جست‌وجوی استاد و پژوهشگر

• Analytic Number Theory
• Prime Number Distribution
• Additive Number Theory
• +۵ مورد دیگر

Prof. Alessandro Zaccagnini is an Associate Professor at the Department of Mathematical, Physical and Computer Sciences, University of Parma. He graduated in Mathematics in 1989 and obtained his PhD in 1994, focusing on Analytic Number Theory. His academic journey includes a competitive appointment as Associate Professor in 2004 after serving as a Researcher from 1993 to 2004. Education : PhD in Mathematics (1994), University of Parma Academic Positions : Researcher (1993–2004), Associate Professor (2004–present) His research spans Analytic Number Theory, focusing on additive problems like the Hardy-Littlewood conjectures, Goldbach representations, prime distribution in short intervals, Diophantine equations with primes, and Mertens' constants. He also contributes to Cryptography education. Key Research Areas Additive Number Theory (Goldbach, Goldbach-Linnik problems) Prime Distribution in Short Intervals Diophantine-type Problems with Prime Variables Mertens' Constant for Arithmetic Progressions Cryptography and Mathematical Education Recent publications include studies on Laplace convolutions, Cesàro averages for additive problems, and educational materials using everyday objects for mathematical teaching. His work bridges theoretical research (e.g., Riemann zeta function) and practical applications (e.g., cryptographic protocols). Teaching responsibilities include Mathematical Analysis , Cryptography , and Elementary Number Theory for undergraduate and graduate programs in Mathematics and Computer Science.

Giovanni Francesco Basiniمشاهده پروفایل

استاد

• Private Law
• Succession Law
• Family Law
• +۲ مورد دیگر

Giovanni Francesco Basini is Full Professor of Private Law (IUS/01) at the University of Parma, where he has taught since 2005 and currently serves as Director of the Department of Law, Political and International Studies for the 2024–2027 term. He is also a member of the editorial board of the journal Responsabilità civile e previdenza . Education & Academic Career Born in Reggio Emilia, 25 May 1965. Appointed Full Professor of Private Law at the University of Parma in autumn 2005. Previously taught Institutions of Private Law at the Faculty of Law of Parma. Regular visiting lecturer at Bocconi University (Milan) from 2001/2002 to 2017/2018 (Private Law). Lecturer in “Successioni per causa di morte” at the School of Specialization for the Legal Professions, Universities of Pavia & Bocconi, 2017/2018–2022/2023. Research Focus Basini’s scholarship concentrates on four interlocking domains: Succession due to death and generational transfer of family wealth – analysing intestate and testamentary succession, forced heirship, and reform proposals. Family law – custody, filiation, recognition of children (including so-called “incestuous” children), grandparents’ visitation rights, and the assignment of the family home. Obligations and contracts – limitation clauses, contract invalidity, and the intersection of private law with artistic and cultural heritage. Art and cultural-heritage law – legal regulation of cultural assets within private-law frameworks. Publication Trends Across more than 180 works, Basini has produced extensive monographic contributions, journal articles, and commentaries. Late-career outputs (2020–2024) evidence a sustained focus on succession reform, the legal status of vulnerable persons, and the interplay between family relationships and property transmission. Earlier works (2006–2015) chart evolving Italian jurisprudence on spousal and filiation rights, often highlighting constitutional tensions and de iure condendo perspectives. Editorial & Institutional Service Member, Editorial Board, Responsabilità civile e previdenza . Director, Department of Law, Political and International Studies, University of Parma (2024–2027). Frequent keynote speaker and trainer for continuing legal-education programs aimed at practitioners. Teaching & Advising At the five-year single-cycle Master’s Degree in Law at Parma, Basini currently teaches: Civil Law I – Successions and Donations (2nd year) Family Law (2nd year) Institutions of Private Law (1st year) He maintains weekly office hours and accepts appointments ad hoc via e-mail, underscoring a strong commitment to student mentoring.

Miroslav Bulíčekمشاهده پروفایل

دانشیار

• Partial differential equations
• Continuum thermodynamics
• Mathematical modelling
• +۳ مورد دیگر

Miroslav Bulíček is an Associate Professor at the Mathematical Institute of the Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic. He has been with Charles University since 2006, progressing from Researcher to Senior Assistant Professor (2012-2021) and currently serving as Associate Professor since January 2022. He is also a Senior Researcher at the University Center for Mathematical Modeling, Applied Analysis and Computational Mathematics (MathMac) since 2014. His educational background includes a habilitation in Mathematics-Mathematical Analysis from Charles University (2021), a Ph.D. in Mathematical and Computational Modeling from Charles University (2003-2006), and a Master's degree in Mathematical modeling in physics and technology from Charles University (1998-2003). Bulíček's research focuses on Partial differential equations, Continuum thermodynamics, and Mathematical modelling . His work primarily addresses the mathematical analysis of nonlinear systems describing flows of incompressible fluids, with particular emphasis on thermodynamically compatible models, implicit constitutive relations, and viscoelastic rate-type fluids. He has made significant contributions to the understanding of existence, uniqueness, and regularity of solutions to complex fluid models, especially those describing far-from-equilibrium systems in continuum thermodynamics. His recent publications demonstrate a strong focus on advanced mathematical analysis of fluid models with applications in material sciences. The research trends show increasing sophistication in handling non-Newtonian fluids, stress-diffusion phenomena, and thermodynamically consistent models. His work bridges pure mathematical analysis with practical applications in continuum mechanics, particularly in the analysis of viscoelastic rate-type fluids with stress diffusion. NEURON Fund for Support of Science Award (2012) for the project "Qualitative analysis of incompressible Navier-Stokes-Fourier equations" Czech Mathematical Society Award for young researchers (2014) for publications during 2009-2013 Bulíček has successfully supervised multiple PhD students including Mark Dostalík, Michael Zelina, Michal Bathory, and Tomáš Los. He serves as principal investigator for the GAČR project 20-11027X "Mathematical analysis of partial differential equations describing far-from-equilibrium open systems in continuum thermodynamics" (2020-present). His research has been supported by various grants including GAČR project 18-12719S, GAČR 16-03230S, and ERC-CZ no. LL1202, demonstrating sustained funding for his research program. He is actively involved in the University Center for Mathematical Modeling (MathMac) and has organized several international conferences and workshops, including the "Modelling, partial differential equations analysis and computational mathematics in material sciences" conference in Prague (2024) and the "Mathematical Aspects of Fluid Flows" EMS School in Kácov (2024), contributing significantly to the mathematical community in fluid dynamics and partial differential equations.

• Clinical Neurology
• Neurodegeneration
• Parkinson's Disease
• +۱۰ مورد دیگر

Günter Höglinger is a Professor at the Ludwig Maximilian University of Munich , affiliated with the Department of Neurology in the Medical School. As a Director of the Neurological Clinic and Polyclinic at Klinikum der LMU, he bridges clinical and basic research to develop novel diagnostics and therapies for neurodegenerative diseases. He is a full member of the GSN and a regular member of the MCN. Fields of Interest : Clinical Neurology, Neurodegeneration, Parkinson’s Disease, Alpha-synuclein, Tau Protein, Biomarker Discovery, Neuroimaging, Genetics/Epigenetics, Cellular Neuroscience. His research focuses on diseases linked to protein aggregation, particularly alpha-synucleinopathies (e.g., Parkinson’s disease, Lewy body dementia, multiple system atrophy) and tauopathies (e.g., frontotemporal dementia, progressive supranuclear palsy, corticobasal degeneration). He employs therapeutic trials, clinical cohorts, biomarker discovery, neuroimaging, and genetic/epigenetic analyses to investigate prion-like propagation of misfolded proteins and resilience factors. Recent work includes clinical trials on tau-targeting therapies (e.g., tilavonemab, gosuranemab) and neuroimaging studies of tau deposition. Selected Publications Trends : His earliest listed work (2011) explores genetic risk factors for progressive supranuclear palsy, while recent studies (2021–2022) emphasize clinical trial outcomes and neuroimaging biomarkers for tauopathies. Contact : Guenter.Hoeglinger@med.uni-muenchen.de

• Computer Science
• Formal Methods
• Automata Theory
• +۳ مورد دیگر

Dr Daniel Hausmann is a Lecturer in the Department of Computer Science at the University of Liverpool, affiliated with the School of Electrical Engineering, Electronics and Computer Science. His research focuses on formal methods, automata theory, and game theory, with applications to reactive synthesis and modal fixpoint logics. Current academic rank: Lecturer Key research areas: Formal verification, automata theory, game-based synthesis algorithms Contributions: Development of tools like COOL-MC and COOL 2 for modal fixpoint logics Recent research trends involve solving complex games for system verification, optimizing symbolic algorithms, and advancing coalgebraic approaches to satisfiability checking. His work spans both theoretical foundations and practical implementations for formal verification systems. Notable collaborations include researchers at the intersection of computer science and logic (e.g., N. Piterman, L. Schröder). The University of Liverpool's Computer Science department supports his work through academic infrastructure and research partnerships.

• Actuarial Science
• Insurance
• Risk Management
• +۳ مورد دیگر

Gee Lee is an Associate Professor in the Department of Statistics & Probability and the Department of Mathematics at Michigan State University. His work bridges actuarial science with advanced statistical and machine learning methodologies, focusing on practical applications for insurance risk modeling. PhD, University of Wisconsin-Madison Associate (ASA), Society of Actuaries His research centers on insurance loss modeling for rate-making and loss reserving, multivariate insurance coverage optimization, dependence structure analysis, and integrating machine learning into actuarial frameworks. Current projects include deep neural networks for claim prediction, unstructured data analysis, and multivariate coverage optimization. Recent publications highlight trends in crop insurance modeling (2025), regularization techniques (2024), multivariate risk retention strategies (2023), textual data analysis (2022), copula regression (2022), and reinsurance game theory (2022). Earlier works explore shrinkage methods, word embeddings, longitudinal claims, healthcare data, and deductible ratemaking. Gee Lee supervises MS and PhD students in actuarial science. Former advisees include Leonard Korreshi (2024), Qiaozhen Qian (2023), and Scott Manski (2020, co-advised). He also supports undergraduate research through MSU’s REU program and directed study courses.

• Learning Theory
• Neural Networks
• Deep Learning
• +۶ مورد دیگر

Professor Dingxuan Zhou is a distinguished academic serving as Professor and Head of School of Mathematics and Statistics at The University of Sydney, joining the institution on August 29, 2022. He is also a member of The Net Zero Institute and has held significant editorial positions, including editor-in-chief of the journal "Analysis and Application" of "Mathematical Foundations of Computing" and serving on the editorial boards of over ten international journals. Educational Background: BSc in Mathematics from Zhejiang University, China (1988) PhD in Mathematics from Zhejiang University, China (1991) Professor Zhou's research spans learning theory, neural networks, wavelet analysis, and approximation theory, with his current focus on the theory of deep learning. His work aligns with the Faculty of Science Research Strengths in Complex Systems, Precision and Digital Health, Data and Decisions, and National Security. His research demonstrates a consistent progression from foundational mathematical theory to cutting-edge applications in machine learning and artificial intelligence, with particular emphasis on understanding the theoretical underpinnings of neural networks and deep learning systems. His extensive publication record reveals a strong trend toward distributed learning frameworks, approximation theory for neural networks, and the mathematical foundations of deep learning. Recent work focuses on federated learning, transformers, physics-informed neural networks, and the theoretical analysis of over-parameterized networks, reflecting the evolving landscape of machine learning research with increasing emphasis on theoretical guarantees and practical applications. Scientific Awards: Humboldt Research Fellowship (1993) Fund for Distinguished Young Scholars from the National Science Foundation of China (2005) Highly-cited Researcher by Thomson Reuters/Clarivate Analytics (2014-17) World's Top 2% Scientist by Stanford University (2021, 2022, 2023) Professor Zhou has demonstrated exceptional leadership in research and mentorship, having conducted over 40 research grants as Principal Investigator, supervised more than 20 PhD students, and co-organized over 20 international conferences. His collaborative approach is evident in his extensive co-authorship network across multiple institutions globally. He has also served in significant administrative roles including Head of Department of Mathematics (2006-12), Associate Dean of School of Data Science (2018-22), and Director of the Liu Bie Ju Centre for Mathematical Sciences (2019-22) at City University of Hong Kong.

Laurent Condatمشاهده پروفایل

پژوهشگر

• Optimization
• Convex Relaxation
• Stochastic Algorithms
• +۵ مورد دیگر

Laurent Condat is a Senior Research Scientist at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia, where he conducts research in optimization algorithms and their applications. He is affiliated with the College of Engineering, Department of Computer Science, and has previously held research positions at CNRS in France, working at GREYC in Caen and GIPSA-Lab in Grenoble. Dr. Condat received his PhD in 2006 from Grenoble Institute of Technology, followed by a 2-year postdoc in Munich, Germany. He was recruited as a permanent researcher by CNRS in 2008 and has been on leave from CNRS since November 2019 to work at KAUST. In February 2025, he was promoted to 'chargé de recherche hors classe' (senior research scientist) by CNRS. His research focuses on deterministic and stochastic optimization algorithms, convex relaxations, and applications to machine learning, signal and image processing. His work spans theoretical foundations of optimization methods to practical implementations for distributed and federated learning systems. He has developed several influential algorithms including RandProx, TAMUNA, and LoCoDL that address communication efficiency in distributed optimization. His recent publications demonstrate strong trends in communication-efficient distributed optimization, with particular emphasis on federated learning, compression techniques, and local training methods. His work bridges theoretical optimization with practical machine learning applications, showing consistent innovation in algorithmic design for large-scale problems. Best reviewer award at AISTATS 2025 Meritorious Service Award from Mathematical Programming Stanford's list of world's top 2% most influential scientists Dr. Condat has co-supervised PhD students including Daniele Picone and Julien Baderot. He serves as an Associate Editor for IEEE Transactions on Signal Processing and has presented his work at numerous international conferences including plenary talks at major optimization workshops. His research is supported through KAUST funding and collaborative projects with researchers worldwide.

Romana Kadzikowska-Wrzosekمشاهده پروفایل

استاد

• Personality Psychology
• Motivational Psychology
• Self-regularization
• +۴ مورد دیگر

Romana Kadzikowska-Wrzosek is a Professor of Psychology at SWPS University and serves as the Dean of the Faculty of Psychology in Sopot. She is affiliated with the Department of Basic Psychology and Institute of Psychology, focusing on personality and motivational psychology, particularly self-regulation, goal setting, and action planning. Research Interests Her research explores: Self-Regulation: Investigating mechanisms linking willpower, autonomy, and action control in adolescents and adults. Chronobiology and Sleep Research: Examining bedtime procrastination, chronotype influences on sleep patterns, and mental health outcomes. Motivational Psychology: Applying Self-Determination Theory to understand autonomous vs. controlled motivational regulations in diverse populations. Scientific Contributions She authored the book Willpower. Autonomy, Self-Regulation, and Action Control (2013) and published extensively in journals like Personality and Individual Differences and Current Psychology . Her work bridges personality theory with practical health and behavioral outcomes. Teaching and Leadership At SWPS University, she teaches personality psychology and leads the Faculty of Psychology in Sopot, emphasizing interdisciplinary collaboration and research-driven education.

Nan Chenمشاهده پروفایل

دانشیار

• Applied Mathematics
• Uncertainty Quantification
• Data Assimilation
• +۷ مورد دیگر

Nan Chen is an Associate Professor at the Department of Mathematics, University of Wisconsin-Madison, and a faculty affiliate of the Institute for Foundations of Data Science (IFDS), a multi-University TRIPODS Phase II Initiative. His research spans applied mathematics with applications in atmosphere-ocean science, climate dynamics, and data science. Education: PhD from Courant Institute of Mathematical Sciences (CIMS) and Center of Atmosphere and Ocean Science (CAOS), New York University (NYU), May 2016 Postdoc research associate at CIMS, NYU (June 2016-May 2018) Master's degree from School of Mathematical Sciences, Fudan University, Shanghai Undergraduate in Mechanical Engineering, Fudan University, Shanghai Visited Department of Scientific Computing at Florida State University working with Dr. Max Gunzburger and Dr. Xiaoming Wang Nan Chen's research focuses on contemporary applied mathematics, particularly modeling complex systems, stochastic methods, numerical algorithms, and data science. He specializes in uncertainty quantification (UQ), data assimilation, and developing statistically accurate algorithms to address the curse of dimensionality in large-dimensional complex dynamical systems with strong non-Gaussian features. His work has significant applications in atmosphere-ocean science, including predicting phenomena such as the Madden-Julian Oscillation (MJO), monsoons, El Niño Southern Oscillation (ENSO), and sea ice dynamics. He has also extended his research to material science, neuroscience, and other complex systems. His recent publications demonstrate expertise in inverse problems, wave equations, numerical methods, and data compression techniques that blend mathematical theory with practical applications. Dr. Chen has authored a book titled "Stochastic Methods for Modeling and Predicting Complex Dynamical Systems --- Uncertainty Quantification, State Estimation, and Reduced-Order Models" published by Springer, and a tutorial paper "Taming Uncertainty in a Complex World: The Rise of Uncertainty Quantification — A Tutorial for Beginners" in the Notices of the AMS. Professional Activities: Organizing "Data Meets Dynamics: Workshop on Data Assimilation for Complex Systems and Applications" (August 21-22, 2025) Author of two articles in Elsevier's Reference Module in Earth Systems and Environmental Sciences Participant in Wisconsin Science and Computing Emerging Research Stars (WISCERS) program Judge for Outstanding Student Paper Award (OSPA) program at American Geophysical Union (AGU) fall meetings Involved in Madison Experimental Mathematics Lab (MXM Lab) Dr. Chen actively mentors undergraduate students for research during semesters and summers, encouraging them to present at the UW undergraduate symposium. He also offers reading and independent study courses for interested undergraduates. He is currently seeking highly motivated PhD students to join his research group with possible Research Assistantship support.

• Fluid structure interaction
• Calculus of Variations
• Partial differential equations
• +۱ مورد دیگر

Malte Laurens Kampschulte serves as Assistant Professor at the Department of Mathematical Analysis, Faculty of Mathematics and Physics, Charles University in Prague. He leads research within S. Schwarzacher's fluid structure interaction group and the OP JAK project FerrMion, following his role as Substitute Professor at the University of Leipzig during Summer 2024. His academic credentials include: B.Sc in Mathematics (2009) and Computer Science (2010) from RWTH Aachen M.Sc in Mathematics (2012) from RWTH Aachen Ph.D. in Mathematics (2018) with thesis "Gradient flows and a generalized Wasserstein distance in the space of Cartesian currents" Dr. Kampschulte's research centers on fluid structure interaction, calculus of variations, partial differential equations, and geometric measure theory. His work examines variational aspects of Eulerian-Lagrangian frameworks, relaxation methods for generalized solutions, topological invariants in PDEs, and current transport on manifolds. This integrated approach bridges theoretical analysis with physical applications in continuum mechanics. Analysis of his 2023-2024 publications reveals concentrated focus on three-dimensional fluid-structure systems with viscoelastic solids, compressible fluids, and self-collision phenomena. Key contributions include global weak solution frameworks for contact problems, variational approaches to hyperbolic evolutions, and regularity analysis for free surface dynamics—demonstrating both mathematical rigor and physical relevance. As Principal Investigator for the PRIMUS grant "Qualitative and quantitative Analysis for non-linear non-uniformly elliptic models" (previously held by Anna Balci), he oversees active research funding while mentoring through an open PostDoc position. His leadership extends to the FerrMion project where he develops mathematical frameworks for fluid-matter interactions. Based in the Department of Mathematical Analysis at Charles University, Dr. Kampschulte collaborates within S. Schwarzacher's research group to advance mathematical understanding of fluid-structure systems through both theoretical innovation and computational modeling.

Kristen A. Carpenterمشاهده پروفایل

استاد

• American Indian Law
• Indigenous Peoples' Rights
• Cultural Property Law
• +۷ مورد دیگر

Kristen A. Carpenter serves as Council Tree Professor of Law and Director of the American Indian Law Program at the University of Colorado Law School. She is a leading scholar in American Indian Law, Indigenous rights, cultural property, and human rights with extensive international engagement. Professor Carpenter's research focuses on Indigenous peoples' rights in domestic and international contexts, with particular expertise in cultural property, religious freedom, language rights, and tribal sovereignty. Her work bridges legal theory with practical applications for Indigenous communities, examining how legal frameworks can better serve Indigenous self-determination and cultural preservation. Her scholarship reveals a consistent trajectory toward strengthening Indigenous rights through multiple legal frameworks. Early work established foundational concepts in cultural property and religious freedom, while more recent publications address emerging challenges in language preservation, international diplomacy, and migration. A significant portion of her research examines the practical implementation of the United Nations Declaration on the Rights of Indigenous Peoples. North American member of the UN Expert Mechanism on the Rights of Indigenous Peoples (EMRIP), appointed in 2017 Justice of the Shawnee Tribe's inaugural Supreme Court Regular speaker at UN forums including the International Year of Indigenous Languages kickoff Author of influential casebook Case and Materials on Federal Indian Law Professor Carpenter actively engages with Indigenous communities through teaching, scholarship, and service. She directs the American Indian Law Program at Colorado Law, teaches courses in American Indian Law, Cultural Property Law, and Indigenous Peoples in International Law, and mentors students through the Native American Law Students Association. Her scholarship informs both academic discourse and practical legal strategies for Indigenous rights advocacy worldwide.

Anne-Laure Dalibardمشاهده پروفایل

استاد

• Geophysical fluids
• Boundary layers in fluid mechanics
• Congestion models
• +۵ مورد دیگر

Anne-Laure Dalibard is a Professor at Sorbonne University's Faculty of Science and Engineering, affiliated with the Jacques-Louis Lions Laboratory (UMR CNRS 7598). She also serves as a Junior member of the Institut Universitaire de France (2020-2025) and was previously a part-time professor at the École Normale Supérieure in Paris (2021-2024). Her research focuses on mathematical analysis of fluid mechanics with applications to geophysical and oceanographic phenomena. Education: Student at ENS Ulm (2001-2005) PhD at CEREMADE, Paris-Dauphine University (defended October 8, 2007) Dalibard's research centers on geophysical fluids, boundary layers in fluid mechanics, congestion models, roughness models, scalar conservation laws, and homogenization theory. She specializes in asymptotic analysis of fluid equations relevant to oceanographic models, particularly those involving rotating fluids and boundary layer phenomena. Her work bridges rigorous mathematical analysis with practical applications in environmental fluid dynamics. Her recent publications demonstrate a consistent focus on boundary layer phenomena in fluid mechanics, with particular emphasis on geophysical applications. She has made significant contributions to understanding boundary layers in rotating fluids, congestion models in Navier-Stokes systems, and wave phenomena in stratified fluids. Her mathematical approach typically involves rigorous analysis of partial differential equations with singular perturbations, often using asymptotic methods, homogenization theory, and kinetic formulations. Scientific Awards: Junior member of the Institut Universitaire de France (2020-2025) Principal Investigator for ERC Starting grant BLOC (2015-2020) Leader of ANR BOURGEONS project (2023-2027) Dalibard leads substantial research initiatives including the ANR BOURGEONS project (2023-2027), which involves over 30 researchers, PhD students, and post-docs working on fluid dynamics aspects relevant to geophysical flows. She has supervised several PhD students including Jean Rax and Gabriela Lopez-Ruiz, and mentored post-doctoral researchers such as Frédéric Marbach, Marc Briant, and Matthew Paddick. Her research has been supported by prestigious grants from the European Research Council and the French National Research Agency. She is actively involved with the Jacques-Louis Lions Laboratory at Sorbonne University and collaborates extensively with researchers across France and internationally. Her work often intersects with oceanographic applications, connecting mathematical theory with environmental fluid dynamics problems.

Haipeng Luoمشاهده پروفایل

دانشیار

• Machine Learning
• Online Learning
• Reinforcement Learning
• +۳ مورد دیگر

Haipeng Luo is an Associate Professor at the Thomas Lord Department of Computer Science, University of Southern California, holding the IBM Early Career Chair. He previously worked as a Postdoctoral Researcher at Microsoft Research, NYC, and has held visiting roles at Google and Amazon. His research focuses on developing practical machine learning algorithms with strong theoretical guarantees, particularly in online learning, bandit problems, reinforcement learning, and game theory. PhD in Computer Science, Princeton University (2011–2016) BSc in Computer Science, Peking University (2007–2011) His work spans adversarial and stochastic environments, addressing challenges in reinforcement learning, game dynamics, calibration, and omniprediction. Recent publications highlight advancements in regret minimization, game equilibrium computation, and robust optimization frameworks. Key contributions include algorithms for zero-sum games, bandit problems with feedback graphs, and theoretical analyses of convergence properties in multi-agent systems. Scientific accolades include Best Paper Awards at COLT 2021, COLT 2018, NeurIPS 2015, and ICML 2015. He has received prestigious grants such as the NSF CAREER Award (2020), Google Faculty Research Award (2020), and NSF CRII Award (2018). His students have secured academic and industry positions, and he actively teaches graduate courses in machine learning and online optimization.

Alessandro Ottazziمشاهده پروفایل

مدرس ارشد

• Geometric Analysis
• Lie Groups
• Sub-Riemannian Geometry
• +۳ مورد دیگر

Dr. Alessandro Ottazzi is a Senior Lecturer in the School of Mathematics and Statistics at the University of New South Wales (UNSW). He earned his PhD from the University of Genoa (Italy) and held postdoctoral positions at the University of Bern (Switzerland), Università di Milano-Bicocca, and Università di Trento. His research spans geometric analysis, Lie groups, sub-Riemannian geometry, and CR structures, with a focus on the interplay between algebraic topology and analytic methods. Ottazzi's work consistently explores geometric rigidity, function spaces on non-Euclidean structures, and mappings in stratified groups. Recent publications emphasize Hardy spaces, Carnot group embeddings, and measure theory on metric trees. His research demonstrates deep connections between differential geometry, harmonic analysis, and operator theory.