthropology at the University of Washington, Seattle, with an additional appointment as Adjunct Professor in the Department of Epidemiology. He serves as the Development Core Director at the Center for Studies in Demography and Ecology (CSDE) and is affiliated with multiple research centers including the Center for AIDS and STD/Center for AIDS Research, the Center for Statistics and the Social Sciences, the eScience Institute, and the Quantitative Ecology and Resource Management program. His research focuses on human infectious disease ecology, particularly HIV transmission dynamics among sexual and gender minorities. His expertise spans social network analysis, exponential random graph models, epidemic modeling, and agent-based modeling. Dr. Goodreau's work examines sexual networks among gay and bisexual men, HIV disparities, pre-exposure prophylaxis (PrEP), sexual behavior patterns, and the intersection of viral evolution with social structure. His recent publications demonstrate a strong emphasis on mathematical modeling of HIV transmission, vaccine impacts, and prevention strategies. His work often addresses the complex interplay between sexual network structures and disease spread, with particular attention to men who have sex with men (MSM) populations. His influential software packages include statnet and EpiModel, which are widely used for network and epidemic modeling. Dr. Goodreau leads several research teams including statnet, EpiModel, CAMP (Coalition for Applied Modeling Project), and EvoNetHIV, contributing significantly to methodological advances in network-based epidemiological research. His work bridges anthropology, epidemiology, and computational modeling to address critical questions in infectious disease dynamics.

Tom FosterView profile

Professor

• Metamorphic Petrology
• Tectonics
• Solid Earth Geology
• +6 more

Tom Foster is a Professor in the Department of Earth & Environmental Sciences at the University of Iowa , where he has held academic positions since 19712. His research focuses on metamorphic petrology , high-temperature reaction kinetics , computer modeling of geological processes , and Proterozoic tectonics . He has also contributed to interdisciplinary projects in planetary geology and geoinformatics . Education: Ph.D. and M.A. in Geology, Johns Hopkins University B.S. in Geology, University of California, Santa Barbara His research integrates thermodynamic modeling with field studies to understand metamorphic processes, mineral assemblages, and tectonic evolution. Recent work spans 3D metamorphic textures , contact aureole dynamics , and geochemical databases like NMITA for Neogene marine biota. Key trends in his 15 most recent publications (2010–1999) include: Metamorphic reaction kinetics using computer simulations Proterozoic tectonic modeling in Colorado and Greenland Fluid infiltration processes in metamorphic rocks Planetary geology and Mars mission data analysis Geochemical databases for fossil biodiversity Scientific Awards: Fellow, Geological Society of America Fellow, Mineralogical Society of America GSA Best Poster Award (1997) Foster has supervised 12 Ph.D. and M.S. students , including Elizabeth Goeke, Claudia Sartini-Rideout, and Alessandro Moretti. He has also advised visiting scholars from institutions in Switzerland, Italy, and Germany. His collaborative work extends to interdisciplinary projects in informatics and planetary exploration .

• Surgical Data Science
• 3D Computer Vision
• Medical Imaging
• +3 more

Lennart Bastian is a PhD Student at the Chair of Computer Aided Medical Procedures (Prof. Navab) at Technische Universität München . His research focuses on Surgical Data Science , 3D Computer Vision , and Medical Imaging , with specific interests in 3D Reconstruction , Pointcloud Segmentation , and Scene Understanding . His recent work includes advancements in Operating Room semantics , holistic face anonymization , and scalable statistical shape modeling . Across 2025, his publications demonstrate strong engagement with topological neural networks , SO(3) forecasting , and 3D shape matching algorithms for medical applications. Lennart has supervised numerous student projects, including Learning Robust Deformation Energies Neural Interpolation for Dynamic 6D Pose Weakly Supervised Segmentation in collaboration with the Chair of Computer Science Applications in Medicine.

Laura PalagiView profile

Professor

• Nonlinear Optimization
• Mixed Integer Nonlinear Programming
• Semidefinite Programming
• +7 more

Laura Palagi is a Full Professor at Sapienza University of Rome, Department of Computer, Automation, and Management Engineering "Antonio Ruberti". She has been with the institution since 1996, progressing from Researcher to Associate Professor in 2005, and Full Professor since March 2020. She currently serves as Coordinator of the PhD program in Automatic Control, Bioengineering and Operations Research (ABRO) since February 2024 and is the GEP committee representative at the DIAG Department. Her research focuses on developing and analyzing methods for solving nonlinear optimization problems with continuous and discrete variables. Key research themes include decomposition methods for training Support Vector Machines and Deep Networks, methods for Mixed Integer Nonlinear Programming (MINLP), Semidefinite Programming (SDP), standard quadratic problems (StQP), and convex quadratic constrained problems. She also develops predictive machine learning models for healthcare applications and surrogate models for engineering. Her recent publications span optimization methods, machine learning applications in healthcare, sustainability assessment, and network design. Her work demonstrates a strong integration of theoretical optimization with practical applications across multiple domains. Continuous Optimization Awards 2020 Member Best Paper Award from Journal of Global Optimization Honorable Mention from Marguerite Frank Award jury for Best EJCO Paper 2024 EURO Doctoral Dissertation Award Professor Palagi teaches multiple courses including Optimization and Decision Science, Laboratory of Decision Science, Optimization Methods for Machine Learning, and Optimization for Medical programs. She serves as thesis advisor for numerous Bachelor's and Master's students in Management Engineering, Mechanical Engineering, and Data Science programs.

Wallner, JohannesView profile

Professor

• Discretization in Geometry and Dynamics
• Computational Line Geometry
• Freeform Architecture
• +8 more

Johannes Wallner is a Professor of Geometry at the Institute for Geometry , Graz University of Technology (TU Graz), since January 2007. Previously, he held positions at TU Wien, including a part-time professor role (2009-2013) in the Geometric Modeling and Industrial Geometry group. His work bridges theoretical geometry with computational applications in architectural design, machining, and surface analysis. Research Interests: Discretization in Geometry and Dynamics Computational Line Geometry Freeform Architectural Structures Subdivision Algorithms in Riemannian Geometry Geometric Tolerancing and Constraint Problems Publications focus on discrete differential geometry, mesh processing, and geometric modeling for architecture. His 2024 work on quad mesh mechanisms and 2023 studies on developable surfaces exemplify his cross-disciplinary impact. Grants: Led FWF-funded projects including SFB/Transregio (I-705), Doctoral College Discrete Mathematics (W1230), and studies on computational differential geometry, nonlinear subdivision, and geometric tolerancing. Editorial Contributions: Co-edited conference proceedings for Advances in Architectural Geometry (2010, 2012, 2014) and served as editor for Internationale Mathematische Nachrichten (2008-2017).

David W. DowdyView profile

Professor

• Tuberculosis
• HIV
• Epidemiology
• +5 more

David W. Dowdy, MD, PhD, ScM, serves as Executive Vice Dean for Academic Affairs and Professor at Johns Hopkins Bloomberg School of Public Health with joint appointments at the School of Medicine. He holds primary affiliation with the Department of Epidemiology and joint appointments in the International Health division and Global Disease Epidemiology and Control division. Dr. Dowdy is an infectious disease epidemiologist and general internist focused on tuberculosis, the world's most deadly infectious disease. Dr. Dowdy earned his MD (2008), PhD (2008), and ScM (2002) from Johns Hopkins University, and BS (1999) from Duke University. His interdisciplinary research integrates experimental and observational epidemiology, infectious disease modeling, health economics, and implementation science. He directs the Bioinformatics, Modeling, and Biostatistics Core of the JHU Tuberculosis Research Advancement Center and serves as PI/MPI of four NIH-funded clinical trials focused on TB case-finding and preventive treatment. His research spans multiple continents including Malawi, Uganda, South Africa, Vietnam, Pakistan, Ghana, Mozambique, Tanzania, and the United States. Dr. Dowdy's work emphasizes translating epidemiological data into meaningful policy decisions, with particular focus on cost-effectiveness of TB interventions and diagnostic strategies in resource-limited settings. His recent publications (2023-2025) demonstrate continued productivity with emphasis on TB screening approaches, preventive treatment strategies, diagnostic testing, and implementation science. Notable Awards and Recognitions: Strategic & Technical Advisory Group on Tuberculosis (STAG-TB), World Health Organization (2023) JHU Catalyst Award recipient (2020) Multiple Advising, Mentoring, and Teaching Recognition Awards (2018, 2013) Young Investigator Prize, International Union Against Tuberculosis and Lung Disease (2012) Teaching Excellence Awards from both Johns Hopkins and UCSF Dr. Dowdy is deeply committed to mentorship, with many senior-author publications first-authored by his trainees. He actively contributes to major research initiatives including the Uganda Tuberculosis Implementation Research Consortium (U-TIRC), HIV, Infectious Disease and Global Health Implementation Research Institute (HIGH IRI), and the NHLBI-funded HLB-SIMPLe Alliance. His work consistently addresses critical gaps in TB control, particularly around case-finding and diagnosis in high-burden settings.

Jonathan GryakView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Applied Algebra
• +5 more

Jonathan Gryak is an Assistant Professor of Computer Science and Data Science at Queens College and the CUNY Graduate Center, where he also serves as Deputy Executive Officer. He leads the Interdisciplinary Data Science Lab (IDSL), focusing on developing novel AI/ML methods for biomedical applications that leverage underlying problem morphology and operational constraints. Education: B.S. in Mathematics and Computer Science (Dual), Rensselaer Polytechnic Institute M.S. in Mathematics, Fairfield University M.Phil. in Computer Science, CUNY Graduate Center Ph.D. in Computer Science, CUNY Graduate Center (2017) Gryak's research centers on Nonlinear Algebraic Data Analysis, combining tensor analysis, numerical algebraic geometry, deep neural networks, and invariant theory to create more accurate models of complex real-world data. His Sequential Algebrogeometric Analysis (SAGA) approach captures disease progression through heterogeneous, longitudinal medical data. His work bridges the gap between theoretical mathematics and practical clinical applications, particularly in cardiac care, traumatic brain injury, and food allergy diagnostics. His recent publications demonstrate a strong emphasis on interpretable machine learning methods, especially those employing tropical geometry, for critical healthcare applications. These include predicting heart failure therapy needs, detecting acute respiratory distress syndrome, and improving oral food challenge outcome prediction. His research consistently focuses on methods that incorporate domain knowledge, handle asynchronous data, and leverage intrinsic data structures while maintaining clinical interpretability. Scientific Awards: CUNY Faculty Fellowship Publication Program (2024) NSF grant for improving treatments for heart failure patients through machine learning Gryak actively mentors PhD and undergraduate students in the IDSL, guiding research that spans from theoretical mathematical developments to clinical implementations. His lab collaborates with medical professionals to translate AI techniques into commercial applications that impact patient care. Current projects include multimodal data integration for clinical decision support across various conditions including cancer, traumatic brain injury, and inflammatory bowel disease. The Interdisciplinary Data Science Lab under Gryak's leadership develops end-to-end solutions, from novel mathematical techniques to industry and clinical partnerships for commercialization. Recent work has produced automated systems for endoscopic disease assessment, hematoma segmentation, and cardiac event prediction, with multiple patents stemming from this research.

• Knowledge Representation and Reasoning
• Quantum Computation
• Artificial Intelligence
• +3 more

Professor Sanjiang Li is affiliated with the University of Technology, Sydney (UTS) as a Professor in the Faculty of Engineering and Information Technology , specifically within the Centre for Quantum Software and Information . With a PhD in Mathematics from Sichuan University and a BSc from Shaanxi Normal University, his research spans quantum computation , knowledge representation and reasoning , and formal verification of quantum systems . His recent work focuses on quantum circuit transformation , including novel methods like adaptive divide-and-conquer and Monte Carlo Tree Search frameworks. He has advanced symbolic verification techniques using tensor decision diagrams and explored classical-quantum hybrid algorithms for resource-efficient training. Dr. Li has received prestigious awards such as the ARC Future Fellowship and Alexander von Humboldt Research Fellowship . He supervises PhD students including Calum Holker and Guangxi Li , and contributes to quantum software development through funded projects like the Sydney Quantum Academy and ARC Discovery Projects .

• Swedish mother-tongue education
• Social interaction in educational settings
• Communication aids for children with disabilities
• +7 more

Niklas Norén is a Senior Lecturer in Didactics at the Department of Education, Uppsala University. His work bridges Swedish language education with social interaction analysis, focusing on communication practices in educational settings. He supervises students at basic, bachelor's, and master's levels while leading the Special Needs Education specialization within the Master Programme in Educational Sciences. Member of research groups: CLIP, STOLP, PS Network affiliations: NISCI, OFTI Research spans three core areas: (1) Communication aids for children with neurological impairments, (2) Institutional interaction analysis using EMCA methodology, and (3) Grammatical constructions in conversational contexts. Recent projects examine classroom discourse, mathematical reasoning in groups, and digital writing practices. Key article trends: 2022-2025 work emphasizes mathematical discourse and digital communication , while longitudinal research (2013-2022) explores pivot constructions and eye-gaze AAC devices . Methodologically grounded in ethnomethodology and conversation analysis . Network involvement includes coordination of NISCI (special educational needs network) and web administration for OFTI. His research combines theoretical linguistics with practical applications in inclusive education, particularly for children with cerebral palsy and autism spectrum disorders.

Ahmed HeikalView profile

Professor

• Cellular and molecular biophysics
• Energy metabolism
• Mitochondrial dysfunction
• +7 more

Ahmed Heikal is a Professor at the Department of Chemistry and Biochemistry within the Swenson College of Science and Engineering at the University of Minnesota Duluth. His research focuses on cellular biophysics , mitochondrial metabolism , and fluorescence-based biosensors to study molecular dynamics in complex environments. Developing two-photon microscopy and time-resolved spectroscopy tools Investigating macromolecular crowding and ionic strength sensing in living systems Collaborating with institutions like Utrecht University and Mayo Clinic Heikal's recent publications (2024-2017) span topics in fluorescence correlation spectroscopy , NAD(P)H metabolic imaging , and FRET sensor design , with applications in cancer metabolism and biomolecular environments . He has received recognition as a Fellow of the Royal Society of Chemistry (2021) and secured Grant-in-Aid from the University of Minnesota (2020–2021). His lab trains students in biophysical methods including cell culture , ultrafast spectroscopy , and image processing , with alumni pursuing PhD programs at institutions like Cornell University , Northwestern University , and University of Chicago . The lab emphasizes interdisciplinary research at the interface of chemistry , biology , and physics , while maintaining shared facilities like confocal microscopy and NMR spectrometers at UMD. Heikal also serves as an Associate Editor for Frontiers in Physics and Molecular Biosciences journals since 2022.

• machine translation
• analogy
• multilingual alignment
• +7 more

Yves Lepage is a Professor at Waseda University's Faculty of Science and Engineering, specifically within the Graduate School of Information, Production, and Systems. He maintains an active research laboratory (lepage-lab.ips.waseda.ac.jp) and teaches courses including Example-based machine translation/NLP, Natural language processing, and Master's/Doctoral thesis supervision for the 2025 academic year. His research focuses on the application of analogical reasoning to natural language processing problems, particularly machine translation. Lepage's work spans formal analogy between strings, sentence-level analogies, morphological analysis, and multilingual systems. His research interests include machine translation, analogy, multilingual alignment, multilingual large language models, and foreign language aids. He has made significant contributions to understanding analogical density in corpora and developing methods to leverage analogies for translation, especially in low-resource scenarios. His publication record shows consistent output through 2024, with research evolving from foundational work on proportional analogy to sophisticated applications with neural networks. Recent work explores masked prompt learning for analogies, fuzzy analogies for translation, and organizing lexica into analogical grids for morphological generation across languages. Waseda University Teaching Award (Spring semester 2016) Lepage has successfully led multiple research projects funded by the Japan Society for the Promotion of Science, including "Theoretically founded algorithms for the automatic production of analogy tests in NLP" (2021-2024) and "Self-explainable and fast-to-train example-based machine translation using neural networks" (2018-2021). His work has involved international collaboration, including a 2023-2024 research period at the University of Montreal. He serves as Concurrent Researcher at the Waseda Research Institute for Science and Engineering (2024-2026) and has been active in professional organizations including the Information Processing Society of Japan and the Japanese Natural Language Processing Association.

• Numerical Relativity
• General Relativity
• Applied Mathematics
• +3 more

Professor Yoneda Gen is affiliated with Waseda University 's School of Fundamental Science and Engineering , where he has held a professorship since at least 2025. His work focuses on Numerical Relativity , General Relativity , and Computational Physics , with particular emphasis on constraint propagation analysis in Einstein equations. Education : PhD in Science from Waseda University His research explores advanced formulations for stable numerical simulations of gravitational systems, including the covariant BSSN formulation , C 2 -adjusted systems , and discrete variational derivative methods . He has developed techniques to improve numerical stability through eigenvalue analysis and constraint damping mechanisms. Research trends in his publications (1994–2024) show consistent focus on: Constraint propagation in ADM/BSSN systems High-dimensional spacetime singularities Hyperbolic formulations for relativistic simulations Structural preservation in differential equations He has received multiple Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (2004–2007, 2010–2014, 2020–2023). His work has been cited over 233 times with an h-index of 10. Teaching activities include courses on: Mathematics B3 (Calculus for Physics) Special Exercise on Mathematics Research on Relativity Theory Seminars in Applied Mathematics Hamiltonian structures in numerical methods

Uwe BäselView profile

Professor

• Geometry
• Kinematics
• Probability Theory
• +4 more

Prof. Uwe Bäsel is affiliated with the Faculty of Engineering at Leipzig University of Applied Sciences , focusing on Mechanical Engineering . His research spans geometry, kinematics, and probability theory, with applications in gear technology and random processes. He contributes to the EMB | Institute for Development-Oriented Mechanical Engineering , particularly in transmission technology and stochastic geometry. His work emphasizes non-uniform gear ratios , geometric probability , and kinematic synthesis . Key projects include modeling cam mechanisms for non-uniform motion and analyzing Buffon-Laplace needle problems. His publications address integral geometry, random point distances, and oloid properties. Prof. Bäsel’s recent research explores complex-valued functions in plane differential geometry , incomplete beta functions for motion transfer , and sinc integrals . He integrates mathematical rigor with engineering applications, particularly in transmission systems and geometric modeling.

• Mechatronics
• Robotics
• Embedded Systems
• +2 more

Dr. Roozbeh Vaziri is an Associate Professor and Head of the Department of Mechatronics (English) at Cyprus Aydin University. His academic responsibilities include teaching advanced courses in robotics, embedded systems, and engineering mathematics. Education: Doctorate in Mechanical Engineering, Eastern Mediterranean University (2017) Master's in Mechanical Engineering, Eastern Mediterranean University (2008) Bachelor's in Chemical Engineering, Islamic Azad University (2006) Research Focus: His field expertise spans mechatronics, robotics, embedded systems, computer-aided design, and applied mathematics, reflecting his interdisciplinary engineering background. Awards & Advising: No awards or student advising details are currently documented.

• Symbolic-Numerical Analysis
• Differential-Algebraic Equations
• Computational Mechanics
• +3 more

Davide Stocco is a Research Fellow at the Department of Industrial Engineering, University of Trento. He also serves as a Teaching Assistant in the same department, contributing to courses like Computational Methods for Mechatronics and Mechatronic Systems Simulation. His research focuses on symbolic-numerical analysis, differential-algebraic equations (DAEs), and computational mechanics. He develops tools for real-time simulations, tire-ground modeling, and matrix factorization techniques. Recent publications reveal trends in DAE index reduction using symbolic computation, parallel processing of bordered matrices, and geometric modeling for mechatronic systems. His work bridges symbolic mathematics with practical engineering applications. As a Teaching Assistant, he collaborates with Professors Enrico Bertolazzi and Francesco Biral in the Mechatronics Engineering program. He actively contributes to academic research and teaching at the University of Trento.