جست‌وجوی استاد و پژوهشگر

Natalya Pya Arnqvistمشاهده پروفایل

دانشیار

• Statistical Regression Modelling
• Functional Data Analysis
• Shape Preserving Smoothing
• +۷ مورد دیگر

Natalya Pya Arnqvist is an Associate Professor in Mathematical Statistics at Umeå University, Sweden. She is affiliated with the Department of Mathematics and Mathematical Statistics and has active roles in research groups focused on Functional Data Analysis, Semiparametric Regression, and Statistical Learning for Spatio-Temporal Data. Her career includes prior positions at Nazarbayev University (2015-2020), University of Bath (2011-2015), and KIMEP University (2000-2005). Education : PhD in Statistics (University of Bath, UK, 2007-2010), CSc in Physical and Mathematical Sciences (Institute for Mathematics, Kazakhstan, 2000-2005). Her research centers on statistical regression modelling and functional data analysis , with significant contributions to shape constrained additive models (SCAMs) and model-based functional clustering . She has developed R packages such as scam , fdaMocca , and nilde for these methodologies. Recent publications highlight applications in applied demography , defect detection , and nonlinear state space modeling , reflecting her focus on bridging statistical theory with industrial and ecological challenges. She teaches undergraduate and graduate courses in probability, regression, and statistical learning.

Christine Solnonمشاهده پروفایل

استاد

• Ant Colony Optimization
• Constraint Programming
• Combinatorial Optimization
• +۷ مورد دیگر

Christine Solnon is a Professor of Computer Science at INSA Lyon, affiliated with the CITI lab and Inria EMERAUDE team. Her research bridges Ant Colony Optimization (ACO) and Constraint Programming (CP) to solve complex combinatorial problems in vehicle routing, scheduling, and graph algorithms. Deputy head of science at Inria Lyon Centre Co-investigator in projects like ANR MAMUT (2022-2026) and ANR DeCrypt (2019-2022) Her work focuses on hybridizing ACO with CP for optimization, addressing time-dependent problems (e.g., Time-Dependent TSP with Time Windows ), multi-robot coordination, and differential cryptanalysis. Google Scholar lists 15 recent articles (2025-2023) exploring topics like non-crossing path planning for tethered robots, spatio-temporal traffic modeling, and algorithmic ethics. She mentors PhD students in areas such as Time-Dependent Vehicle Routing Problems and Mathheuristics , often co-supervising with institutions like Lab-STICC and LIRIS. Her software tools (e.g., AntSolver, Castor) demonstrate practical applications of her research.

Lilianne Mujica-Parodiمشاهده پروفایل

استاد مدعو

• Computational Neuroscience
• Brain Aging
• Metabolic Regulation
• +۲ مورد دیگر

Lilianne Mujica-Parodi is an Adjunct Professor in Physics and Astronomy at Stony Brook University and leads the Laboratory for Computational Neurodiagnostics (LCNeuro). Her research employs control systems engineering to study homeostatic regulation in brain circuits, with focus areas including neurometabolic interventions, brain aging, and multiscale neural modeling. Key findings demonstrate nonlinear transitions in brain aging where ketone-based metabolic interventions reverse age-related signaling deficits. Her work integrates neuroimaging (fMRI, MRS), computational modeling, and electrophysiology to explore how energy substrates influence network stability and ion channel regulation. Recent publications highlight applications in diabetes-related brain aging and optimization of computational psychiatry frameworks.

Marius Zimandمشاهده پروفایل

استاد

• computational complexity
• algorithmic information theory
• cryptography

Marius Zimand is a Professor in the Department of Computer and Information Sciences at Towson University. His academic expertise spans computational complexity , algorithmic information theory , and cryptography . Holding Ph.D.s in both Computer Science (University of Rochester) and Mathematics (University of Bucharest), he contributes to the advancement of randomness extraction and theoretical computer science. Education: Ph.D. in Computer Science (University of Rochester), Ph.D. in Mathematics (University of Bucharest) Zimand's research focuses on transforming low-quality randomness into high-quality randomness through efficient algorithms. His work, supported by NSF grants 0634830 (2006-2009) and 1016158 (2010-2014) , explores randomness extractors' applications in cryptography, error-correcting codes, and data structures, with mathematical implications in Kolmogorov complexity and constructive Hausdorff dimension. His recent publications analyze topics such as time-bounded Kolmogorov complexity , dynamic matching in expanders , and universal coding theorems , reflecting a consistent emphasis on randomness extraction and complexity theory. Awards include Best Paper at CSR'2008 and Best Paper at ICALP 2005, Track C . Professional Service: Editorial Board Member of Journal of Universal Computer Science Grant Reviewer for NSF, National Research Council Canada, ANR France, and US-Israel BSF Zimand's contributions to theoretical computer science bridge mathematical rigor with practical applications, maintaining active research and service roles within the academic community.

Evan Gawlikمشاهده پروفایل

دانشیار

• Numerical Analysis
• Finite Element Methods
• Computational Fluid Dynamics
• +۳ مورد دیگر

Evan Gawlik is an Associate Professor in the Department of Mathematics and Computer Science at Santa Clara University (2024–present), previously serving as Associate Professor (2023–2024) and Assistant Professor (2018–2023) at the University of Hawaii. He holds a Ph.D. in Computational and Mathematical Engineering from Stanford University (2015) and a B.S. in Applied and Computational Mathematics from the California Institute of Technology (2010). Education : Ph.D., Stanford University, 2010–2015 B.S., California Institute of Technology, 2006–2010 Research Interests : Focused on numerical analysis, finite element methods, and structure-preserving algorithms for partial differential equations. His work emphasizes geometric numerical integration, computational fluid dynamics, and applications in magnetohydrodynamics (MHD) and general relativity. Key areas include finite element discretization of differential forms, error analysis on manifolds, and thermodynamically consistent numerical schemes. Grants & Funding : NSF Grant DMS-1703719 (2017–2020) ANR Grant GEOMFLUID (ANR-14-CE23-0002-01) Labs & Collaborations : Active in computational mathematics research groups, including contributions to open-source finite element software and collaborations on geometric numerical methods. His GitHub repositories (e.g., egawlik ) showcase code implementations of his research, such as variable density Euler equations solvers.

Tobias Glasmachersمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Optimization Algorithms
• +۶ مورد دیگر

Prof. Dr. Tobias Glasmachers is a Full Professor at the Institut für Neuroinformatik , Ruhr-Universität Bochum, Germany, specializing in the Theory of Machine Learning . He leads the Optimization of Adaptive Systems group and holds appointments in both Computer Science and Interdisciplinary AI research. Key Research Areas : Optimization algorithms, evolutionary computation, reinforcement learning, supervised learning, and neural networks Technical Focus : Gradient-based methods, support vector machines, and adaptive coordinate descent Applications : Robotics, waste sorting facilities, 3D game environments (e.g., Doom/Minecraft), and human-centered AI design Notable Contributions : Development of LM-MA-ES evolution strategy, Hessian Estimation Evolution Strategy, and tachAId tool for ethical AI design. His work bridges theoretical analysis with practical implementations across diverse domains. Teaching : Offers courses in Informatik 1 - Programmieren, Machine Learning: Supervised Methods, and Evolutionary Algorithms. Supervises numerous Bachelor's and Master's theses on AI/ML applications.

Saban Alacaمشاهده پروفایل

استاد

• Number Theory
• Algebraic Number Theory
• Cryptography
• +۷ مورد دیگر

Dr. Saban Alaca is a Professor in the School of Mathematics and Statistics at Carleton University. His research focuses on Number Theory, including difference sets, character sums, theta functions, algebraic number fields, and quadratic forms. He has organized notable conferences like the 13th Canadian Number Theory Association (CNTA XIII) in 2014 and co-edited the proceedings book Advances in the Theory of Numbers . Alaca has supervised numerous graduate students and postdoctoral fellows, contributing to research areas such as cryptography and sequence theory. His work bridges theoretical advancements with applications in communications and coding. Alaca’s academic contributions include over 50 peer-reviewed publications in journals like International Journal of Number Theory and Journal of Combinatorics and Number Theory . His research emphasizes evaluating character sums, studying quadratic forms, and exploring convolution sums. He also co-authored the textbook Introductory Algebraic Number Theory , a key resource for graduate students. He has advised PhD students on topics ranging from almost difference sets to discriminant analysis of algebraic fields. Undergraduate mentorship includes projects on elliptic curve cryptography and primality testing algorithms. Alaca’s work often involves collaboration with colleagues like A. Alaca and K.S. Williams, reflecting a commitment to advancing number theory through both individual and collective efforts.

Maryam Elahiمشاهده پروفایل

دانشیار

• Distributed Systems
• Network Performance Analysis
• Computer Architecture Optimization
• +۴ مورد دیگر

Maryam Elahi is an Associate Professor in the Department of Mathematics & Computing at Mount Royal University (MRU), part of the Faculty of Science and Technology. She holds a PhD in Computer Science from the University of Calgary (2017), an MSc in Software Engineering of Distributed Systems from KTH Royal Institute of Technology (2009), and a BSc in Computer Engineering from Azad University of Mashhad (2005). Her research focuses on networked and distributed systems, emphasizing performance analysis, dynamic bandwidth allocation, and speed-scaling systems. She has secured grants including the Petro-Canada Young Innovators Award (2022) and the Provost’s Teaching and Learning Enhancement Grant (2023). Education: PhD in Computer Science, University of Calgary (2017) MSc in Software Engineering of Distributed Systems, KTH (2009) BSc in Computer Engineering, Azad University of Mashhad (2005) Her research interests span network performance modeling, real-time systems optimization, and energy-efficient computing. She actively contributes to academic committees for major conferences and has participated in leadership programs like WISE Planet Change Leadership (2021/22). Maryam is passionate about mentoring students, particularly through Mitacs Globalink Internships, fostering their growth in academic and professional careers. Her articles explore topics such as frequency scaling in multilevel queues, fair dynamic bandwidth allocation, and turbocharged speed-scaling mechanisms. These contributions reflect her expertise in optimizing resource allocation in distributed environments while balancing fairness and efficiency.

• Programming Languages
• Concurrency
• Embedded Systems
• +۴ مورد دیگر

Dr. Emil Sekerinski is a Professor in the Department of Computing and Software at McMaster University. He holds the position of Undergraduate Advisor for Computer Science (Jan 1, 2025 – June 30, 2025). His expertise spans programming logic (verification, refinement), concurrency (components, implementation), embedded systems (modelling, analysis), and programming languages (run-time, compilation). He is actively involved in research clusters focused on Digital & Smart Systems. His research interests emphasize formal methods in computer science, concurrency theory, parallel algorithms, and embedded systems design. He has contributed to advancing methodologies for software quality assurance and system reliability through formal specifications and automated verification techniques. Recent work includes efficient synchronization mechanisms for object-oriented programming languages and formal development of delay-tolerant multicast protocols for wireless sensors. Dr. Sekerinski has organized and participated in major conferences such as FMTea'24 (Co-Chair) and ICTAC'24 (Program Committee). His teaching includes advanced courses like CAS 781 Advanced Topics: Advanced Compiler Design and Optimization and SFWR ENG 3BB4 Concurrent System Design . He maintains an active presence in academic outreach through LinkedIn, Instagram, and other platforms. His work bridges theoretical foundations with practical applications, including environmental sensor data analysis and holistic embedded system development. Despite no explicit mention of awards, his contributions to formal methods education and research are widely recognized in his field.

Liza O'Mooreمشاهده پروفایل

دانشیار

• Reinforced and Prestressed Concrete Design
• Concrete Technology
• Durability of Concrete Structures
• +۷ مورد دیگر

Associate Professor Liza O’Moore is the Associate Dean (Academic) of the Faculty of Engineering, Architecture and Information Technology at the University of Queensland. She holds a PhD in Civil Engineering and has over 30 years of experience in structural and concrete design. Her research focuses on reinforced concrete design, durability, and sustainable construction materials like geopolymer concretes. She has led national and international projects, including advising on Australia’s first graduate-entry Engineering Master’s program. Liza has been recognized with awards such as the 2010 UQ Teaching Excellence Award and 2011 ALTC Citation for Outstanding Contribution to Student Learning. She is a Life Member of the Concrete Institute of Australia, serving as its first female National President (2011–2013). Her interdisciplinary work includes engineering education research, particularly in transition support for first-year students and large-class teaching strategies. Her recent publications address corrosion mitigation in sewer infrastructure, bio-concrete innovations, and educational initiatives for inclusive learning environments. She has contributed to over 40 peer-reviewed articles and actively engages with industry through consultancy and professional organizations. Education: BEng (Hons), PhD in Civil Engineering from The University of Queensland. Leadership Roles: National President of Concrete Institute of Australia (2011–2013), Associate Dean (Academic) since 2021. Key Projects: Development of Australia’s first graduate-entry Engineering Master’s program (CSU, 2016). Liza’s research spans both technical advancements in concrete technology and pedagogical innovations in engineering education, reflecting her dual commitment to academic excellence and industry relevance.

Yisong Yueمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Neurosymbolic AI
• +۶ مورد دیگر

Yisong Yue is a Professor of Computing and Mathematical Sciences at the California Institute of Technology (Caltech). He holds a B.S. from the University of Illinois (2005) and a Ph.D. from Cornell University (2010). His research focuses on machine learning, neurosymbolic AI, autonomous systems, and applications in robotics, science, and healthcare. Key affiliations include advisory roles at Asari AI and CaineX, and leadership roles in ICLR (Board Member, 2024–present; General Chair, ICLR 2025). Yisong's work bridges theory and practice, emphasizing deployable AI solutions. Notable contributions include Neurosymbolic Programming, AI-driven protein optimization, and safety-critical control systems. His research has led to impactful applications in robotics, medical coding automation, and molecular engineering. He has advised numerous students, including Jennifer Sun (Ph.D., Cornell), Yujia Huang (Citadel Securities), and Guanya Shi (CMU faculty). Awards include the Best Paper Award at ICRA 2020 and Okawa Foundation Grant recognition. His lab explores frontiers in adaptive experiment design and human-AI collaboration. Yisong has collaborated with institutions like NASA (MLNav for Martian navigation) and Disney Research (behavior modeling). His work appears in top venues like NeurIPS, ICML, and Science Robotics.

Chaona Chenمشاهده پروفایل

مدرس

• Computational Modelling of Social Signals
• Human-Centred AI
• Social Robotics
• +۳ مورد دیگر

Dr. Chaona Chen is a Lecturer in Robotics at the University of Sheffield's School of Computer Science, specializing in computational modeling of social signals, cultural influence on communication, and human-centered AI/social robotics. She holds a Ph.D. and B.Sc. from the University of Glasgow and Wuhan University respectively. Her research emphasizes culturally adaptive social robots and mental health applications. Education: Ph.D. in Psychology & Neuroscience, University of Glasgow (UK) B.Sc. in Computer Science, Wuhan University (China) Research Interests: Dr. Chen's work focuses on: - Mathematical modeling of facial expressions, gaze, and body movements - Cultural and social conventions influencing human communication - Developing AI/social robots for social skill training in mental health contexts Awards & Funding: Leverhulme Early Career Fellowship (£100k, 2021-2024) Lord Kelvin/Adam Smith Fellowship (£90k, 2021-2024) Best Workshop Paper Award (IEEE ICRA 2021) Grants & Projects: European Research Council-funded FaceSyntax project (2017-2021) Multiple grants from EPSRC, ESRC, and international collaborations Teaching & Supervision: Supervises 2-4 Masters and 3-6 Undergraduate research projects annually. Teaches courses in Social Robotics and Advanced Cognition. Labs & Collaborations: Active in Sheffield Robotics and the Complex Systems Modelling research group. Collaborates with MIT Media Lab and Carnegie Mellon University on social robotics.

Eleni Vasilakiمشاهده پروفایل

استاد

• Bioinspired Machine Learning
• Neuromorphic Computing
• Computational Neuroscience
• +۳ مورد دیگر

Professor Eleni Vasilaki holds the Chair in Bioinspired Machine Learning at the University of Sheffield's School of Computer Science, where she serves as Head of the Machine Learning research group and member of the Complex Systems Modelling research group. She joined as Lecturer in 2009 and became Professor in 2016. Education includes: Bachelor's in Informatics and Telecommunications from University of Athens Master's in Microelectronics from University of Athens DPhil in Computer Science and Artificial Intelligence from University of Sussex Research focuses on developing novel machine learning techniques inspired by biological principles, particularly in reinforcement learning and reservoir computing methods. Her team collaborates with material scientists and engineers to design neuromorphic computing hardware. Publications demonstrate strong emphasis on neuromorphic computing, machine learning applications in neuroscience, reservoir computing systems, and computational modeling of biological processes. Recent work addresses device-agnostic modeling, physical neural networks, and stochastic computing platforms. Significant grants include: MARCH: Magnetic Architectures for Reservoir Computing Hardware (£936,815, Co-PI) ActiveAI - active learning and selective attention for robust AI (£953,584, Co-PI) Modeling probabilistic reinforcement learning in Drosophila (Google, £50,769, PI) CausalXRL: Causal explanations in Reinforcement Learning (£309,915, PI) Brains on Board: Neuromorphic Control of Flying Robots (£2,128,934, Co-PI) Leads the Machine Learning research group and collaborates with the Complex Systems Modelling group, focusing on brain-inspired computing architectures and neuromorphic hardware design.

Heiko Dietrichمشاهده پروفایل

استاد

• Computational Group Theory
• Algebra
• Group Theory
• +۳ مورد دیگر

Heiko Dietrich is a Professor in the School of Mathematics at Monash University and serves as the Associate Dean Graduate Education in the Faculty of Science. His roles include overseeing graduate education, research leadership, and editorial board memberships. He holds a doctoral degree from the University of Braunschweig (2009) and has held positions at institutions including the University of Trento and University of Auckland. Research Interests His research focuses on computational group theory , computational algebra , finite groups , and Lie algebras . He applies computational methods to problems in algebra and has contributed to areas such as Hadamard matrices and classification of quantum states. Recent Research Trends Recent work includes studies on maximal subgroups of the Monster group, coclass theory, and algorithmic approaches to group isomorphism. His publications span theoretical advances and applications in quantum information and combinatorics. Awards: Australian Research Council Discovery Early Career Researcher Award (2013) Cheryl E. Praeger Visiting Research Fellowship (2022) 2019 Victorian Tall Poppy Award Advising & Grants He has supervised over 20 students, including HDR candidates and Master’s researchers. Notable projects include investigations into finite p-groups, computational group theory, and combinatorial identities. He led research initiatives funded by ARC and international collaborations, such as the Computing with Lie groups and algebras project (2019–2023). Labs & Affiliations Editorial roles include Associate Editorships at Mathematische Nachrichten , Journal of Computational Algebra , and Beiträge zur Algebra und Geometrie . He contributes to STEM education through CSIRO’s STEM Professionals in Schools program.

Natasha Dobrinenمشاهده پروفایل

استاد

• Logic
• Ramsey Theory
• Set Theory
• +۲ مورد دیگر

Prof. Natasha Dobrinen is a Full Professor in the Department of Mathematics at the University of Notre Dame's College of Science, specializing in logic, Ramsey theory, set theory, and combinatorics. Her research explores infinite-dimensional Ramsey theory, topological dynamics, and ultrafilters. Education includes: Ph.D. in Mathematics, University of Minnesota (2001) B.A. in Mathematics, University of California, Berkeley (1996) Her research focuses on Ramsey theory applied to infinite relational structures, canonical partition relations, and connections between topological Ramsey spaces and ultrafilters. She investigates combinatorial properties of universal structures and their applications to set theory. Publication analysis reveals predominant focus on structural Ramsey theory, ultrafilters, and set-theoretic combinatorics, with recent work extending to higher-dimensional partition relations and applications to forcing. Scientific awards and honors: Distinguished Women in Math Lecture, UCLA (2023) International Congress of Mathematicians Invited Speaker (2022) Excellence in Research Award (2016) Visiting Fellow, Isaac Newton Institute (2015) Advising includes 4 PhD students and several postdoctoral researchers. Major grants include multiple NSF awards totaling over $700,000 for research in Ramsey theory and relational structures. Leads research groups in discrete mathematics and logic, collaborating internationally with institutions like Charles University and University of Vienna.