جست‌وجوی استاد و پژوهشگر

Reka Z. Albertمشاهده پروفایل

استاد

• Network Science
• Systems Biology
• Signal Transduction
• +۶ مورد دیگر

Reka Z. Albert is a Distinguished Professor in the Department of Physics at Penn State University, with significant interdisciplinary affiliations including the Huck Institutes of the Life Sciences and the Penn State Cancer Institute (Next-Generation Therapies). Her research bridges physics, biology, and computational science through innovative network-based approaches to complex biological systems. Her primary research interests focus on network science applied to biological contexts, particularly in signal transduction pathways , gene regulatory networks , plant-pollinator ecological networks , and network medicine . She develops and applies Boolean and dynamic network models to understand the structure, dynamics, and control principles of complex biological systems. Analysis of her recent publications reveals a strong emphasis on applying network theory to solve biological problems across multiple scales - from molecular signaling to ecological communities. Her work demonstrates particular strength in translating abstract network concepts into concrete biological insights, with applications spanning plant biology, cancer research, and traditional medicine systems. Sloan Research Fellowship (2004-present) Numerous National Science Foundation grants as Principal Investigator Professor Albert maintains an active research program with significant mentoring responsibilities, overseeing multiple graduate students and postdoctoral researchers. Her work has generated substantial external funding, including continuous support from the National Science Foundation since 2004. She leads interdisciplinary collaborations that bridge physics, biology, and computational sciences, creating innovative approaches to understanding complex biological phenomena through network theory.

Ariane Masudaمشاهده پروفایل

استاد

• Number Theory
• Finite Fields
• Permutation Polynomials
• +۳ مورد دیگر

Dr. Ariane Masuda is a Professor in the Department of Mathematics at the School of Arts and Sciences, City University of New York (CUNY), specifically at New York City College of Technology. She concurrently serves as the Mathematics Education Clinical Experiences Director and a City Tech OER Fellow, demonstrating dual commitment to research and pedagogical innovation. Her academic credentials include: Ph.D. in Mathematics, Carleton University, Canada M.Sc. in Mathematics, Federal Fluminense University, Brazil B.S. in Mathematics, Federal University of Paraná, Brazil Dr. Masuda's research centers on Number Theory with specialized expertise in Finite Fields, Permutation Polynomials, and their cryptographic applications. Her work bridges abstract algebra and practical implementations, particularly in coding theory and cryptographic protocol design. She has made seminal contributions to understanding permutation binomials, Rédei permutations, and subgroup structures in linear groups, often revealing connections between combinatorial patterns and algebraic properties. Analysis of her 15 most recent publications (2024-2008) reveals consistent focus on algebraic structures within finite fields, with increasing emphasis on computational aspects and educational applications. Her research trajectory shows progression from theoretical foundations in permutation polynomials toward interdisciplinary applications in optimization and cryptography, while maintaining core number-theoretic investigations. Dr. Masuda has secured significant research funding as Principal Investigator for multiple PSC-CUNY grants: Traditional A grants: 2013-2020, 2021-2022, 2023-2025 Traditional B grant: 2020-2021 She has mentored 30 students through high school and undergraduate research programs and previously served as OER Co-Director for the U.S. Department of Education-funded Opening Gateways project (2017-2021), which targeted Hispanic-Serving Institution development. Currently directing Mathematics Education Clinical Experiences, she integrates research insights into teacher preparation while advancing open educational resources through her City Tech OER Fellowship, creating synergies between theoretical mathematics and classroom practice.

Lutz Hendricksمشاهده پروفایل

استاد

• Macroeconomics
• Human Capital
• Economic Growth
• +۳ مورد دیگر

Lutz Hendricks is a Professor of Economics at the University of North Carolina at Chapel Hill, with his office located in Gardner Hall 06C. He teaches advanced macroeconomic theory courses at both undergraduate (Econ520) and graduate (Econ720, Econ920) levels. Dr. Hendricks received his PhD from the University of Pennsylvania in 1996. Prior to joining UNC Chapel Hill, he held faculty positions at Arizona State University, Iowa State University, and the University of Sydney. His research focuses on macroeconomics, with specific expertise in human capital and economic growth. His work encompasses overlapping generations models, dynamic programming approaches to macroeconomic theory, infinite horizon models (both discrete and continuous time), endogenous growth theories, and stochastic growth modeling. Professor Hendricks maintains an extensive collection of teaching materials covering modern macro theory topics. He is actively engaged in graduate education, supervising PhD students through courses like Econ720 (Advanced Macro Theory I) and Econ920 (Macro student workshop). His teaching philosophy emphasizes reading multiple expositions of the same material from different angles to achieve deep understanding, and he provides extensive resources including previous exams dating back to 2008. Professor Hendricks has developed comprehensive resources on using the Julia programming language for economic research, covering installation, arrays, debugging, optimization, parallel computing, and workflow management. He maintains professional boundaries by stating he has no openings for research positions and does not maintain social media accounts.

Ira Neitzelمشاهده پروفایل

استاد

• PDE-Constrained Optimization
• Numerical Analysis
• Optimal Control Theory
• +۵ مورد دیگر

Professor Ira Neitzel leads the Research Group for Optimization with Partial Differential Equations at the Institute for Numerical Simulation, Faculty of Mathematics and Natural Sciences, University of Bonn. Her research focuses on PDE-constrained optimal control problems, numerical analysis, and phase-field fracture modeling. She maintains active collaborations with institutions including TU Darmstadt and Leibniz University Hannover. Her primary research interests include: PDE-Constrained Optimization Numerical Analysis of Optimal Control Problems Regularization Approaches for Nonsmooth Control Fracture Propagation Modeling using Phase-Field Methods Recent work emphasizes quasilinear parabolic PDEs, state constraints, and sparse control applications in fracture mechanics. Analysis of her 15 most recent publications (2019-2025) reveals consistent focus on: Mathematical foundations of phase-field fracture control Numerical methods for state-constrained problems Convergence analysis of SQP algorithms Error estimation in finite element discretization Key journals include SIAM Journal on Control and Optimization, ESAIM: COCV, and Numerische Mathematik. Her scientific contributions include leadership in DFG Priority Program SPP 1962 and organization of the "Women in Optimization" workshop series. Notable projects include "Optimizing Fracture Propagation Using Phase-Field Approach" (SPP 1962) and "Sparse Controls in Optimization of Quasilinear PDEs" (SFB 1060). Professor Neitzel advises doctoral researchers including Andreas Hehl and Konstantinos Dimitriou. She teaches advanced courses in Numerical Algorithms, Scientific Computing, and Graduate Seminars on Numerical Simulation. Her group maintains active participation in the International GAMM Activity Group on Optimization with PDEs.

Arka P Ghoshمشاهده پروفایل

استاد

• Stochastic Control
• Queueing Networks
• Stochastic Modeling
• +۴ مورد دیگر

Arka P Ghosh is a Professor at Iowa State University's Department of Statistics, with courtesy affiliations in the Department of Mathematics and the Department of Industrial and Manufacturing Systems Engineering. He holds a Ph.D. in Statistics from the University of North Carolina, Chapel Hill (2005), and a B-Stat and M-Stat from the Indian Statistical Institute, Kolkata, India (1998, 2000). Ph.D. in Statistics, University of North Carolina, Chapel Hill, 2005 M-Stat and B-Stat, Indian Statistical Institute, Kolkata, 1998-2000 His research focuses on Stochastic Control, Queueing Networks, Random Walks, and Random Graphs, with applications in statistical classification, clustering, and applied probability models. His work bridges theoretical analysis and practical optimization in stochastic systems. Arka teaches courses such as Stat 690: Introduction to Measure Theory Stat 641: Foundations of Probability Theory Stat 305: Engineering Statistics Stat 105: Introduction to Statistics for Engineers and coordinates online courses for the Statistics Department. He has mentored numerous Ph.D. and M.S. students, including Dong Dai, Subhomoy Ghosh, and Reza Rastegar, many of whom hold academic or industry positions in statistics, mathematics, and data analytics.

Dragan Matićمشاهده پروفایل

دانشیار

• Information Sciences
• Bioinformatics
• Software Development
• +۵ مورد دیگر

Dr. Dragan Matić serves as an Associate Professor in the Department of Computer and Information Sciences at the Faculty of Science and Mathematics, University of Banja Luka. His academic career spans over two decades with significant contributions to computational science. Graduate Mathematician, Faculty of Science and Mathematics, Novi Sad (2001) Master Mathematician, Faculty of Science and Mathematics, Novi Sad (2008) Doctor of Mathematics, Faculty of Mathematics, Belgrade (2013) Professor Matić's research focuses on the intersection of computer science and biology, with particular emphasis on developing computational methods for biological network analysis. His work bridges theoretical computer science with practical applications in bioinformatics, especially in the areas of graph theory applied to protein-protein interaction networks. He has developed innovative algorithms using variable neighborhood search, genetic algorithms, and mixed-integer programming to solve complex combinatorial problems in biological contexts. His publication record shows a consistent trajectory of high-quality research, with recent work (2022-2024) demonstrating continued productivity and relevance in computational biology. The articles reveal a strong focus on applying graph theory and combinatorial optimization to biological problems, particularly in protein network analysis, with increasing interdisciplinary collaboration across Europe. Professor Matić has received research support through multiple significant projects: Connecting Education and Research Communities for an Innovative Resource Aware Society (COST Action EU Project, 2020-2024) Development of artificial intelligence methods for solving computational biology problems (2020-2021) Development and application of combinatorial optimization methods and machine learning in bioinformatics (2019-2020) General Education Project in Bosnia and Herzegovina (Save the Children - USAID, 2019-2023) He teaches courses including Introduction to Web Technologies, Programming Basics 2, Information Technology and Society, Computer Science Teaching Methodology, Human-Computer Interaction, and Bioinformatics at the master's level in biology. His teaching reflects his research interests, connecting theoretical computer science with practical applications.

Luitpold Babelمشاهده پروفایل

استاد

• Discrete Mathematics
• Structural and Algorithmic Graph Theory
• Combinatorial Optimization
• +۶ مورد دیگر

Luitpold Babel is a Professor of Mathematics and Computer Science at the Faculty of Business Administration, University of the Federal Armed Forces Munich. He has been serving in this position since 2007 and continues to be actively involved in teaching and research as evidenced by his Spring Term 2025 course offerings including Fundamentals of Computer Science, Scientific Computing with Matlab, and Engineering Mathematics tutorials. His educational background includes: 1982-1987: Studied mathematics at the Technical University of Munich 1987: Diploma (with distinction) 1990: Doctorate (with distinction) 1997: Habilitation Professor Babel's research has evolved significantly over his career, beginning with theoretical work in discrete mathematics and graph theory before transitioning to applied defense technology research. His current focus spans operations research applications in military technology, particularly UAV route planning, missile guidance systems, and logistics optimization. He has developed expertise in translating complex mathematical concepts into practical engineering solutions for defense applications, with particular emphasis on kinematic constraints in path planning and risk assessment in navigation. An analysis of his publication trends reveals a clear shift from pure graph theory (1990-2005) toward increasingly applied research in aerospace engineering and defense technology (2010-present). His recent work demonstrates sophisticated integration of mathematical optimization with real-world constraints in military applications, with growing emphasis on cooperative systems, real-time replanning, and decentralized decision-making for missile and UAV fleets. His contributions have been recognized with: Teaching Award of the University of the Bundeswehr Munich (2015), awarded by the Student Convention Study Award of the German Society for Defense Technology eV Professor Babel has supervised over 30 master's and bachelor's theses, primarily focusing on defense-related applications of mathematics and computer science. His research has been supported by substantial external funding from the Federal Ministry of Defense and through multiple industry partnerships with major defense contractors including MBDA Deutschland GmbH and RAM-System GmbH. Current projects include Decentralized Flight Path Planning (2023-2025) and Studies on Technical-Logistical Tasks (2021-2024), demonstrating his continued active engagement in cutting-edge defense research.

Joaquín Ariasمشاهده پروفایل

دانشیار

• Constraint Logic Programming
• Answer Set Programming
• Event Calculus
• +۴ مورد دیگر

Joaquín Arias is an Associate Professor at King Juan Carlos University since 2025. His career includes 2020-2025 as Assistant Professor at the same institution and prior pre-doctoral research at IMDEA Software Institute (2013-2020). He has collaborated with institutions like University of Texas at Dallas and Aalto University. Education: Ph.D. in Computer Science (2020, Universidad Politécnica de Madrid) M.Sc. in Computer Science (2015) B.Sc. in Computer Science (2014) M.Arch. in Architecture (2002) Research interests revolve around Constraint Logic Programming , Answer Set Programming , and their applications in Event Calculus , Stream Data Analysis , and Value-Aware Systems . He has developed frameworks like s(CASP) for non-grounded reasoning and Mod TCLP for tabled constraints. Recent articles demonstrate expertise in integrating Large Language Models with logic programming, automated legal reasoning , and real-time system verification . His work emphasizes explainability, constraint handling, and semantic coherence in AI systems. Scientific awards include the best paper prize at CAEPIA 2021 . He has contributed to proceedings as editor for ICLP workshops and authored numerous papers in TPLP , PADL , and AI & LAW .

Nicolas Gillisمشاهده پروفایل

استاد

• Low-rank matrix approximations
• Nonnegative matrix factorization
• Continuous and discrete optimization
• +۶ مورد دیگر

Nicolas Gillis is a Professor in the Department of Mathematics and Operational Research at the Faculty of Engineering, University of Mons, Belgium. His research focuses on theoretical and applied aspects of low-rank matrix approximations, nonnegative matrix factorization (NMF), optimization, and computational complexity, with applications in machine learning, data mining, and hyperspectral imaging. Research Interests: Low-rank matrix approximations, NMF, numerical linear algebra, machine learning, and signal processing. Publications: Authored the first comprehensive book on NMF, available in print and digital formats, with accompanying MATLAB code on GitLab. Teaching: Created a doctoral course on NMF with 6 lectures and 4 exercise sessions for the SOCN doctoral school. Upcoming Events: Organizing the third workshop on Low-Rank Models and Applications (LRMA 25) in September 2025, and the SOCN study day in Mons.

Hung Vinh Tranمشاهده پروفایل

استاد

• Partial Differential Equations
• Hamilton-Jacobi Equations
• Viscosity Solutions
• +۳ مورد دیگر

Professor Hung Vinh Tran is a faculty member in the Department of Mathematics at the University of Wisconsin Madison, where he maintains his office in Van Vleck Hall (715 Van Vleck). His research focuses on partial differential equations, with particular expertise in Hamilton-Jacobi equations, viscosity solutions, and homogenization theory. Professor Tran actively contributes to the mathematical community through editorial work, seminar organization, and mentoring of graduate students and postdocs. Professor Tran's research spans multiple areas of partial differential equations, with primary contributions to Hamilton-Jacobi equations and their applications. His work explores viscosity solutions, homogenization theory, and connections between PDEs and dynamical systems. He has made significant advances in understanding large time behavior of solutions, optimal convergence rates in homogenization, and mathematical analysis of mean curvature flows. His research bridges pure and applied mathematics with applications in mathematical physics, control theory, and geometric analysis. Professor Tran serves as an associate editor for the SIAM Journal on Mathematical Analysis and Advances in Continuous and Discrete Models. He was previously editor for Minimax Theory and its Applications (2020-2025). His editorial contributions reflect his standing in the mathematical community and expertise in nonlinear PDEs. Professor Tran has advised numerous PhD students who have gone on to prestigious positions: Yeoneung Kim (Ph.D. 2019) - Now Assistant Professor at SeoulTech Son Nguyen Thai Tu (Ph.D. 2022) - Now Visiting Assistant Professor at Michigan State University Yuxi Han (Ph.D. 2024) - Now Golomb Visiting Assistant Professor at Purdue University Jiwoong Jang (Ph.D. 2024) - Now Novikov postdoctoral fellow at University of Maryland His research is supported by multiple prestigious awards: Vilas Faculty Early-Career Investigator Award (2022-2024) Simons Fellowship (academic year 2021-2022) NSF CAREER grant DMS-1843320 Distinguished paper award from ICCM (2017) Current NSF grant DMS-2348305 (2024-2027) Professor Tran actively organizes mathematical events including the Virtual Analysis and PDE Seminar (VAPS) connecting researchers worldwide. He has organized multiple Summer Meetings in PDE in Vietnam (Gặp Gỡ Mùa Hè) fostering international collaboration. His 'Diễn Giải Toán Học' series and 'toan0mau' YouTube channel featuring discussions with prominent mathematicians like Ngo Bao Chau have made advanced mathematical concepts accessible to Vietnamese-speaking audiences.

• data science
• cyber-physical systems
• mathematical modeling
• +۵ مورد دیگر

Dr. Oleksii Bychkov serves as Head of the Department of Software Systems and Technologies at Taras Shevchenko National University of Kyiv's Faculty of Information Technology, a position he has held since 2014. His extensive career includes roles as Deputy Dean of the Faculty (2013-2016), Assistant Professor at the Faculty of Cybernetics (2001-2013), and Director of the Information Technology Research Center (2006-2013). A State Prize winner and member of the Ukrainian Academy of Science, he bridges theoretical cybernetics with practical information systems development. Education: Doctor of Sciences (DSc) in Information Technology PhD in Physics and Mathematics Dissertation: "Construction of optimal qualitative characteristics of stochastic neutral equations of neutral type" (Specialty 01.05.01) Dissertation: "Information technologies for analysis and synthesis of continuous-discrete information systems and processes based on fuzzy hybrid automata" (Specialty 05.13.06) Research Focus: Dr. Bychkov pioneers cyber-physical systems and fuzzy modeling through groundbreaking work in possibility theory and hybrid automata stability. His research integrates mathematical modeling with data science to solve complex problems in aerospace, healthcare, and economic systems. The development of perceptive elements and Lyapunov optimal functions represents significant theoretical contributions with practical software implementation. Publication Trends: Analysis of his 15 most recent works reveals a strong trajectory toward applying possibility theory to real-world cyber-physical systems. Key themes include stability analysis of hybrid automata (40% of publications), fuzzy differential equations (30%), and data-driven solutions for information systems (30%). His work increasingly intersects with AI applications in real estate valuation, aircraft dynamics, and educational technology. Scientific Recognition: State Prize of Ukraine in Science and Technology Membership in Ukrainian Academy of Science Research Leadership: Dr. Bychkov directs the Erasmus+ iBIGworld initiative for Big Data innovations while securing grants for mathematical modeling of economic systems. His mentorship program develops next-generation researchers in cybernetics, with recent projects focusing on continuous-discrete process optimization and social information retrieval systems. Technical Infrastructure: As former Director of the Information Technology Research Center, he established specialized labs for hybrid automata simulation and fuzzy system development. Current teams focus on cyber-physical testbeds for aircraft dynamics and real-time social search algorithms within university information systems.

• Stochastic calculus for fractional Brownian motion
• Financial mathematics
• Theory and statistics of random processes and fields
• +۶ مورد دیگر

Professor Yuliia Mishura has been a leading figure at Taras Shevchenko National University of Kyiv since 1976. She currently serves as Professor and Head of the Department of Probability, Statistics and Actuarial Mathematics in the Faculty of Mechanics and Mathematics . Education: BSc + MSc, Kyiv State University, 1975 PhD, Kyiv State University, 1978 DSc (Habilitation), Institute of Mathematics, Kyiv, 1990 Research interests lie at the intersection of stochastic analysis , fractional processes and financial mathematics . She investigates stochastic calculus for fractional Brownian motion, multifractional processes, stochastic differential equations driven by such processes, functional limit theorems, optimal stopping, and statistical inference for models exhibiting long-range dependence. Her recent work focuses on mixed fractional and multifractional models , parameter estimation in non-Gaussian settings , functional limit theorems in multiplicative financial schemes , and Malliavin-calculus techniques applied to option pricing and hedging under memory . Scientific leadership: Principal investigator of the national project “Exact formulas, estimates, asymptotic properties and statistical analysis of complex evolutionary systems with many degrees of freedom” . Team leader of 15 researchers (7 DSc, 8 PhD) and 8 PhD students. Collaborations & projects: INTAS Grant 99-000-16 (Ukrainian coordinator, 2000–2002) TEMPUS-TACIS IB-JEP-25054-2004 (Kyiv team leader, 2004–2008) NATO Grant PST.CLG.980408 (2003–2006) EU IRSES “Multifractionality” 230804 (Kyiv team leader, 2009–2012) STORM project with University of Oslo (2018–2020) State Fund for Fundamental Research of Ukraine grant 2020.02/0026 (2020–2022) The research group maintains active international ties with universities in Vilnius, Oslo, Liverpool, Napoli, Dresden and others.

Christian Landschützerمشاهده پروفایل

دانشیار

• Logistics Engineering
• Mobility & Production
• Simulation-Based Optimization
• +۵ مورد دیگر

Christian Landschützer is an Associate Professor at the Institute of Logistics Engineering , Graz University of Technology, specializing in Mobility & Production . His work bridges engineering design with logistics innovation, focusing on simulation-based optimization and Industry 4.0 integration. Recent research trends include autonomous forestry logistics , biomass handling systems , and Physical Internet principles for hyperconnected logistics platforms. He has received accolades such as the Physical Internet Pioneer Award (2015) and Erfinder der TU Graz (2021), reflecting his leadership in technical logistics. Key projects like FutureWoodTrans and CBE4I demonstrate his commitment to sustainable solutions in industrial and environmental contexts.

Mykhailo Petrovych Chornoborodovمشاهده پروفایل

دانشیار

• Radar
• Digital Signal Processing
• Databases
• +۱ مورد دیگر

Mykhailo Petrovych Chornoborodov is an Associate Professor at Zaporizhia National Technical University, where he has been working since 2010. He holds the academic degree of Candidate of Technical Sciences in the specialty 05.12.17 "Radio and television systems." His primary affiliation is with the university's radio engineering department, where he contributes to both teaching and research activities in radar systems and signal processing. Education: Zaporizhia State Technical University, Radio Instrumentation, 1999 Academic Degree: Candidate of Technical Sciences (2009) Academic Title: Associate Professor Dr. Chornoborodov's research focuses on radar systems, digital signal processing, databases, and military doctrine. His work primarily addresses challenges in radar technology, particularly in interference compensation and signal processing techniques. He has developed methods for improving radar performance, including compensation of impulse interference in coherent-pulse radars and enhancement of tactical and technical characteristics of radar systems like the "Pelican" and 35D6. His research bridges theoretical signal processing with practical military and defense applications. His publication record since 2003 demonstrates consistent contributions to radar and signal processing fields. The research spans military applications, meteorological monitoring, and advanced signal processing methods, with particular emphasis on weight functions for discrete Fourier transforms and pseudorandom sequence design. His most recent work (2019) focuses on pseudorandom sequence synthesis and new code sequences for phase modulation, showing continued innovation in the field. Scientific Interests: Radar, Digital Signal Processing, Databases, Military Doctrine Teaching: Devices for generating, shaping and transmitting radio signals; Signal reception and processing devices; Theory of radio engineering systems; Radio and TV broadcasting systems and networks Dr. Chornoborodov maintains active participation in scientific conferences, including the III Scientific and Technical Conference "State and Development of the Navy of the Armed Forces of Ukraine at the Current Stage" (2003), the II International Radio Electronics Forum "Applied Radio Electronics. State and Prospects of Development" (2005), and multiple scientific and technical conferences of the Kharkiv University of Air Forces (2005-2014). His scholarly contributions are documented through his ORCID (0000-0003-1230-9374) and Scopus (35762538500) identifiers.

• Optimization
• Operations Research
• Mathematical Programming
• +۳ مورد دیگر

PD Dr. Stephan Brandt serves as an Associate Professor at the Institute of Optimization and Operations Research, University of Ulm, holding the German academic rank of Privatdozent—a post-doctoral qualification for independent teaching and research. His institutional presence is confirmed by current office and postal addresses at the university. His research spans foundational and applied aspects of Optimization and Operations Research , with emphasis on: Mathematical Programming Discrete and Continuous Optimization Linear and Nonlinear Programming Combinatorial Optimization Algorithmic Decision Theory Stochastic Optimization Dr. Brandt contributes to the department's academic mission through theoretical advancements and practical problem-solving frameworks in resource allocation and system efficiency.