جست‌وجوی استاد و پژوهشگر

Bo Zhuمشاهده پروفایل

استادیار

• Computer Graphics
• Computational Physics
• Scientific Machine Learning
• +۳ مورد دیگر

Bo Zhu is an Assistant Professor at Georgia Tech's School of Interactive Computing. His research focuses on computer graphics, computational physics, and scientific machine learning, particularly in fluid dynamics, vortical structures, and computational design. He holds a Ph.D. in Computer Science from Stanford University and completed postdoctoral training at MIT CSAIL. Prior to Georgia Tech, he served as an Assistant Professor at Dartmouth College. His work is supported by grants such as the NSF CAREER Award (2022). Education: Ph.D. in Computer Science, Stanford University Postdoctoral Training: MIT CSAIL Dr. Zhu's research bridges physics simulation and machine learning, addressing challenges in fluid dynamics and material design. His group develops high-performance algorithms for fluid-structure interaction, topology optimization, and biomedical modeling. Recent projects include real-time fluid simulation techniques and neural network-based approaches for cardiac cell analysis. His publications span topics like fluid reconstruction from videos, particle-based methods, and biomimetic engineering. The NSF CAREER Award recognizes his innovative contributions to computational science and engineering. Advising and Grants: Zhu's grants support interdisciplinary projects in fluid dynamics and machine learning. He advises students in computational physics and design, though specific advisee names are not listed. His lab collaborates with industry and academic partners to advance simulation-driven engineering solutions.

Daan Vorselenمشاهده پروفایل

استادیار

• Immunology
• Biophysics
• Cellular Biology
• +۵ مورد دیگر

Dr. Daan Vorselen is an Assistant Professor in the Department of Cell Biology and Immunology at Wageningen University & Research. He holds an interdisciplinary background in biology (Leiden University) and biophysics (Vrije Universiteit Amsterdam), with postdoctoral training at Stanford University and the University of Washington. His research focuses on the role of physical forces in immune cell dynamics, particularly in phagocytosis and efferocytosis. Key methodologies include deformable microspheres for force sensing and advanced microscopy techniques. Current projects explore mechanobiology approaches, phagocytic cup shaping, and molecular regulation of cellular cleanup processes in diseases like cancer and neurodegeneration. Education: Bachelor/Master in Biology, Leiden University PhD in Biophysics, Vrije Universiteit Amsterdam Postdoctoral Research: Stanford University and University of Washington with Julie Theriot Research Interests: His work combines biophysical techniques with molecular biology to study how mechanical forces influence immune cell behavior. Central themes include: Mechanical regulation of phagocytosis and efferocytosis Role of physical forces in immune response evasion by cancer cells Development of tools like hydrogel microspheres for force measurement Genome-wide screens to identify phagocytosis regulators Scientific Contributions: Recipient of CRI Irvington Fellowship (postdoc) Recent grants: NWO-M1 and VLAG awards for immune-mechanical studies Collaborations with institutions like the Morgan Huse lab and Michael Bassik lab Lab Activities: The Vorselen Lab actively mentors MSc students and PhD candidates, focusing on interdisciplinary training. Current opportunities include funded PhD positions in immune mechanobiology and phagocytosis dynamics. The lab also engages in international conferences and hosts visiting researchers.

• Multiscale Modeling
• Biological Processes
• Physical Processes
• +۳ مورد دیگر

Mariya Ptashnyk is an Associate Professor in the School of Mathematical & Computer Sciences at Heriot-Watt University, specializing in Mathematics. She holds an ORCID identifier (0000-0003-4091-5080) and has been affiliated with the university since at least 2015. Her research focuses on multiscale modeling of biological and physical processes, with contributions to plant tissue biomechanics, soil-water interactions, and cell signaling pathways. Education: PhD in Mathematics from the University of Heidelberg, Germany. Postdoctoral research at the University of Oxford and the Centre for Modelling, Simulation in Biosciences (BIOMS), Heidelberg University. Research Interests: Ptashnyk’s work integrates mathematical analysis with biological systems, particularly in understanding root growth mechanics, water transport in soils, and cellular signaling. Her models address challenges in agricultural sustainability, drought mitigation, and plant-microbe interactions. She has pioneered techniques in homogenization theory and multiscale analysis for complex biological systems. Recent Trends in Publications: Her recent work emphasizes mechanotransduction pathways, root-water dynamics, and stochastic modeling of biological processes. Key themes include the role of rhizodeposition in soil rewetting, collective cell migration mechanisms, and non-local chemotaxis models. Awards: Heriot-Watt University Teaching Excellence Award (2019). The Student Union Oscars (2023). Teaching & Activities: Ptashnyk teaches courses like Advanced Mathematical Biology and Applied Analysis. She actively reviews for journals (e.g., Journal of Mathematical Biology ) and organizes conferences (e.g., SciCADE 2026). Her activities include visiting research stints at institutions like the Erwin Schrödinger Institute. Labs/Teams: While no specific lab is named, her collaborations span international teams in plant biology, computational mathematics, and environmental science.

Keith Smithمشاهده پروفایل

مدرس

• Biomedical Network Analysis
• Neuroimaging Data Analysis
• Machine Learning in Neuroscience
• +۴ مورد دیگر

Keith Smith is a Lecturer in the Department of Computer and Information Sciences at the University of Strathclyde, where he leads the Digital Health & Wellness Research Group (DHaWG). Previously, he held positions as a lecturer at Nottingham Trent University and as a UKRI Innovations Fellow in Medical Informatics at the University of Edinburgh. He earned his PhD in biomedical signal processing from the University of Edinburgh's IDCOM lab. His research focuses on computational tools for analyzing biomedical networks, including neuroimaging data from structural and functional brain networks, protein interaction networks, and metabolic networks. Key areas include hierarchical complexity of brain networks, machine learning applications for neuroimaging, and theoretical foundations of network geometry and complexity. He collaborates widely with clinical and academic partners to address challenges in neurological and mental health conditions like Alzheimer’s, depression, and schizophrenia. His work contributes to UN Sustainable Development Goals, particularly improving health and well-being through advanced data-driven methodologies. He currently oversees PhD projects exploring brain networks, deep learning for disease prediction, and evolutionary protein biology. Notable achievements include the UKRI fellowship and impactful interdisciplinary collaborations. His talks and presentations, such as on statistical complexity of brain networks, highlight his commitment to advancing theoretical and applied network science.

Sara Kellerمشاهده پروفایل

پژوهشگر ارشد

• Biomedical Engineering
• Medical Imaging
• Ultrasound Therapy
• +۳ مورد دیگر

Sara Keller is a Research Fellow and Postdoctoral Research Assistant in the Department of Engineering Science. She holds a PhD in Bioengineering from the University of Washington (2021) and a BME from Vanderbilt University (2016). Her research focuses on ultrasound-guided therapies, particularly using microbubbles for targeted drug delivery and biofilm treatment. She joined the BUBBL group in 2021, specializing in cavitation activity analysis and medical acoustics. Her work spans biofilm disruption, cancer treatment monitoring, and preclinical safety studies in porcine models. Key contributions include developing acoustic devices for cell strain quantification and investigating nonlinear echoes from microbubbles. She collaborates on projects like intracranial hemodynamics modeling in sickle cell anemia and optimizing ultrasound-mediated drug delivery systems. Her recent articles emphasize therapeutic efficacy, safety protocols, and translational applications of ultrasound technologies. Research interests include advancing diagnostic tools through cavitation monitoring and enhancing drug penetration in solid tumors. Advising and grants: No formal advisees listed; current role focuses on postdoctoral research. Active in the BUBBL group for collaborative biomedical engineering projects.

Tian Wangمشاهده پروفایل

پژوهشگر ارشد

• Theory and Computation
• Computational Chemistry
• Materials Chemistry
• +۴ مورد دیگر

Tian Wang is a Research Fellow in the Department of Chemistry at the University of Washington, College of Arts & Sciences. His research focuses on theoretical and computational approaches to materials design, particularly in electrocatalysis, perovskite materials, quantum dots, and supercapacitors. He holds a Ph.D. from the National University of Singapore (2021), an M.S. from Columbia University (2016), and a B.S. from Nanjing University (2014). His work emphasizes understanding and optimizing material properties through confinement effects, vacancy engineering, and surface reconstruction. Recent studies involve high-entropy alloys for hydrogen evolution reactions and novel lithium recovery methods using hydrogel networks. He has contributed to advancements in perovskite solar cells, fluorescent probes for cellular analysis, and optoelectronic materials. Major Research Areas: Theory and Computation, Materials Chemistry, Electrochemistry Key Projects: Defects passivation in perovskites, supercapacitor performance enhancement via molecular confinement, laser-induced material modifications for oxygen evolution Notable collaborations include projects with Prof. Xiaosong Li and Prof. Zhi-Kuang Tan. His research often intersects computational modeling with experimental synthesis to address energy storage and sustainable materials challenges.

Leon O. Chuaمشاهده پروفایل

استاد

• Cellular Neural Networks
• Nonlinear Dynamics
• Chaos Theory
• +۳ مورد دیگر

Leon O. Chua is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley. He joined the faculty in 1970 after serving as an Assistant and Associate Professor at Purdue University. His research focuses on Cellular Neural Networks, Nonlinear Dynamics, and Chaos Theory, with contributions to circuit theory and complexity science. Chua is a Fellow of the IEEE and has received numerous awards, including the IEEE Gustav Kirchhoff Award (2005) and the Neural Networks Pioneer Award (2000). He holds 7 U.S. patents and 8 honorary doctorates from international universities. Education: B.S., Electrical Engineering, Mapúa Institute of Technology, 1959 M.S., Electrical Engineering, Massachusetts Institute of Technology, 1961 Ph.D., Electrical Engineering, University of Illinois, 1964 Research Interests: Cellular Neural Networks and their applications Nonlinear circuits and chaos theory Complex systems and bifurcation analysis Notable Achievements: Coined the term 'memristor' in 1971, later validated experimentally Founded the Cellular Neural Network (CNN) paradigm Recipient of the Top 15 Most Cited Author in Engineering (2002) Lab & Teams: He leads the NOEL (NOnlinear ELectronics) Lab at UC Berkeley, focusing on nonlinear circuits and systems.

Anna Vlasitsمشاهده پروفایل

استادیار

• Neuroscience
• Ophthalmology
• Neurobiology
• +۳ مورد دیگر

Anna Vlasits, PhD is an Assistant Professor in the Department of Ophthalmology and Visual Sciences at the University of Illinois at Chicago. Her research focuses on understanding retinal neural circuits in health and disease, particularly how retinal neurons process visual information and how this is altered in neurodevelopmental disorders like Fragile X syndrome. She directs the Vlasits Lab, which employs advanced microscopy and computational methods to study retinal function. Her work has received awards from the Knights Templar Eye Foundation, L’Oréal/UNESCO, and the Grass Foundation. Education: PhD in Neuroscience from UC Berkeley (2012) Postdoctoral research at University of Tübingen (Germany) and Northwestern University Research interests include motion and color processing in retinal neurons, synaptic interactions, and retinal dysfunction in neurodevelopmental disorders. Recent studies explore GABAergic modulation of chromatic processing and retinal abnormalities in Fragile X syndrome mouse models. Awards: Knights Templar Eye Foundation Award, L’Oréal/UNESCO Prize for Women in Science, Grass Foundation Award Lab activities include hiring postdoctoral researchers and developing novel imaging techniques for deep-tissue neural recording. Collaborations involve advanced optical tools and interdisciplinary neuroscience approaches.

• Topological Data Analysis
• Machine Learning
• Biomedical Engineering
• +۳ مورد دیگر

Dhananjay Bhaskar is a Research Fellow in the Department of Genetics at Yale School of Medicine, Yale University. His research integrates topological data analysis, machine learning, and mathematical modeling to address problems in biophysics and biomedical research. He holds a PhD in Biomedical Engineering and Sc.M. in Data Science from Brown University, and degrees in Computer Science and Applied Mathematics from the University of British Columbia. His work spans applications such as immune response analysis, epidermal regeneration, IVF embryo selection, and cancer cell migration. Education: PhD Brown University (2021), ScM Data Science (2021), MSc Applied Mathematics (2017, UBC), BSc Computer Science (2015, UBC). Research interests focus on leveraging interdisciplinary methods to understand complex biological systems. Key areas include topological analysis of single-cell data, machine learning for medical diagnostics, and computational modeling of cellular dynamics. His work on glial scar formation and calcium signaling in epidermis regeneration has advanced understanding of tissue repair mechanisms. Notable recognition includes the 2024 Kavli Postdoctoral Fellowship for his project on neuroenergetic principles in C. elegans neural circuitry. Collaborations include work with Smita Krishnaswamy on immune response prediction and Valentina Greco on epithelial regeneration. Publications highlight contributions across neuroscience, immunology, and cell biology, with recent focus on multimodal AI for psychiatry and geometric scattering methods for molecular analysis.

Ümmü Seleme Nizam Bayrakمشاهده پروفایل

پژوهشگر

• Hyperuniformity
• Nonlinear dynamics
• Random matrix theory
• +۳ مورد دیگر

Ümmü Seleme Nizam Bayrak is a Researcher at the Faculty of Electrical Engineering and Information Technology, Ruhr University Bochum, affiliated with the Simply Complex Lab. She holds a Ph.D. in Electrical Engineering and Information Technology from Ruhr University (2019–2025), an M.Sc. in Physics from Boğaziçi University (2014–2019), and a B.Sc. in Mathematics from the same institution (2009–2014). Her research focuses on hyperuniformity , nonlinear dynamics , and complex systems , with applications in materials science, biophysics, and interdisciplinary studies. Recent work explores self-organization in dissipative systems and universality across scales, from quantum dots to biological cells. Her publications highlight advancements in laser-based synthesis techniques and nonlinear systems, reflecting a blend of experimental and theoretical approaches. She actively contributes to the Simply Complex Lab’s projects, investigating emergent phenomena in driven systems and complex networks.

Keith Blowمشاهده پروفایل

استاد

• Photonics
• Optical Networks
• Optical Processing
• +۴ مورد دیگر

Keith Blow is a Professor in Electronic Engineering at Aston University, leading the Photonics Research Group and the Adaptive Networks Communications Research Group. He holds a BA (First Class Honours) in Physics and Theoretical Physics from Cambridge University (1978) and a PhD in Solid State Physics from the Cavendish Laboratory (1981). Prior to joining Aston in 1999, he worked at BT Research Laboratories, focusing on optical fiber technologies and nonlinear effects. His research spans photonics, optical networks, adaptive communication systems, and energy-efficient protocols. Key areas include soliton-based transmission, nonlinear optical processing, and wireless sensor networks. He has supervised 6 students and contributed to over 99 publications, with notable work on soliton crystals, optical frequency combs, and FSO channel optimization. Blow serves on the editorial board of the Journal of Modern Optics and reviews for conferences like the Advanced Photonics Congress. His labs focus on advancing optical communication systems, network efficiency, and sensor network applications, emphasizing practical implementations of theoretical findings.

• Computational Mathematics
• Mathematical Biology
• Numerical Analysis
• +۳ مورد دیگر

Dr. Andreas Aristotelous is an Associate Professor in the Department of Mathematics at the University of Akron's College of Engineering and Polymer Science. His research focuses on computational mathematics, mathematical biology, and numerical analysis, with applications in biomedical modeling, fluid dynamics, and materials science. He specializes in developing and analyzing numerical methods for partial differential equations, particularly those modeling complex biological systems and physical phenomena. His work integrates advanced computational techniques like discontinuous Galerkin methods, hybrid discrete-continuum models, and deep learning approaches to study problems such as biofilm dynamics, SARS-CoV-2 infection mechanisms, and developmental biology processes like dorsal closure in Drosophila. Recent studies emphasize heterogeneity in medical data, immune response modeling, and microgravity biofilm growth. Dr. Aristotelous's publications span computational epidemiology, fluid dynamics, and interdisciplinary applications of mathematical modeling. He actively contributes to the scientific community through peer-reviewed articles and maintains a research website at https://blogs.uakron.edu/aaristot/ .

Sylvain Senéمشاهده پروفایل

استاد

• Computer Science
• Theoretical Computer Science
• Discrete Mathematics
• +۵ مورد دیگر

Sylvain Sené is a Professor of Computer Science at Aix-Marseille University (AMU), affiliated with the Department of Computer Science and Interactions (DII) and the Computer Science and Systems Laboratory (LIS). He leads the ANR-funded project FANs (Foundations of Automata Networks) and focuses on discrete mathematics, theoretical computer science, and computational properties of automaton networks. His research bridges abstract computational models with applications in biology, particularly gene regulatory networks and cellular reprogramming. Research Interests: Automaton networks, Boolean networks, and cellular automata Computational complexity and dynamical systems Discrete mathematics and theoretical computer science Applications in systems biology and genetic networks Key Projects: Principal investigator of the ANR project FANs (2019–2023), focusing on advancing automata network theory Collaborations with CNRS, Chilean universities, and international institutions Advising & Grants: Directed PhD students including Pacôme Perrotin and Martín Ríos Wilson Secured funding through ANR and other national/international grants Labs & Teams: LIS (Computer Science and Systems Laboratory), collaborating with interdisciplinary teams in biology and mathematics.

Yohan Johnمشاهده پروفایل

عضو هیئت علمی

• Dynamical Systems Theory
• Computational Neuroscience
• Cognitive Neuroscience
• +۷ مورد دیگر

Yohan John is a Research Assistant Professor in the Neural Systems Laboratory at Sargent College, Boston University, specializing in computational and systems neuroscience. He holds a PhD from Boston University’s Department of Cognitive and Neural Systems, where he studied under Profs. Dan Bullock and Frank Guenther, focusing on reinforcement learning and timing in the basal ganglia. His postdoctoral work with Prof. Helen Barbas explored cognitive-emotional interactions using computational modeling. Yohan’s research centers on dynamical systems theory as a unifying framework for understanding brain dynamics and psychiatric disorders, particularly how disruptions in neural networks manifest as symptoms. Education: BSc in Physics, St Stephen's College, Delhi (2004) MSc in Physics, Indian Institute of Technology Bombay (2006) PhD in Cognitive and Neural Systems, Boston University (2011) His research interests span dynamical systems theory , computational neuroscience , cognitive-emotional interactions , and psychiatric disorder modeling . He is particularly interested in how brain networks generate stable cognitive and behavioral states (attractors) and how their pathology leads to mental illness. He also investigates broader philosophical and epistemological questions in science, especially the role of metaphor, naming, and boundaries in cognition. Yohan’s recent publications and essays reflect a strong interdisciplinary approach, bridging neuroscience, philosophy, AI, and science communication. His work on semiotic ghosts in LLMs, the power of naming, and visual metaphors in science demonstrates his interest in the intersection of cognition, language, and computation. These writings reveal a consistent theme: understanding complex systems through dynamic, emergent, and metaphorical lenses. Scientific Awards: No scientific awards mentioned in the provided texts. Yohan is actively involved in science outreach, writing for the public on Quora (where he is a top writer in neuroscience) and co-organizing the NeuroLogos YouTube channel, which discusses recent developments in cognitive neuroscience. He has also led discussion groups on dynamical systems, neural representations, and computational theories of mind. While no formal students or grants are listed, his advisory or mentoring roles may exist informally through these educational initiatives. Labs and Teams: Neural Systems Laboratory, Sargent College, Boston University (current affiliation) Emergence Journal Club (organized by Yohan) NeuroLogos YouTube channel (co-organizer and contributor)

• Mathematical Biology
• Biochemical Kinetics
• Systems Biology
• +۳ مورد دیگر

Santiago Schnell is the Provost and Professor of Mathematics at Dartmouth College, with adjunct roles in Biochemistry & Cell Biology and Biomedical Data Science. His research integrates mathematical, computational, and statistical approaches to address complex problems in biomedical sciences, focusing on rigor, reproducibility, and robustness. Key areas include enzyme kinetics, systems biology, and scientometrics. Affiliations: Provost, Dartmouth College Professor of Mathematics, Dartmouth College Adjunct Professor of Biochemistry & Cell Biology Adjunct Professor of Biomedical Data Science Research Interests: Schnell's work bridges theoretical and experimental biology through models for enzyme kinetics, reaction networks, and biomedical data analysis. He pioneers methods to standardize enzyme data reporting (e.g., EnzymeML) and evaluates research university performance metrics. His team explores macromolecular crowding effects, protein aggregation, and interdisciplinary applications like medicine-art interfaces. Publications: Recent work emphasizes re-evaluating quasi-steady-state approximations, analyzing ER stress sensors, and modeling neuroblastoma. His articles span mathematical biology, biochemistry, and systems biology, reflecting expertise in both theory and application. Labs/Teams: Leads a multidisciplinary group at Dartmouth, collaborating globally. Current team includes postdoc Abhishek Mallela and graduate student Isabella Gimon, advancing projects on biochemical kinetics and biomedical data science.