Find Academic Supervisors

Aashutosh MistryView profile

Assistant Professor

• Energy Technologies
• Electrochemistry
• Battery Science
• +3 more

Aashutosh Mistry is an Assistant Professor in the Department of Mechanical Engineering at the Colorado School of Mines. His research group operates from CoorsTek 207, focusing on experimental and theoretical approaches to advance energy technologies. Contact details include the email aashutosh.mistry@mines.edu and phone number 832-730-9071. Mistry's research integrates physics-based modeling, controlled experiments, and machine learning to bridge gaps between novel materials and scalable energy devices. Key interests encompass battery science, ion transport dynamics, multiscale electrolyte behavior, and sustainable energy transitions. His work targets applications like electrified transportation, solid-state batteries, and electrochemical systems optimization. Recent publications emphasize data-driven electrochemistry, electrolyte transport mechanisms, and machine learning applications. Trends include operando characterization of battery materials, predictive modeling of ion motion, and sustainability-focused energy research. Articles frequently utilize advanced techniques like electrophoretic NMR and computational simulations to resolve transport complexities. Mistry leads an active research group developing tools for microstructure analysis and transport phenomena. The team synergizes multiscale experimentation with theoretical frameworks to address energy technology challenges.

Semra KocabıyıkView profile

Professor

• Molecular Mechanisms of Protein Thermostability
• Molecular Chaperones
• Proteasome Function
• +3 more

Semra Kocabıyık is a Professor in the Department of Biological Sciences at Middle East Technical University (METU). Her research focuses on molecular mechanisms of protein stability, molecular chaperones (e.g., small heat-shock proteins), proteasome function, and stress responses in thermoacidophilic archaea, particularly Thermoplasma volcanium. She has contributed to improving enzyme stability and recovery under stress conditions using molecular chaperones. Education: B.Sc. in Agriculture, Ankara University (1972–1977) M.Sc. in Biological Sciences, METU (1980–1982) Ph.D. in Biology, METU (1982–1986) Postdoc, Department of Biology, University of Louisville, USA (1990–1992) Research Interests: Her work integrates biochemistry, molecular biology, and structural biology to study protein stability, stress adaptation in archaea, and enzyme engineering. Key areas include small heat-shock proteins, proteasome regulation, and applications of molecular chaperones in biotechnology. Publications: Recent articles highlight advancements in protein engineering, archaeal stress responses, and structural dynamics of chaperones, reflecting her expertise in extremophile biology and protein function. Achievements: With 95 publications, 139 WoS citations, and 44 thesis advisories, her contributions span academia and biotech applications. Labs & Collaborations: Her lab focuses on archaeal molecular machines and employs techniques like microarray analysis, surface-enhanced Raman spectroscopy (SERS), and molecular cloning.

Jeremy GordonView profile

Associate Professor

• Medical Physics
• Magnetic Resonance Imaging (MRI)
• Metabolic Imaging
• +3 more

Dr. Jeremy Gordon is an Associate Professor in the Department of Radiology & Biomedical Imaging at the University of California, San Francisco (UCSF). He holds a PhD in Medical Physics from the University of Wisconsin-Madison (2013) and a BS in Physics & Astronomy from the University of Georgia (2008). Prior to his faculty role, he worked as a postdoctoral scholar (2013–2016) and Senior Bioengineer (2016–2020) at UCSF. His research focuses on developing novel hyperpolarized MRI techniques for metabolic imaging, particularly in pancreatic cancer, multiple sclerosis, Alzheimer’s Disease, and brain perfusion studies. These methods leverage hyperpolarized 13C and x-nuclei to assess metabolic pathways and treatment responses. Key applications include non-invasive metabolic biomarker identification and improved clinical care for cancer and neurological disorders. Major awards include the Distinguished Reviewer Award (2018), RSNA ITARSc Program recognition (2017), and multiple merit awards from the International Society for Magnetic Resonance in Medicine (2013). He is affiliated with the Advanced Imaging Technologies Resource Group and the Hyperpolarized MRI Technology Resource Center at UCSF. Recent work emphasizes multi-center clinical trials, data standardization (DICOM integration), and open-source tools for X-nuclear imaging. His lab collaborates widely, with studies involving metabolic imaging of the brain, abdomen, and heart under various physiological conditions (e.g., glucose challenges).

LIU BoxiangView profile

Assistant Professor

• Genomics
• Bioinformatics
• Machine Learning
• +3 more

Asst Prof LIU Boxiang holds the position of Assistant Professor and NUS Presidential Young Professorship at the Department of Pharmacy and Pharmaceutical Sciences, National University of Singapore (NUS), within the Faculty of Science. His research focuses on integrating multi-omics approaches with computational methods to study complex diseases such as coronary artery disease and age-related macular degeneration. He specializes in developing statistical and machine learning tools for genomic analysis, including eQTL mapping and deep learning architectures for gene expression regulation. Education: BA in Biophysics (Illinois Wesleyan University), MS and PhD in Bioinformatics (Stanford University). He contributed to the GTEx consortium and is part of the Asian Immune Diversity Atlas (AIDA) initiative. His lab develops methods like ANTseq for ancestry determination and scPrediXcan for cell-type-specific transcriptome studies. Research Interests: Functional genomics, eQTL analysis, deep learning in biomedicine, and computational tools for omics data integration. His work bridges disciplines such as natural language processing and computer vision with biological questions. Scientific Awards: NUS Presidential Young Professorship (2021). His lab's innovations include ParaMed, a biomedical translation dataset, and LinearDesign for optimized mRNA stability. Advising and Grants: Leads the Liu Lab (boxiangliulab.com), focusing on single-cell genomics, mitochondrial dynamics, and computational biomedicine. Collaborates on projects like the RESET cohort study for cardiovascular disease prevention.

Christopher MyersView profile

Adjunct Professor

• Biological Physics
• Complex Systems
• Networks
• +9 more

Christopher Myers is an Adjunct Professor in the Department of Physics at Cornell University and a Senior Research Associate at the Cornell Center for Advanced Computing. He is also a member of the graduate faculty in Physics, Computational Biology, Applied Mathematics, and Computational Science and Engineering. His research spans multiple disciplines, connecting physics, biology, and computational science. Myers earned his B.A. in History from Yale University in 1984 and his Ph.D. in Physics from Cornell University in 1991. His academic journey includes postdoctoral positions at UC Santa Barbara and the Cornell Theory Center, followed by various research roles at Cornell institutions including the Institute of Biotechnology and arXiv.org (where he served as Scientific Director from 2014-2016). Myers' research focuses on complex systems at the intersection of physics, biology, and computational science. His primary areas include infectious disease dynamics and host-pathogen interactions, theoretical and computational systems biology, biological information processing, dynamics and cascades on networks, and the structure and dynamics of intracellular networks. He has made significant contributions to understanding how complex systems behave across multiple scales, from molecular networks to ecological communities. His work often employs computational approaches to model and analyze biological phenomena. His recent publications (2020-2024) show a strong trend toward interdisciplinary research connecting computational methods with biological and ecological systems. There's a clear focus on network approaches to understanding disease transmission, particularly in plant-pollinator communities, as well as developing new computational methods for analyzing complex systems. His work increasingly integrates machine learning techniques with traditional modeling approaches to address complex biological questions. Myers has been actively involved in teaching and mentoring, having served as an Adjunct Professor since 2010 and teaching courses such as 'Computational Methods for Complex Systems' (Physics 7682). He has also developed and taught workshops on Python for high performance computing, data science, and AI with deep learning through Cornell's various educational programs including CVW and eCornell. His research has been conducted through multiple labs and teams, including the Cornell Center for Advanced Computing (current), the Institute of Biotechnology (2007-2017), and the Cornell Theory Center (1993-1997, 1998-2007). These teams have focused on computational approaches to biological problems, with particular emphasis on systems biology, infectious disease modeling, and software development for scientific computing.

Jun AllardView profile

Professor

• Mathematical Biology
• Computational Biology
• Cell Mechanics
• +4 more

Jun Allard is a Professor at the University of California, Irvine, with joint appointments in the Department of Mathematics and Department of Physics and Astronomy. He is affiliated with the Center for Complex Biological Systems and the NSF-Simons Center for Multiscale Cell Fate Research. Education includes: Ph.D. Applied Mathematics, University of British Columbia (2011) M.Sc. Physics, Dalhousie University (2007) B.Sc. Mathematical Physics, Queen's University (2005) His research specializes in mathematical and computational modeling of cellular and biomolecular mechanics. Key interests include how cells utilize force, space, and time to solve problems, with applications in immune cell signaling, cytoskeletal dynamics, and intracellular transport. His work combines theoretical models with experimental collaborations to uncover fundamental biological mechanisms. Recent publications (2021-2025) predominantly focus on computational approaches to cellular processes, including molecular transport mechanisms, immune receptor dynamics, and cytoskeletal organization. These studies employ advanced stochastic modeling, biophysical simulations, and quantitative experimental methods to reveal principles governing cellular behavior. Scientific awards include: UCI Chancellor's Award for Distinguished Fostering of Undergraduate Research (2015) Emerging Diversity Scholar, National Center for Institutional Diversity (2016) Honorable Mention, NSF Graduate Research Fellowship (2012) He has advised over 12 doctoral students and leads the Allard Lab, which develops computational models for cell mechanics. Major grants include NSF awards for research on molecular-tether reactions (DMS-2052668), nanoparticle adhesion (CBET-1929565), and multiscale cell fate (DMS-1763272). The lab collaborates internationally with experimental groups and participates in interdisciplinary initiatives including the Chemical and Materials Physics program.

Alison JohnstonView profile

Associate Professor

• Statistical Ecology
• Biodiversity Monitoring
• Citizen Science
• +3 more

Dr. Alison Johnston is a Reader in Statistics and Director of CREEM at the University of St Andrews' School of Mathematics and Statistics. She specializes in developing statistical methods for ecological applications, particularly using citizen science data to study bird population dynamics and biodiversity patterns. Educational background includes a BSc in Quantitative Ecology from the University of St Andrews and a PhD from the University of Cambridge. Research focuses on: Statistical modeling of species distributions and population trends Bias correction in citizen science data Climate change impacts on avian communities Conservation prioritization through spatial analysis Her publications demonstrate consistent innovation in integrating large-scale ecological datasets, with recent work emphasizing climate-driven range shifts, conservation effectiveness, and methodological advances in statistical ecology. Research consistently addresses the challenge of extracting reliable ecological insights from complex observational data. Honors include the 2021 Marsh Award for Ornithology. She supervises PhD students working on biodiversity monitoring, spatial capture-recapture models, and statistical applications in conservation. Dr. Johnston leads projects at the Centre for Research into Ecological & Environmental Modelling (CREEM), developing tools that support evidence-based conservation policy and biodiversity management across multiple continents.

• Statistical Mechanics
• Dynamical Systems
• Percolation Theory
• +5 more

Peter Grassberger is a Visiting Research Professor at the Department of Physics and Astronomy, University of Calgary, Canada. His academic journey includes professorships at institutions such as the University of Wuppertal (1977–2005) and the John-von-Neumann Institute in Jülich (1996–2005). He holds a Dr. Phil. from the University of Vienna (1965) and a Habilitation from Bonn University (1973). His research spans statistical physics, nonlinear dynamics, and complex systems. Key contributions include work on strange attractors, percolation theory, and computational methods like the PERM algorithm for polymer systems. He is renowned for foundational papers on estimating attractor dimensions and for pioneering studies in directed percolation and self-organized criticality. Grassberger's awards include being a Highly Cited Researcher with over 13,000 citations. His work bridges theoretical physics and applications, such as medical diagnostics and earthquake prediction. He has advised numerous students and holds editorial roles in journals like Journal of Physics A and Complexity .

Bradley SmithView profile

Professor

• Molecular Imaging
• Organic Chemistry
• Biophysics
• +3 more

Bradley D. Smith is the Emil T. Hofman Professor of Science and Director of the Notre Dame Integrated Imaging Facility at the University of Notre Dame, where he has held academic positions since 1991. He leads the Smith Group, focused on interdisciplinary research combining organic synthesis, biochemistry, and photonics to develop molecular imaging probes for applications in medicine, including drug discovery and diagnostics. His work emphasizes fluorescent dyes (e.g., squaraine-rotaxanes) for imaging cellular processes, bacterial infections, and tumors. Smith earned his PhD from the Pennsylvania State University (1988) and B.Sc. from the University of Melbourne (1983), with postdoctoral training at Columbia University and Oxford University. His accolades include Fellowships from the Royal Society of Chemistry and AAAS, and teaching awards. The Smith Group’s innovations span over 300 publications, with notable contributions to photothermal therapy, near-infrared imaging agents, and supramolecular chemistry. Advising over 20 PhD students, his lab integrates synthetic chemistry, bioimaging, and nanotechnology, highlighted by creative student cakes symbolizing research milestones. Beyond academia, his work impacts gold recovery and environmental chemistry through supramolecular systems.

• Material Science
• Mathematical Modeling
• Fractal Networks
• +5 more

Professor Tony Roberts is the Head of School in the School of Mathematical Sciences at Queensland University of Technology (QUT). He holds a PhD from the Australian National University and is a Fellow of the Australian Mathematics Society. His research focuses on the interplay between material microstructure and macroscopic properties, with emphasis on topology optimization, random structure modeling (e.g., Gaussian fields, percolation models), and material property analysis such as conductivity, diffusion, and fluid flow. He develops computational methods for analyzing experimental techniques like 3D statistical reconstruction and small-angle scattering. His recent work includes optimizing piezoelectric materials for robotics, studying diffusion dynamics in fractal networks, and modeling material failure mechanisms. Key contributions span multi-functional piezoelectric components, anisotropic elastic properties of additively manufactured alloys, and fracture mechanics in perforated materials. Awards include his fellowship in the Australian Mathematics Society. Supervision interests include structural optimization, diffusion in random media, and porous material failure modeling. Education: PhD (Australian National University) Affiliations: Faculty of Science, School of Mathematical Sciences Research Themes: Material science, computational modeling, fracture mechanics, stochastic systems

Kevin FloresView profile

Associate Professor

• Mathematical Biology
• Precision Medicine
• Environmental Toxicology
• +4 more

Kevin Flores is an Associate Professor in the Department of Mathematics at North Carolina State University (NC State), and Director of the Biomathematics Graduate Program. He leads the Flores Lab, focusing on developing mathematical and statistical methods for parameter estimation, uncertainty quantification, and forecasting in Precision Medicine, Environmental Toxicology, and Synthetic Biology. His work bridges computational approaches with biological systems analysis. Dr. Flores earned his PhD in 2009 from Arizona State University. His research groups include the Mathematical Biology cluster within the Department of Mathematics. His affiliations include Cox Hall 406D and the College of Sciences at NC State. Research interests emphasize interdisciplinary applications: (1) Mathematical Biology involving tumor heterogeneity, viral dynamics, and angiogenesis modeling; (2) Biostatistics focusing on parameter estimation in complex systems; and (3) Computational Tools for biomedical image analysis and machine learning in healthcare. His lab pioneered methods like biologically-informed neural networks and topological data analysis for biological systems. Recent work highlights include: (1) tumor spheroid modeling predicting clinical variability; (2) BK virus infection dynamics in transplant patients; (3) EEG-based brain-computer interface improvements using GANs; and (4) few-shot learning for plant phenotyping. His methodologies address challenges in sparse data scenarios and integrate mechanistic understanding with data-driven approaches. Awards and recognition : None explicitly listed in provided texts. Advising and grants: No specific advisees or grant details provided in texts. His lab's software tools support image segmentation and population modeling. Labs/teams: Directs the Flores Lab for Mathematical Biology at NC State, specializing in hybrid computational-experimental approaches. Collaborates across departments in biomathematics and engineering.

Bo LiView profile

Professor

• Scientific computing
• Numerical analysis
• Biophysics
• +9 more

Bo Li is a Professor in the Department of Mathematics at the University of California, San Diego (UCSD). He holds affiliations with the Quantitative Biology Ph.D. Program and the Halicioglu Data Science Institute as a faculty member. His research focuses on scientific computing, numerical analysis, and applied mathematics with applications in biophysics, computational biology, materials science, and continuum mechanics. Current projects include biomolecular simulation, variational solvation methods, bacterial colony dynamics modeling, and neural network foundations. Li has led multiple funded research initiatives, including NIH and NSF grants, and has been involved in interdisciplinary collaborations. He teaches advanced courses such as Topics in Applied Mathematics (Math 217) and Numerical Analysis (Math 270B). His work bridges mathematical theory with computational methods for solving complex biological and physical systems.

• Soft Materials
• Biological Materials
• Neutron Scattering
• +4 more

Jan Swenson is a researcher at Chalmers University of Technology, where she earned her PhD in Physics in 1996. Her research focuses on soft materials, particularly the role of water in biological systems and supercooled water dynamics. She employs neutron scattering and molecular dynamics simulations to study protein aggregation (e.g., Alzheimer's and Huntington's diseases), lipid nanoparticles for RNA delivery, and sugar-protein interactions. Her work bridges physics, chemistry, and biomedicine, aiming to develop novel materials for medical applications and energy storage. Education: PhD in Physics, Chalmers University of Technology (1996) Postdoctoral Research, University College London, UK (structure/stability of clay gels) Research Interests: Soft materials, biological materials' hydration, neutron scattering analysis, supercooled water properties, and protein stabilization via sugars. Her recent projects include modeling material dynamics using computer simulations and optimizing lipid nanoparticles for therapeutic RNA delivery. Grants & Collaborations: Works with colleagues to develop new data analysis methods for neutron scattering. Active in interdisciplinary projects involving drug delivery systems and materials science. Labs/Teams: Part of Chalmers' research groups focused on biomaterials and energy materials, contributing to structural battery electrolyte development.

• Nanoparticle Science
• Fluorescence Spectroscopy
• Material Science
• +4 more

Dr. Daniel Doveiko is a Researcher in the Pure & Applied Chemistry department at the University of Strathclyde's Faculty of Science . His work focuses on nanoparticle design, fluorescence spectroscopy, and material characterization, with applications in environmental science, biomedical engineering, and drug delivery systems. He is currently a Research Co-investigator on the EPSRC-funded Doctoral Training Partnership (2020-2025), collaborating on nanoparticle metrology and molecular dynamics studies. He holds a PhD in Physics and has published extensively in journals like Journal of Chemical Physics and Langmuir . His research employs advanced techniques including molecular dynamics simulations and fluorescence recovery after photobleaching (FRAP). Notable achievements include developing smartphone-based microscopy systems and studying silica nanoparticle interactions with fluorescent dyes. Key areas: Nanoparticle adsorption mechanisms, quantum chemistry calculations, biomedical nanocarriers Techniques: Molecular dynamics, fluorescence spectroscopy, X-ray scattering Award: Certificate of Achievement (2023) His work bridges theoretical and experimental chemistry, contributing to both fundamental material science and applied biomedical solutions.

• Future(s) studies
• Speculation in Science
• Philosophy of Science and Technology
• +3 more

Dirk S. Hovorka is a Professor of Systems and Design in the Department of Business Information Systems at the University of Sydney Business School. His work bridges theoretical and practical aspects of information systems, with a particular focus on how technology shapes and is shaped by societal practices. He serves as Senior Editor of JAIS (Research Perspectives), Editorial Board Member of ISR, and Co-chair of the HICSS 'Informing Research: Engaging with Futures' mini-track. Dr. Hovorka's educational background includes a BA (Honours), an MS in Geology, an MS in Interdisciplinary Telecommunications, and a PhD in Information Systems from the University of Colorado. His academic journey has positioned him at the intersection of technical and philosophical approaches to information systems. Hovorka's research addresses how scientific and societal practices bring forth 'worlds' through theory, design, and conceptualizations of 'the future.' His work recognizes that the future is resistant to full prediction and control, with increasing societal change rendering past knowledge less indicative of future states. He focuses on speculative approaches to 'knowing' regarding technology, society, and biophysical environments. His research spans Future(s) studies, Speculation in Science, Philosophy of Science and Technology, Interpretive Research and Qualitative Methods, Sustainability, and System Dynamics. Analysis of Hovorka's recent publications reveals a strong trajectory toward speculative futures and the philosophical dimensions of technology. His work consistently examines how we engage with uncertain futures through design and conceptual frameworks. The articles demonstrate increasing interdisciplinary reach, connecting information systems with philosophy, sustainability studies, and organizational theory, while maintaining methodological rigor through interpretive and qualitative approaches. Hovorka has received significant recognition for his scholarly and teaching contributions: AIS Best Paper (2011) 'Secondary Design: A Case of Behavioral Design Research' Beta Gamma Sigma Professor of the Year (2018) Wayne Lonergan Award for Outstanding Teaching (2018) Dean's Award for Teaching (2022) Multiple USS Teaching Citations (2015, 2017, 2020, 2022) As an educator, Hovorka supervises multiple PhD students working on projects related to digital inequality, AI adoption in health services, and human-centered artificial intelligence. His teaching portfolio includes innovative courses such as 'Gadgets, Gods and Godzilla,' 'The Nature of Systems' (an MBA class on System Dynamics), 'Agile Project Methods,' and 'Philosophy of Business Research' for PhD students. His approach emphasizes critical thinking about technology's role in society and the philosophical foundations of business research.