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Laszlo UjjView profile

Associate Professor

• Nonlinear Optics
• Ultrafast Laser Spectroscopy
• Coherent Raman Spectroscopy
• +7 more

Dr. Laszlo Ujj is an Associate Professor in the Department of Physics at the University of West Florida, part of the Hal Marcus College of Science and Engineering. He has been a key contributor to both undergraduate and graduate-level physics education and maintains an active experimental research program in advanced optical spectroscopy. Education: Ph.D. in Physics, University of Szeged, Hungary (2001) Ph.D. in Nonlinear Spectroscopy/Physics, JPTE University of Pecs, Hungary (1990) M.S. in Theoretical Physics, JATE University of Szeged, Hungary (1983) Dr. Ujj's research focuses on nonlinear optics , ultrafast laser spectroscopy , and coherent Raman spectroscopy , with applications in bio-photonics and material analysis . He has developed state-of-the-art laser spectroscopy systems at UWF and previously at the University of Arizona. His work bridges experimental innovation and theoretical understanding in optical science. His recent publications reflect a strong trend toward label-free biological imaging , laser-induced breakdown spectroscopy (LIBS) for elemental analysis, and ultrafast dynamics in biomolecules . These works span disciplines including biophysics, materials science, and analytical chemistry, showcasing interdisciplinary impact. Scientific Recognition: h-index of 14 (Web of Science and Google Scholar) Over 599 citations by 2019 (Web of Science) Google Scholar: 727 citations, i10-index of 17 Presentations at American Physical Society and International Conference on Advanced Vibrational Spectroscopy Dr. Ujj has supervised numerous undergraduate researchers, many of whom have pursued advanced degrees at institutions such as Harvard University , the University of New Mexico , and the University of Arizona . His educational efforts include revising core physics courses and integrating research into the undergraduate curriculum. He teaches a wide range of courses including quantum theory, thermodynamics, electromagnetism, and laser physics. He also leads the Laser Spectroscopy Lab at UWF, where students engage in hands-on research with cutting-edge optical systems. Laboratory and Research Team: Dr. Ujj has developed and maintained advanced laser spectroscopy laboratories at both the University of Arizona and UWF. His lab focuses on coherent Raman microscopy, LIBS, and ultrafast spectroscopy, providing students with direct experience in experimental design, instrumentation, and data analysis.

• Microwave Engineering
• Semiconductor Device Modeling
• Nonlinear Circuit Analysis
• +3 more

Giorgio Vannini is a Full Professor of Electronics at the Department of Engineering, University of Ferrara, where he has been since 2005. His academic career spans over three decades, with prior roles as a Research Fellow and Associate Professor at the University of Bologna. He has held leadership positions including Head of the Engineering Department (2007-2015) and membership in the Academic Senate (2012-2015). Education: Laurea in Electronic Engineering from the University of Bologna (1987), Ph.D. in Electronic and Computer Science Engineering from the University of Bologna (1992). Research: Focused on nonlinear semiconductor device modeling (e.g., GaN HEMTs, III-V FETs), advanced microwave circuit design, and electromagnetic simulation techniques. Key contributions include the Nonlinear Integral Model (NIM) and dynamic I/V characterization systems. Awards: Best Paper Awards at the European Microwave Conference (1995), GAAS98 (1998), and GAAS2001 (2001). Projects: Led over 20 research contracts with industry leaders like Leonardo, Sumitomo, and Huawei, and participated in EU Framework Program initiatives including TARGET and Eurostars. Spin-off: Co-founded MEC srl, an academic spin-off for microwave engineering solutions.

Chiu-Yen KaoView profile

Professor

• Applied Mathematics
• Numerical Analysis
• Partial Differential Equations
• +4 more

Chiu-Yen Kao is the Keck Foundation Professor of Applied Mathematics and Computer Science at Claremont Graduate University. She holds a Ph.D. from the University of California, Los Angeles (2004). Her research focuses on applied mathematics with an emphasis on shape optimization for eigenvalue problems, numerical methods for hyperbolic and dispersive equations, and mathematical biology. She has received notable awards including the Alfred P. Sloan Research Fellowship (2009) and the IEEE Signal Processing Society’s Best Paper Award (2013). Prof. Kao has secured multiple NSF grants, including the RUI: Geometric Optimization Involving PDEs (2022–2025) and Numerical Spectral Study of Elliptic Operators (2018–2022). Her work bridges computational methods with real-world applications, such as medical imaging and biological systems. Key research directions include extremal geometric eigenvalue problems, biomedical modeling (e.g., ciliary muscle thickness), and numerical analysis for PDEs. Educations: Ph.D., University of California, Los Angeles (2004) Her publications span computational approaches to optimization, spectral geometry, and medical applications. Recent work includes studies on flat tori eigenvalues, maximal population models in ecology, and therapies for anthrax treatment. She collaborates across disciplines, evidenced by co-authored papers in ophthalmology and infectious disease. Awards: NSF Grants, Simons Foundation Collaboration Award, IMA Recognition Grants: Over $1M in NSF funding for PDE optimization and numerical studies Labs/Teams: Active in interdisciplinary research groups focusing on mathematical biology and computational PDEs. Her work is disseminated through top journals like SIAM Journals and Journal of Mathematical Biology .

• Numerical Analysis
• Approximation Theory
• Multiresolution Analysis
• +7 more

Francesc Arandiga Llau is a Professor in the Department of Mathematics at the Faculty of Mathematics, Universitat de València, Spain. He is affiliated with the ANIMS (Numerical Analysis, Images, Multiresolution and Simulation) research group, where he conducts research in applied mathematics with a focus on numerical methods and their applications. Education: PhD from Universitat de València (1992), thesis on operator approximation and spectral radius continuity, supervised by Dr. Vicent Caselles Costa. His research interests center on Numerical Analysis , Approximation Theory , and Multiresolution Methods , with significant contributions to WENO schemes , nonlinear interpolation , and image and signal compression . His work often bridges theoretical developments with practical implementations in computational mathematics and engineering. He has made notable advances in the stability, accuracy, and adaptability of reconstruction techniques for piecewise smooth and discontinuous functions. The analysis of his recent publications reveals a consistent focus on high-order numerical methods, particularly in the context of image processing and data compression . His work leverages multiresolution analysis , radial basis functions , and adaptive interpolation to improve accuracy and efficiency. Themes across his articles include monotonicity preservation, error control, and the design of nonlinear schemes that avoid spurious oscillations near discontinuities. There are no scientific awards explicitly mentioned in the provided text. Francesc Arandiga has extensive collaborative research, particularly with scholars such as Rosa Donat, Dionisio F. Yáñez, Pep Mulet, and Antonio Baeza. His work has been supported through various research projects, though specific grants are not detailed in the text. He has advised students, including those who have completed theses under his supervision, although a full list is not provided. He is a key member of the ANIMS research group, which focuses on Numerical Analysis, Images, Multiresolution, and Simulation. This team works on developing and analyzing advanced computational methods for scientific and engineering applications, particularly in the areas of data representation, image processing, and numerical solutions to differential equations.

Eva KopeckáView profile

Professor

• Functional Analysis
• Geometry of Banach Spaces
• Nonlinear Analysis
• +1 more

Univ.-Prof. Dr. Eva Kopecká is a Professor at the University of Innsbruck's Department of Mathematics, Faculty of Mathematics, Computer Science and Physics. She specializes in Functional Analysis, Geometry of Banach Spaces, Nonlinear Analysis, and Combinatorics. Currently teaching Discrete Mathematics and Introduction to Higher Analysis in the 2024 summer semester, she also leads the Research Seminar in Functional Analysis. Her work focuses on projection algorithms, Lipschitz mappings, and fixed point theory. Notable research includes studies on alternating projections, zone diagrams, and geometric embeddings. She has conducted projects funded by the Austrian Science Fund (FWF), including work on Lipschitz mappings and contraction operators. No formal awards are listed, but her contributions to operator theory and functional analysis are widely recognized. Consultation hours are by email appointment.

Eric MillerView profile

Professor

• Signal and Image Processing
• Tomographic Image Formation
• Inverse Problems
• +4 more

Eric Miller is a Professor of Electrical and Computer Engineering at Tufts University's School of Engineering. He also holds adjunct professorships in Computer Science, Biomedical Engineering, and Mathematics. His academic roles include serving as Chair of the Electrical and Computer Engineering department and leading the Lab for Imaging Science Research (LaISR). Miller earned his SB, SM, and PhD in Electrical Engineering from MIT (1990–1994). His research focuses on signal and image processing, particularly inverse problems, tomographic imaging, and applications in medical imaging, environmental monitoring, and security screening. He has pioneered methods like the parametric level-sets (PaLEnTIR) for reconstruction and shape-based inversion algorithms. His work integrates physics-based modeling with computational techniques, addressing challenges in subsurface sensing, biomedical diagnostics, and materials science. Miller is a Fellow of IEEE and a member of honor societies like Tau Beta Pi and Phi Beta Kappa. Over 489 publications reflect his contributions to imaging science, with recent advancements in AI-driven pedestrian behavior analysis and X-ray anomaly detection.

Shaunak BopardikarView profile

Associate Professor

• Cyber-Physical Systems Security
• Autonomous Motion Planning
• Scalable Computation
• +5 more

Shaunak Bopardikar is an Associate Professor in the Department of Electrical and Computer Engineering at Michigan State University (MSU), affiliated with the Center for Connected Autonomous Networked Vehicles for Active Safety (CANVAS). He holds a B.Tech. and M.Tech. from IIT Bombay and a Ph.D. from UC Santa Barbara. His research focuses on scalable computation, cyber-physical systems security, and autonomous motion planning. Previously, he worked as a Staff Research Scientist at United Technologies Research Center and a postdoctoral researcher at UC Santa Barbara. Education: B.Tech. and M.Tech. in Mechanical Engineering (CADA), Indian Institute of Technology Bombay (2004) Ph.D. in Mechanical Engineering (Dynamics and Control), University of California, Santa Barbara (2010) Research Interests: Dr. Bopardikar explores advanced methods for autonomous systems, including randomized algorithms for large-scale optimization, adversarial motion planning, and resilient cyber-physical systems. His work integrates game theory, control systems, and sensor networks to address challenges in autonomous vehicle safety, perimeter defense, and multi-agent collaboration. Key Research Trends: His recent publications emphasize game-theoretic approaches to security, optimal motion planning under uncertainty, and multi-fidelity modeling for sensor systems. He has contributed to frameworks for secure route planning, dynamic sensor selection, and adversarial emulation in cyber-physical systems. Teaching and Advising: He teaches courses in control systems and has an open Ph.D. position for students interested in his research areas. His group focuses on collaborative projects with industrial and academic partners. Labs and Affiliations: His work leverages the CANVAS center to advance connected autonomous vehicle technologies, emphasizing real-world applications of theoretical advancements.

• Motion Planning for Autonomous Vehicles
• Cyber-Physical Systems Security
• Randomized Algorithms
• +3 more

Shaunak D. Bopardikar is an Associate Professor in the Department of Electrical and Computer Engineering at Michigan State University. He specializes in motion planning for autonomous vehicles, cyber-physical systems security, and randomized algorithms. Prior roles include Staff Research Scientist at United Technologies Research Center and Postdoctoral Researcher at the Center for Control Dynamical Systems and Computation. His teaching includes courses like ECE 313 (Control Systems), ECE 416 (Digital Control), and graduate-level courses on game theory and linear systems. Research interests focus on autonomous systems, adversarial motion planning, and sensor selection. Key trends in his work include applying game theory to security challenges and developing scalable algorithms for high-dimensional systems. He leads research on perimeter defense strategies, cooperative robotic systems, and stealth-resilient control mechanisms. Current funding includes the NSF CAREER Award for attack-resilient multi-agent systems. His advising focuses on doctoral candidates interested in his research areas.

• Numerical Analysis
• Computational Mathematics
• Boundary Element Methods
• +3 more

Thomas Führer is a Researcher at TU Wien's Institut für Analysis und Scientific Computing, part of the Faculty of Mathematics and Geoinformation. His primary research focuses on numerical analysis and computational mathematics, with expertise in boundary element methods (BEM), finite element methods (FEM), and adaptive algorithms. He has contributed significantly to the development of efficient solvers and preconditioning techniques for partial differential equations, particularly in FEM-BEM coupling and nonlinear transmission problems. His work emphasizes computational efficiency and optimal convergence rates in adaptive methods. Key research areas include: Adaptive mesh refinement strategies Preconditioning for iterative solvers Isogeometric analysis (IGA) Stokes and Navier-Stokes equations Domain decomposition methods Publications highlight contributions to the theoretical foundations of numerical methods, with a focus on practical implementation and computational performance. Collaborations include Dirk Praetorius, Michael Feischl, and other leading figures in computational mathematics.

Ilkka NissiläView profile

Researcher

• Biomedical Optics
• Neuroimaging
• Optical Tomography
• +7 more

Ilkka Nissilä, Ph.D., is a Staff Scientist at the Department of Neuroscience and Biomedical Engineering , Aalto University. With a career spanning over two decades, his work focuses on diffuse optical tomography , near-infrared spectroscopy , and neonatal brain imaging . He served as a Principal Investigator for the Academy of Finland-funded project Multimodal neuroimaging of children (2016–2018) and has collaborated internationally through visiting researcher appointments. Education : Doctoral Degree in Engineering, Helsinki University of Technology (2004) Master's Degree in Engineering, Helsinki University of Technology (1998) Research Themes : Biomedical optics and optical tomography for brain imaging Neurovascular coupling and hemodynamic responses Developmental neuroscience in infants/children Emotional and sensory processing in early life Algorithm development for image reconstruction Integration of NIRS with TMS/MEG/EEG Article Trends : Recent work combines deep learning with diffuse optical tomography for improved brain imaging Studies maternal mental health impacts on child brain development Advances frequency-domain data utilization and 3D anatomical modeling in neonatal studies Activities : Visiting Researcher (2001–2008) at multiple foreign institutions Conference Presentations Media Impact : 2023: AI-Mind General Assembly participation 2022: Co-developed a skin-stroking device for alcohol cravings 2019: Maternal anxiety effects on infant brain covered in Finnish media Collaborations : International partnerships in biomedical optics Interdisciplinary work with pediatric and psychiatric researchers

• Biomedical Engineering
• Biomedical Image Processing
• Medical Physics
• +5 more

Dr. PELİN ÇİRİŞ is an Assistant Professor in the Department of Biomedical Engineering at the Faculty of Engineering, Akdeniz University, Antalya, Turkey. She also serves as the Director of the Biomedical Technologies Application and Research Center and Deputy Director of the Science and Technology Application and Research Center at Akdeniz University. Previously, she served as Head of Department for Biomedical Engineering from 2014-2020 and continues as Deputy Head since 2016. Her academic career includes significant postdoctoral training at Harvard Medical School and Yale University. Education: Post Doctorate, Harvard University, Harvard Medical School, Brigham And Women's Hospital, Radiology (2013-2015) Post Doctorate, Yale University, School Of Medicine, Diagnostic Radiology (2012-2013) Doctorate, Yale University, School Of Engineering And Applied Science, Biomedical Engineering (2008-2012) Masters (Non-Thesis), Yale University, School Of Engineering & Applied Science, Engineering And Applied Science (2008-2010) Postgraduate, Johns Hopkins University, School Of Engineering, Biomedical Engineering (1998-2000) Undergraduate, Purdue University, School Of Electrical And Computer Engineering, Electrical Engineering (1994-1998) Dr. Çiriş's research spans multiple domains of biomedical imaging and engineering, with a strong focus on magnetic resonance imaging (MRI) techniques and applications. Her work encompasses advanced MRI physics, quantitative imaging methods, and clinical applications across various medical fields. She has made significant contributions to signal modeling in MRI, particularly in cancer imaging contexts including prostate and cervical cancers. Her research also extends to neuroimaging for brain tumor visualization and white matter tractography, as well as cardiac imaging applications for tissue characterization and functional assessment. She has developed innovative approaches like the GAME (Gaussian Augmentation of the Monoexponential) model for analyzing MRI signal decays in cancer tissues. The trajectory of Dr. Çiriş's publication record reveals a progression from fundamental MRI techniques to sophisticated clinical applications. Her early work focused on image reconstruction, parallel imaging, and real-time interventional guidance. Over time, her research evolved to emphasize quantitative approaches for tissue characterization in oncology, particularly in gynecologic and prostate cancers. Recent publications demonstrate expertise in advanced modeling techniques for MRI signal decays, thermometry applications, and image processing methods for clinical decision support. This progression reflects a career dedicated to bridging engineering innovation with practical clinical applications across multiple medical specialties. Scientific Awards: Magna Cum Laude Award (Gynecological cancers), International Society for Magnetic Resonance in Medicine (2015) Magna Cum Laude Award (Prostate cancer), International Society for Magnetic Resonance in Medicine (2015) PhD Candidacy Awarded With Distinction, Yale University (2012) Travel Grant for Top 25 Papers, IEEE International Symposium on Biomedical Imaging (2007) Melvin Judkins Young Investigator Award, American Heart Association (2007) Academic Honors and Dean's Lists, Purdue University (1998) Dr. Çiriş has secured research funding including the project 'Assessing validity of MRI T2* hypoxia measurement in cervical cancer' (2014-2015). She serves as an Editor for the Journal of Magnetic Resonance Imaging since 2015, demonstrating her standing in the MRI research community. She has contributed to academic governance as a jury member for Assistant Professorship Appointment Committee at Akdeniz University. Her leadership extends to directing research centers focused on biomedical technologies at Akdeniz University, where she oversees interdisciplinary teams working on medical imaging technologies. As Director of the Biomedical Technologies Application and Research Center and Deputy Director of the Science and Technology Application and Research Center, Dr. Çiriş leads interdisciplinary teams focused on advancing medical imaging technologies and their clinical translation. Her centers foster collaboration between engineers, physicists, clinicians, and computer scientists to develop innovative solutions for diagnostic and therapeutic challenges in medicine, particularly in the areas of cancer imaging, neuroimaging, and cardiac applications.

Jonathan ChisumView profile

Associate Professor

• Millimeter-Wave Technology
• Antenna Design
• Wireless Communications
• +7 more

Jonathan Chisum is an Associate Professor in the Department of Electrical Engineering at the University of Notre Dame's College of Engineering. His research focuses on developing advanced millimeter-wave (MMW) circuit and antenna systems for wireless communications and sensing, leveraging cutting-edge materials and technologies to achieve unprecedented performance and functionality. MMW artificial materials/metamaterials for GRIN lens antennas in satcom and 5G networks Phase-change materials for programmable antennas and circuits Nonlinear microwave/magnetic transceivers and sensors for low-power applications He has contributed to hybrid optimization workflows for lens design, 3D-printed GRIN lenses, and energy-efficient wireless solutions. His work has been recognized through awards such as the ONR Senior Research Fellow designation. ONR Senior Research Fellow

• Applied Mathematics
• Fractional Calculus
• Special Functions
• +4 more

İsmail Onur KIYMAZ is a Professor at the Faculty of Arts and Sciences, Kırşehir Ahi Evran University , Turkey. His academic journey includes a PhD in Mathematics from Gazi University (2003) and an MSc from Hacettepe University (1997). Research Interests: Applied Mathematics, Fractional Calculus, Special Functions, Differential Equations, Integral Transforms, Numerical Analysis. Students: Supervised 11 theses, including Enes Ata (PhD, 2024), Fatma Karaca Vural (PhD, 2022), and Gizem Tümer (MSc, 2022). Projects: Led 23 projects, such as generalized fractional operators and image encryption algorithms. Collaborated on SEIR epidemic models for vaccine impact analysis. Awards: Recipient of TÜBİTAK UBYT Awards (2013, 2006, 2005, 2003, 2001) and Gazi University Publication Incentive Awards (2005, 2003, 2001). Publications: 40+ articles, focusing on fractional differential equations, generalized special functions, and computational methods.

Sunčica ČanićView profile

Professor

• Applied Mathematics
• Partial Differential Equations
• Fluid-Structure Interaction
• +5 more

Sunčica Čanić is a Full Professor in the Department of Mathematics at the University of California, Berkeley, with prior appointments at the University of Houston. She holds a Ph.D. in nonlinear hyperbolic conservation laws from Stony Brook University (1992). Education: Ph.D. in Nonlinear Hyperbolic Conservation Laws, Stony Brook University (1992) Research Interests: Applied and numerical analysis of partial differential equations Deterministic and stochastic fluid-structure interaction Optimal design of vascular prostheses (stents) Mathematical and computational modeling of bioartificial pancreas Computational modeling of collective states in magnetic colloidal suspensions Microswimmer dynamics Recent Publications: Her recent work focuses on nonlinearly coupled stochastic and deterministic fluid-structure interaction problems, poroelastic materials, and computational optimization of biomedical devices like vascular stents and bioartificial pancreas scaffolds. Articles address existence of solutions, numerical methods, and applications in hemodynamics. Scientific Awards: National Science Foundation Distinguished MPS Lecturer Award (2007) Esther Farfel Award (2018) SIAM Fellow (2014) AMS Fellow (2020) AWM-SIAM Sonia Kovalevsky Lecture Prize (2024) Advising and Grants: Advised Ph.D. student Jeffrey Kuan , who received an NSF Postdoctoral Fellowship (2023). Current research grants include NSF DMS-2408928 (2024-2027) for next-generation stent design and DMS-2247000 (2022-2025) for cell encapsulation modeling. Labs and Collaborations: Collaborates with medical specialists at the Texas Medical Center and UC San Francisco Biodesign Laboratory. Developed computational frameworks for stent design, bioartificial pancreas, and microswimmer dynamics with interdisciplinary teams.

Juan G. RestrepoView profile

Professor

• Complex Networks
• Synchronization
• Nonlinear Dynamics
• +5 more

Juan G. Restrepo is a Professor in the Department of Applied Mathematics at the University of Colorado Boulder, where he maintains an active research program in complex systems and network science. His work bridges theoretical mathematics with applications in physical, biological, and social systems. Professor Restrepo's research focuses on complex network dynamics, particularly synchronization phenomena, nonlinear dynamics and chaos, spread of information and disease in social networks, and criticality in brain networks. His work spans theoretical foundations of network science while addressing real-world applications from cardiac dynamics to social contagion processes. He has made significant contributions to understanding higher-order interactions in networks through hypergraphs and simplicial complexes, revealing new synchronization phenomena and dynamical behaviors. Analysis of his recent publications reveals a strong trajectory toward higher-order network structures, with increasing focus on hypergraphs, simplicial complexes, and topological approaches to network dynamics. His work connects mathematical theory with applications in neuroscience, quantum systems, epidemiology, and social dynamics, demonstrating the unifying power of network science across disciplines. Recent papers show growing integration of machine learning techniques with traditional dynamical systems approaches. Professor Restrepo maintains an active research group investigating fundamental questions in network dynamics while exploring applications to real-world systems. His work on criticality in neural networks and resource transport mechanisms has implications for understanding brain function and developing more efficient networked systems.