جست‌وجوی استاد و پژوهشگر

Daniel Segalmanمشاهده پروفایل

استاد

• Structural Dynamics
• Mechanics of Materials
• Smart Materials and Structures
• +۴ مورد دیگر

Professor Daniel Segalman is affiliated with the Department of Mechanical Engineering at Michigan State University (MSU), within the College of Engineering. Previously, he served as a Senior Scientist at the University of Wisconsin-Madison's Department of Engineering Physics and held a distinguished role as a Member of Technical Staff at Sandia National Laboratories. He earned his PhD in Engineering Mechanics from the University of Wisconsin-Madison in 1978. Research Interests: Segalman specializes in structural dynamics, mechanics of materials, smart materials and structures, vibrations, dynamics, and uncertainty quantification. His work emphasizes contact mechanics, jointed structures modeling, and nonlinear system analysis. He has contributed extensively to the development of Iwan models for joint dynamics and modal analysis techniques for complex systems. Key Contributions: His research spans applications in automotive, petroleum, and aerospace industries, with a focus on predictive simulation methodologies, model validation, and energy dissipation in jointed systems. Notable areas include damping in lap joints, nonlinear modal analysis frameworks, and verification strategies for quasistatic frictional contact. Labs/Teams: While no specific lab names are mentioned, his work aligns with interdisciplinary teams focused on structural dynamics and joint mechanics, reflecting collaborations with institutions like Sandia National Labs and international workshops on jointed structures.

Santosh Vempalaمشاهده پروفایل

استاد

• Theory of Algorithms
• Foundations of Data Science
• Theory of Brain
• +۵ مورد دیگر

Roles and Affiliations: Santosh Vempala is the Frederick G. Storey Chair in Computing and Professor in the School of Computer Science at Georgia Institute of Technology. He also holds courtesy appointments in Mathematics and Industrial and Systems Engineering. He directs the Algorithms, Combinatorics, and Optimization (ACO) PhD program and previously led the Algorithms & Randomness Center (ARC). His work bridges theoretical computer science, data science, and computational neuroscience. Education: PhD in Computer Science from Carnegie Mellon University (1997), advised by Avrim Blum. Postdoctoral fellowship at UC Berkeley (Miller Fellow). Research Interests: Focuses on algorithms, high-dimensional geometry, randomized methods, and applications to brain computation and societal challenges (e.g., Computing for Good). Recent work explores sampling/optimization limits and brain modeling via neural assemblies. His interdisciplinary approach merges theoretical rigor with practical impact in healthcare and technology. Publications Trends: Recent work emphasizes algorithmic diffusion for sampling, neural computation models, and AI evaluation. Key themes include logconcave sampling, optimization complexity, and robust learning. Collaborations span computer science, mathematics, and neuroscience. Awards: Sloan, Guggenheim, ACM, and AMS Fellowships. Recognized for contributions to algorithms and computational theory. Advising & Grants: Advises PhD students and postdocs in optimization, machine learning, and neuroscience. Leads projects like C4G (Computing for Good), addressing global health and societal challenges. Labs & Teams: Founder of ARC and core member of ML@GT. Collaborates with interdisciplinary teams on projects like Brain Assembly Models and OMSCS (Online Master of Science in CS).

André Ranمشاهده پروفایل

استاد مهمان

• Linear Algebra
• Operator Theory
• Systems and Control Theory
• +۳ مورد دیگر

André Ran is a Visiting Professor at the Faculty of Science, Department of Mathematics at Vrije Universiteit Amsterdam. He holds a PhD (1984), Master's (1979), and Bachelor's (1976) in Mathematics from Vrije Universiteit Amsterdam. His research focuses on linear algebra, operator theory, systems and control theory, and linear algebra in spaces with indefinite inner products. He teaches courses in mathematical control theory, linear algebra, and an Introduction to Financial Mathematics. Education: PhD: Semidefinite Invariant Subspaces, Stability and Applications (1984) Master: Spectral Factorization of Weakly Hyperbolic Operator Polynomials (1979) Bachelor in Mathematics (1976) Research Interests: Linear algebra, operator theory, indefinite inner product spaces, systems and control theory, and applications to financial mathematics. Current projects explore spectral analysis and matrix representations in Toeplitz operators with poles on the unit circle. Ancillary Activities: Board Member, Stichting Advancement of Mathematics (1996–present) Extraordinary Professor, North-West University, Potchefstroom (2011–present) Board Member, Stichting Epsilon (2018–present) Recent Work Trends: Recent publications emphasize Toeplitz operators, Fredholm characteristics, matrix equations, and Wiener-Hopf indices. Collaborations span linear algebra and functional analysis. Teaching: Leads courses in Applied Analysis: Financial Mathematics at the MSc level.

Matthias Walterمشاهده پروفایل

استادیار

• Operations Research
• Optimization
• Mathematical Programming
• +۵ مورد دیگر

Matthias Walter is an Assistant Professor in the Department of Mathematics of Operations Research. His research focuses on optimization, mathematical programming, and algorithm design, with applications in transportation, combinatorial optimization, and logistics. He contributes to the SCIP Optimization Suite and has developed the Combinatorial Matrix Recognition Library. His work spans topics such as linear programming relaxations, pseudo-Boolean solving, and multilinear optimization. Key research interests include operations research, integer programming, and algorithmic solutions for complex optimization problems. He has collaborated on projects like optimizing parcel transportation and analyzing congestion games. His recent publications address challenges in flow shop scheduling, graph realization, and pseudo-Boolean functions. Walter actively participates in academic activities, organizing events like the Mathematical Olympiad in Saxony-Anhalt and presenting invited talks on topics such as McCormick relaxations. His contributions to computational tools and theoretical advancements highlight his role in advancing optimization methodologies.

Ron Evansمشاهده پروفایل

استاد

• Number Theory
• Finite Fields
• Character Sums
• +۴ مورد دیگر

Ronald J. Evans is a Professor of Mathematics at the University of California, San Diego (UCSD), affiliated with the Department of Mathematics within the Division of Physical Sciences. His academic career includes roles such as Graduate Vice Chair (2011-2013). He holds a Ph.D. in Mathematics from the University of Illinois (1974). His research focuses on Number Theory, Finite Fields, and Character Sums, with significant contributions to Gauss and Jacobi Sums, as detailed in his influential book *GAUSS AND JACOBI SUMS* (1998). His work integrates algebraic, analytic, and combinatorial methods, addressing topics like hypergeometric functions over finite fields, Pfaffians, and Toeplitz matrices. Evans has authored over 120 publications, including studies on Kloosterman sums, hypergeometric identities, and combinatorial matrix theory. His book has been reviewed in leading journals like *Mathematical Reviews* and *Zentralblatt*. Beyond academia, he is a violist with the Fine Arts Quartet, collaborating with musicians like Ralph Evans. He advocates against academic boycotts of Israel, emphasizing the importance of scientific collaboration over political strife. Key contributions include resolving sign ambiguities in Jacobi sums, analyzing character sums in finite fields, and exploring algebraic structures in quadratic forms. His recent work includes studies on nullities of Toeplitz matrices and class field theory applications. Despite no explicitly listed students or grants, his research has impacted algebraic number theory, combinatorics, and linear algebra.

• Mathematical Logic
• Model Theory
• O-Minimal Structures
• +۶ مورد دیگر

Marcus Tressl is a Lecturer in Pure Mathematics at the University of Manchester , affiliated with the Department of Mathematics. His academic journey includes a PhD and habilitation from the University of Regensburg, and he has been active at Manchester since 2007. Research Interests: Mathematical Logic, Model Theory, O-Minimal Structures, Lattice Ordered Abelian Groups, Boolean Algebras, Differential Algebra, Spectral Spaces, Stone Duality, Commutative Algebra Recent Publications: Focus on distributive lattices, matrix rings, differentially large fields, and applications of model theory to algebraic structures. Teaching: Delivers Mathematical Logic (MATH33021) and supervises MSc projects (MATH61000) , emphasizing LaTeX and mathematical typesetting. Contributions: Authored a book on Spectral Spaces, co-edited proceedings on O-Minimal Structures, and developed resources for Gödel's Incompleteness Theorems, Gröbner Bases, and Neural Network Learning applications.

Anna Stokkeمشاهده پروفایل

استاد

• Combinatorial Representation Theory
• Algebraic Combinatorics
• Mathematics Education
• +۳ مورد دیگر

Dr. Anna Stokke is a Professor of Mathematics at the University of Winnipeg, where she holds the Department of Mathematics and Statistics. She earned her Ph.D. from the University of Alberta, M.Sc. from the University of Manitoba, and B.Sc. from Brandon University. Her research focuses on combinatorial representation theory and algebraic combinatorics, supported by an NSERC Discovery Grant. She has supervised numerous students in research and teaches courses like Calculus, Linear Algebra, and Group Theory. Dr. Stokke is a passionate advocate for math education, co-founding WISE Math and Archimedes Math Schools to improve curriculum and accessibility. She hosts the Chalk & Talk podcast on education and has received prestigious awards including the 3M National Teaching Fellowship (2021) and the PIMS Education Prize (2017). Education: Ph.D. in Mathematics, University of Alberta M.Sc. in Mathematics, University of Manitoba B.Sc. in Mathematics, Brandon University Research Interests: Combinatorial representation theory, algebraic combinatorics, and mathematics education advocacy. Her work includes studies on orthosymplectic groups, cyclic sieving phenomena, and curriculum development. Awards: 3M National Teaching Fellowship Award (2021) Clifford J. Robson Memorial Award for Teaching Excellence (2021) PIMS Education Prize (2017) Clarence Atchison Award for Excellence in Community Service (2015) YMCA-YWCA Women of Distinction Award (2015) Advising & Grants: Supervised over 20 research students, including those in undergraduate and graduate programs. Holds an NSERC Discovery Grant supporting student research. Served as Chair of the Department of Mathematics & Statistics (2017–2022). Labs & Teams: Founded Archimedes Math Schools and co-founded WISE Math. Collaborates with the University of Winnipeg’s Wii Chiiwaakanak Learning Centre on summer math programs. Maintains an active YouTube channel and open-source precalculus review resources.

Shaoning Hanمشاهده پروفایل

استادیار

• Mathematical Optimization
• Mixed-Integer Nonlinear Programming
• Nonsmooth Optimization
• +۳ مورد دیگر

Shaoning Han is a Presidential Young Professor (Assistant Professor) in the Department of Mathematics and the Institute of Operations Research and Analytics (IORA) at the National University of Singapore (NUS). He previously held a postdoctoral position at the University of Southern California (USC), working under Prof. Jong-Shi Pang. His research focuses on mathematical optimization, including mixed-integer nonlinear programming, nonsmooth optimization, and their applications in operations research and data science. Han earned his Ph.D. in Industrial Engineering from USC under Prof. Andrés Gómez and a B.S. in Mathematics from the University of Science and Technology of China (USTC). His work emphasizes advancing optimization methodologies, particularly for problems involving complementarity constraints, indicator variables, and sparsity. Recent contributions include progressive MIP methods for indefinite QPs, real-time solutions for banded matrix problems, and convexification techniques for nonconvex optimization. Han is actively recruiting PhD students interested in mathematical optimization. Research Highlights: His articles span theoretical advances (e.g., epi-stationarity analysis, parametric variational inequalities) and applied frameworks (e.g., robust SVMs, binarized neural networks). Key themes include polynomial-time solvability of MRFs, convex relaxations for low-rank functions, and sparse signal estimation. Awards: Third Place, INFORMS JFIG Paper Competition (2023) Journal of Global Optimization Best Paper Honorable Mention (2023) Teaching: Courses include MA5243 (Advanced Mathematical Programming) and MA3252 (Linear and Network Optimization). Labs/Teams: Active member of IORA, NUS’s Smart Nation Research Cluster.

Pablo Parriloمشاهده پروفایل

استاد

• Optimization
• Game Theory
• Convex Algebraic Geometry
• +۲ مورد دیگر

Pablo A. Parrilo is the Joseph F. and Nancy P. Keithley Professor of Electrical Engineering at the Massachusetts Institute of Technology, affiliated with the Department of Electrical Engineering and Computer Science and the Laboratory for Information and Decision Systems. His research bridges optimization, control theory, and algebraic geometry, focusing on convex optimization, semidefinite programming, and computational methods. Dr. Parrilo develops theoretical foundations and computational tools like SOSTOOLS for solving polynomial optimization problems and provides key insights into system robustness and control synthesis. Research Interests: Dr. Parrilo's work centers on algebraic techniques for optimization and control, including sum-of-squares decompositions, game theory, and convex algebraic geometry. He explores applications in machine learning, autonomous systems, and combinatorial optimization. Publications Focus: His recent publications demonstrate advances in stochastic optimization, geometric algorithms, and non-convex optimization, with consistent themes in efficient computation and theoretical guarantees.

Habib Ammariمشاهده پروفایل

استاد

• Applied Mathematics
• Mathematical Physics
• Medical Imaging
• +۶ مورد دیگر

Habib Ammari is a Professor of Applied Mathematics at ETH Zurich, leading research in wave propagation, mathematical imaging, and metamaterials. He previously served as Director of Research at École Normale Supérieure in Paris. His academic journey includes a Bachelor's, Master's, and PhD from École Polytechnique (1992–1995), followed by a Habilitation from Université Pierre & Marie Curie (1998). Research Interests: Mathematics of subwavelength physics and metamaterials Bio-inspired imaging and neural natural intelligence Multiscale biomedical imaging and super-resolution techniques Publications: His work spans over 300 papers and 9 books, including seminal contributions to inverse problems, plasmonics, and imaging modalities. Recent research focuses on non-Hermitian skin effects, quantum integrable systems, and Anderson localization in subwavelength regimes. Awards and Fellowships: European Research Council Advanced Grant (2010) Kuwait Prize in Basic Sciences (2013) Khwarizmi International Award (2015) Fellowships: American Mathematical Society (2022), Academia Europaea (2021), European Academy of Sciences (2018) Advising: Supervised 40+ PhD students and 27 postdocs, many recipients of prestigious awards like the ETH Medal and ECCOMAS PhD Award. Labs and Collaborations: Active in international initiatives including CISM courses, NSF-CBMS conferences, and collaborations with institutions like Hong Kong Institute for Advanced Study and MSRI.

Micheline Soleyمشاهده پروفایل

استادیار

• Quantum Computing Algorithms
• Atomic and Molecular Physics
• Ultracold Chemistry
• +۴ مورد دیگر

Micheline Soley is an Assistant Professor at the University of Wisconsin–Madison, affiliated with the Department of Chemistry and Department of Physics. She leads the Soley Research Group, focusing on quantum computing algorithms, ultracold collisions, and PT symmetry. Her work bridges chemistry, physics, and data science. Education: PhD in Chemical Physics, Harvard University (2020) Yale Quantum Institute Postdoctoral Fellow (2020–2022) Bachelor of Science in Chemistry and Music, Yale University (2013) Research Interests: Dr. Soley’s research explores quantum computing frameworks, tensor networks, and ultracold chemical systems. Her group develops tools for quantum simulation and investigates fundamental quantum phenomena like PT-symmetry and bound states in the continuum. Awards: American Chemical Society Kavli Emerging Leader (2023) NSF Graduate Research Fellowship (2014) Fulbright Fellowship to Germany (2013–2014) Advising & Labs: The Soley Group includes postdocs, graduate students, and undergraduates. Current projects involve hybrid quantum processors and biomolecular dynamics modeling. The group collaborates with the Data Science Institute and hosts interdisciplinary initiatives. Labs/Teams: Active in the UW Quantum Computing Hub and the Chemistry-Physics Interface Research Network.

Alfonso Agnewمشاهده پروفایل

استاد

• Quantum Gravity
• General Relativity
• Mathematical Physics
• +۴ مورد دیگر

Dr. Alfonso Agnew is a Professor in the Department of Mathematics at California State University, Fullerton. He holds a PhD in Mathematics from Oregon State University (1999), an MS from the same institution (1996), and dual BA/BS degrees in Mathematics and Physics from CSUF (1994). His research focuses on theoretical physics and mathematical physics, with emphasis on quantum gravity, general relativity, twistor theory, and affine differential geometry. Notable contributions include work on gravitational wave analysis using LIGO data, twistor structures in biquaternionic spaces, and historical studies of geometric theorists like Gheorghe Tzitzeica. Recent publications (2001–2022) explore topics such as matrix projective spaces, semiclassical density of states in quantum systems, and applications of twistor theory. He regularly teaches advanced courses like Vector & Tensor Analysis and General Relativity. Though no specific awards or grants are listed, his extensive publication record reflects deep contributions to mathematical physics. No student advisees are documented in the provided materials.

Paul von Bünauمشاهده پروفایل

استاد مدعو

• Artificial Intelligence
• Healthcare Technology
• Machine Learning
• +۴ مورد دیگر

Dr. Paul von Bünau serves as Managing Director (CEO) of IDALab, a strategic advisory firm focused on artificial intelligence in healthcare and biotechnology. He concurrently holds an adjunct academic role at Europa-Universität Viadrina Frankfurt (Oder), where he teaches courses on AI strategy and regulatory compliance in healthcare. His educational background includes a PhD in Machine Learning (TU Berlin), M.Sc. in Pure Mathematics (University of St Andrews), and B.Sc. in Computer Science (University of Potsdam). **Professional Background**: Paul provides strategic AI guidance to multinational healthcare companies, biotech startups, and medical device manufacturers. Key engagements include building AI innovation units for a medtech company, accelerating drug discovery through AI-driven R&D, and developing AI tools for healthcare market access under EU regulations. His approach emphasizes aligning technical solutions with organizational needs and regulatory landscapes. **Research & Teaching**: At Viadrina, he delivers seminars on AI strategy (2024) and regulatory compliance in healthcare AI (2025). His research focuses on non-stationary data analysis, clinical data harmonization, and AI applications in neuroscience. Recent work includes a validated clinical data pipeline for scalable AI deployment (JMIR Medical Informatics, 2023) and algorithms for stationary subspace analysis (Physical Review Letters, 2009). **Key Takeaways from Projects**: Companies with strong engineering cultures often underestimate the cultural and structural changes required for AI integration. Rapid prototyping, talent alignment, and cross-disciplinary teams (e.g., AI + healthcare experts) are critical for success. His work highlights the transformative potential of AI in healthcare while emphasizing ethical and regulatory considerations.

Alberto Condoriمشاهده پروفایل

استاد

• Mathematical Analysis
• Data Science
• Mathematical Epidemiology
• +۵ مورد دیگر

Dr. Alberto A. Condori is a Professor in the Department of Mathematics at Florida Gulf Coast University (FGCU), part of the College of Arts & Sciences. He teaches courses at all levels of the undergraduate and graduate curriculum, focusing on developing problem-solving and critical-thinking skills through data-driven learning and teamwork-based activities. Dr. Condori's research spans multiple mathematical disciplines. Originally focused on Mathematical Analysis, his interests have expanded to include Data Science, Mathematical Epidemiology, Linear Algebra, and Graph Theory. His work explores the intersection between Complex Analysis, Linear Algebra, Operator Theory, and Approximation Theory. Recent projects include co-authoring 'Recent Progress in Function Theory and Operator Theory' (2024), securing a grant to study West-Nile virus in Lee County (2024-2025), and applying spectral graph theory to human trafficking data in Florida. Dr. Condori has been recognized with several prestigious awards: 2023-2024 Senior Faculty Teaching Excellence Award at FGCU 2023-2024 Faculty Excellence in Mentoring Award He actively mentors students in research across mathematics and interdisciplinary topics, facilitating their participation in local and national conferences. Dr. Condori also mentors junior faculty to ensure their professional success and retention. His service includes co-organizing professional conferences, refereeing journal articles, publishing reviews for the American Mathematical Society, and serving as Graduate Program Coordinator for six years at FGCU.

Cara Brooksمشاهده پروفایل

دانشیار

• Inverse Problems
• Ill-posed Problems
• Numerical Analysis
• +۷ مورد دیگر

Cara Brooks is an Associate Professor in the Department of Mathematics at Florida Gulf Coast University's College of Arts & Sciences. She holds a Ph.D. in Mathematics from Michigan State University and serves as Faculty Lead for the Women in STEM Living Learning Community (WiSTEM LLC). Her educational background includes a Ph.D. in Mathematics from Michigan State University. Dr. Brooks specializes in mathematical research focusing on inverse and ill-posed problems, numerical analysis, linear algebra, matrix analysis, and pseudospectra. Her work particularly addresses regularization methods for Volterra equations and sequential algorithms. She has made significant contributions to understanding polynomially isometric matrices, resolvent criteria for normality, and developing improved regularization techniques for ill-posed problems. Her publication record shows consistent scholarly output from 2010 to 2021, with research primarily centered around inverse problems and numerical methods. The publications demonstrate a clear progression in her field, moving from fundamental theoretical work to increasingly sophisticated regularization approaches for challenging mathematical problems. As an educator, Dr. Brooks teaches across the mathematics curriculum including Calculus, Differential Equations, Linear Algebra, Real Analysis, and Numerical Analysis. She also teaches specialized courses such as Matrix Analysis and an Introduction to Numerical Analysis and Scientific Computing. Dr. Brooks maintains an active role in supporting women in STEM fields through her leadership of the Women in STEM Living Learning Community, demonstrating her commitment to both academic excellence and student development.