جست‌وجوی استاد و پژوهشگر

Michael Krivelevichمشاهده پروفایل

استاد

• Probabilistic Methods in Combinatorics
• Random Structures
• Hypergraphs
• +۷ مورد دیگر

Prof. Michael Krivelevich holds the Baumritter Chair in Combinatorics at the School of Mathematical Sciences, Tel Aviv University. His research focuses on probabilistic methods in combinatorics, random graphs, and positional games. He has authored influential books such as Positional Games and contributed to foundational work in random graph theory. Currently teaching Introduction to Combinatorics and Graph Theory (Spring 2025), he has extensive experience in courses like Graph Theory and Hypergraph Coloring. His work bridges theoretical computer science, coding theory, and combinatorics, with over 150 publications. Recent research explores game-theoretic thresholds, random graph evolution, and equitable coloring algorithms. Education: Ph.D. in Mathematics, Tel Aviv University (not explicitly stated, inferred from career trajectory). Research Interests Krivelevich's work emphasizes random structures , extremal graph theory , and probabilistic combinatorics . He investigates phase transitions in random graphs, positional game strategies, and algorithmic challenges in graph coloring. His contributions include proving sharp thresholds for Hamilton cycle games and analyzing WalkSAT performance on smoothed k-CNF formulas. Collaborations span theoretical computer science and discrete mathematics. Publications Recent articles address Hamiltonicity in Maker-Breaker games, equitable coloring of random graphs, and smoothed analysis of satisfiability processes. His work often combines rigorous proofs with algorithmic insights. Teaching & Mentorship Guides students through advanced combinatorial topics and has taught foundational courses since 2002. No explicit student listings available in provided texts.

Dora Selesiمشاهده پروفایل

استاد

• Stochastic Processes
• Stochastic Analysis
• Functional Analysis
• +۳ مورد دیگر

Dora Selesi is a Full Professor at the Department of Mathematics and Informatics, Faculty of Sciences, University of Novi Sad, Serbia. She holds joint appointments at the Medical Faculty and University Centre of Applied Statistics on a partial-time basis. Her academic role includes chairmanship of the Analysis, Probability and Differential Equations division, alongside editorial roles in journals like Novi Sad Journal of Mathematics and Filomat . Education: PhD in Mathematics, University of Novi Sad (2007), thesis: Generalized stochastic processes in infinite dimensional spaces with applications to singular stochastic partial differential equations MSc in Mathematics, University of Novi Sad (2004) Research Interests: Focuses on stochastic processes, stochastic analysis, functional analysis, and their applications to partial differential equations. Key areas include generalized stochastic processes, Malliavin calculus, chaos expansions, fractional calculus, and stochastic PDEs. Her work bridges pure mathematics and applied fields like mathematical physics and epidemiology. Teaching: Teaches advanced courses on mathematical analysis, differential equations, measure theory, actuarial mathematics, and biomathematics. She emphasizes computational tools (e.g., Mathematica, MATLAB) and interdisciplinary applications in her teaching. Affiliations: Active member of societies such as the American Mathematical Society (AMS), European Women in Mathematics (EWM), and the International Society for Analysis, its Applications and Computation (ISAAC). She has organized conferences like the DAAD school on Chaos expansions and contributed to academic committees. Labs & Teams: Leads research on stochastic processes and chaos expansions, collaborating with international scholars. Her workgroup has produced notable research in generalized functions and stochastic differential equations.

• Artificial Neural Networks
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Marija Blagojević is a Full Professor at the Department of Information Technologies within the Faculty of Technical Sciences in Čačak, University of Kragujevac, Serbia. With over fifteen years of experience in teaching and research, she has established herself as a leading academic in Information Technologies and Systems. Her work spans multiple domains including artificial intelligence, machine learning, and educational technologies, contributing significantly to both theoretical advancements and practical applications in these fields. Dr. Blagojević began her academic career at the Technical Faculty in Čačak in October 2007, initially conducting exercises for courses in Informatics Methodology and IT Applications-Practicum. She was appointed as an Assistant in June 2008 and has since advanced to her current position as Full Professor. Throughout her career, she has continuously expanded her expertise through various specialized courses including Oracle Academy courses in database design and programming, machine learning from Stanford University, and certifications in Huawei AI technologies. Her research interests primarily focus on the application of artificial intelligence techniques to solve complex problems across diverse domains. She has made significant contributions to neural network applications, developing models for predicting apricot yields, air pollution levels, and student success in programming courses. Her work in e-learning technologies demonstrates innovative approaches for adaptive course delivery using data mining techniques. She has also pioneered research at the intersection of AI and psychology, exploring concepts like 'Artificial Psychology' and 'PsAIchology'. Analysis of Dr. Blagojević's recent publications reveals a clear trajectory toward interdisciplinary applications of artificial intelligence. Her work increasingly bridges computer science with psychology, healthcare, and environmental science. A notable trend is her focus on explainable AI, ensuring complex machine learning models remain interpretable for end-users. Her research also demonstrates strong commitment to applying technology for social good, particularly in education and rural development contexts, as evidenced by projects like WINnovators Space. Scientific Awards and Recognitions Award from 'dr Milivoje Urošević' foundation for best graduating student in 2006/2007 Four awards from Technical Faculty for excellent academic results each school year Scholarship from Fund for Young Talents Scholarship from University of Kragujevac (as one of 11 best students) Scholarship from Čačak municipality Scholarship from 'Denise Hale' Foundation Award for the best second-place innovative idea from the Union of Engineers and Technicians of Serbia (February 2020) Recognition for the best female scientist with most research results at University of Kragujevac (February 2022) Dr. Blagojević has been actively involved in research supervision and grant-funded projects throughout her career. She has served as a reviewer for three scientific journals and participated in significant research initiatives including 'Development of new information and communication technologies using advanced mathematical methods' (Project III 44006) and 'Application of biomedical engineering in preclinical and clinical practice' (Project 41007). Her international collaboration includes participation in TEMPUS project 544482-TEMPUS-1-2013-1-IT-TEMPUS-JPHES and Erasmus mobility at Alexandru Ioan Cuza University of Iaşi. As a member of the Computer Science Laboratory at the Faculty of Technical Sciences, Dr. Blagojević contributes to a collaborative research environment focused on advancing information technologies. Her interdisciplinary approach connects computer science with psychology, healthcare, and environmental science, demonstrating how technology can address complex real-world challenges while enhancing educational outcomes and community development.

Ivana Vojnovićمشاهده پروفایل

دانشیار

• Functional Analysis
• Pseudodifferential Operators
• Banach Modules
• +۵ مورد دیگر

Ivana Vojnović is an Associate Professor at the Department of Mathematics and Informatics (DMI) of the Faculty of Sciences, University of Novi Sad. She is affiliated with the Functional Analysis, Geometry and Topology research group. Her office is located on the second floor of the DMI&DF building. Her research focuses on functional analysis, pseudodifferential operators, distribution theory, and nonlinear partial differential equations with applications in mathematical physics. Her work includes studies on Banach modules, Hörmander spaces, singular solutions to Schrödinger-type equations, and defect distributions. She has contributed to operator continuity, generalized solutions, and microlocal analysis. Her recent articles (2021–2025) emphasize advanced topics like Colombeau algebras, nonsmooth symbols, and applications to quantum mechanics and optimization. Her research trends show a strong emphasis on abstract functional analytic methods applied to concrete problems in PDEs and mathematical physics. She maintains an active research profile with interdisciplinary interests bridging pure mathematics and applied fields like quantum dynamics and chess engine optimization. No scientific awards or grants are explicitly mentioned. She has an extensive list of advisees or collaborative grants in the provided texts. Her personal website at http://personal.pmf.uns.ac.rs/ivana.vojnovic/ likely contains further details about her research groups or laboratory affiliations.

Dušan Stojnićمشاهده پروفایل

استادیار

• Forest Road Planning
• Forest Resource Utilization
• Forest Transport
• +۲ مورد دیگر

Dr. Dušan Stojnić is an Assistant Professor at the Faculty of Forestry, University of Belgrade, teaching Forest Roads (undergraduate) Forest Opening and Forest Construction (master's) . He holds a doctorate in Biotechnical Sciences - Forestry (2019) and has been employed since 2011. Research Focus: His work centers on Forest road network optimization Multi-criteria decision-making in forestry Forest construction and infrastructure Timber extraction impacts . Publications: He has authored over 50 papers with recent trends in GIS-based forest planning Protected area road siting Fire-prone forest infrastructure Equipment efficiency analysis . Projects: He has been a responsible designer in numerous forest road engineering projects across Serbia and participated in forest resource utilization research initiatives.

• Finite Geometry
• Extremal Combinatorics
• Coding Theory
• +۷ مورد دیگر

Anurag Bishnoi is a tenured Assistant Professor in the Faculty of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology (TU Delft). His research lies at the intersection of discrete mathematics, finite geometry, extremal combinatorics, coding theory, and the polynomial method. He has held prior research positions at The University of Western Australia as a DECRA Research Fellow (2019–2020) and at Freie Universität Berlin as a postdoctoral researcher in the Combinatorics and Graph Theory group (2017–2019). His research interests include: Finite Geometry Extremal Combinatorics Coding Theory Spectral Graph Theory Polynomial Method Ramsey Theory Incidence Geometry Anurag’s recent publications focus on deep connections between combinatorial structures, coding theory, and finite geometry. His work includes explicit constructions of optimal blocking sets and minimal codes using expander graphs, improvements on bounds for the trifference problem, and advances in Ramsey theory via geometric constructions. He frequently employs algebraic and combinatorial techniques, including the Chevalley-Warning theorem and expander mixing lemma, to solve extremal problems. He has received recognition as a DECRA Research Fellow and has published in leading journals such as Transactions of the AMS , Journal of the London Mathematical Society , and Combinatorica . His research is highly collaborative, involving mathematicians such as Noga Alon, John Bamberg, and Bart De Bruyn. Notable scientific contributions and awards include: DECRA Research Fellowship Significant results on Ryser’s conjecture and minimal Ramsey graphs Novel constructions of clique-free pseudorandom graphs Generalizations of classical theorems in finite field theory Anurag advises no formal students listed in the text but collaborates extensively. He also serves as Chief Scientific Advisor for the edtech startup Not A Bot , where he designs mathematical games like 'It’s a trap'. He maintains a research blog that functions as his official website and has been instrumental in disseminating his work and mentoring through expository writing.

• Randomness and Computation
• Algorithms and Optimization
• Complexity Theory
• +۱۲ مورد دیگر

Avi Wigderson is the Herbert H. Maass Professor at the School of Mathematics, Institute for Advanced Study, Princeton, where he leads research in theoretical computer science and discrete mathematics. He organizes the CSDM (Computer Science and Discrete Mathematics) program at IAS, fostering interdisciplinary research and collaboration. Research Interests: His primary research areas include randomness and pseudorandomness, computational complexity, circuit and proof complexity, quantum computation, cryptography, and distributed computing. His work bridges computer science and pure mathematics, particularly through algebra, analysis, and combinatorics. He has pioneered foundational results in derandomization, lower bounds, and the interplay between computation and mathematical structures. The recent publications highlight his continued leadership in advancing algebraic and analytic techniques in complexity theory. Themes include operator scaling, invariant theory, expander graphs, arithmetic circuits, and the asymptotic analysis of tensors and matrix spaces. These works often unify computational problems with deep mathematical frameworks, demonstrating the power of interdisciplinary approaches. Scientific Awards: Edsger W. Dijkstra Prize in Distributed Computing (2023) for the paper 'Completeness Theorems for Non-cryptographic Fault-tolerant Distributed Computing' Advising and Grants: Wigderson has advised numerous PhD students, primarily at the Hebrew University and Princeton, and hosted over 50 postdoctoral researchers at IAS, including many who have become leading figures in theoretical computer science. While specific grants are not listed, his sustained productivity and influence suggest long-term funding from major sources such as the NSF, Simons Foundation, or IAS internal support. Labs and Teams: He leads the CSDM (Computer Science and Discrete Mathematics) group at the Institute for Advanced Study, organizing seminars, workshops, and collaborative research initiatives that bring together mathematicians and computer scientists from around the world.

Dragan Ćetenovićمشاهده پروفایل

دانشیار

• Electrical Power Engineering
• Smart Grids
• Renewable Energy Integration
• +۴ مورد دیگر

Dragan Ćetenović is an Associate Professor at the Department of Electrical Power Engineering within the Faculty of Technical Sciences in Čačak , University of Kragujevac . He was promoted to Associate Professor in July 2024 and has been working on advanced algorithms for power system state estimation since his postdoctoral training at the University of Manchester (2019-2021). PhD in Electrical and Computer Engineering (2019), University of Kragujevac Master's in Electrical Power Engineering (2013), University of Kragujevac Bachelor's in Electrical Engineering (2011), University of Kragujevac His research focuses on dynamic state estimation , Kalman filter optimization , and multi-energy network integration with 16+ SCI journal publications. Key article themes include resilient grid planning, anomaly detection, and cyber-physical energy systems. He has received the Aleksandar Avramović Award and recognition for best young researcher papers. Co-investigator on EPSRC-funded Supergen Energy Networks Hub (2018) and MC² projects Project contributor for "Analysis of the TITAN Kosjerić Industrial Network" (2024) Active participant in international conferences (SGSMA, IEEE PES GM, CIRED)

Mladen Nikolićمشاهده پروفایل

دانشیار

• Machine Learning
• Automated Reasoning
• Earthquake Damage Assessment
• +۲ مورد دیگر

Mladen Nikolić is an Associate Professor at the Faculty of Mathematics, University of Belgrade, specializing in machine learning and automated reasoning. He actively contributes to the Machine Learning and Applications Group (MLA@MATF) and the Automated Reasoning GrOup (ARGO) . His research spans earthquake damage assessment , deep learning object tracking , LLM integration with tabular data , and astronomical data analysis . Recent work focuses on the RELAR Project for rapid earthquake loss assessment, CNN architectures for structural damage classification, and novel approaches to incorporating large language model priors into machine learning systems. His publications demonstrate strong interdisciplinary applications connecting computer science with seismology, transportation engineering, and astrophysics. Developed frameworks for earthquake loss assessment and recovery Advanced deep learning filters for non-linear motion tracking Integrated LLMs with tabular data processing systems Contributed to LSST astronomical data challenges Nikolić maintains active research collaborations through MLA@MATF and ARGO groups, with publications spanning machine learning theory, automated reasoning systems, and practical applications across multiple scientific domains. His work shows increasing focus on real-world deployment of AI systems for disaster response and scientific data analysis.

• Combinatorics
• Probabilistic Methods
• Random Graphs
• +۴ مورد دیگر

Rajko Nenadov is a Lecturer in Theoretical Computer Science at the University of Auckland, New Zealand. Previously, he earned his PhD from ETH Zurich in 2016 under Angelika Steger. He held postdoctoral positions at Monash University (Australia) and ETH Zurich, focusing on combinatorics and graph theory. Between 2018–2022, he worked as a software engineer at Google Zurich, contributing to search ranking algorithms. Returning to academia in 2023, his research emphasizes probabilistic methods, random structures, and applications in theoretical computer science. His education includes a PhD in Computer Science from ETH Zurich (2016). Notable career milestones include postdoctoral research on expanders, pseudorandomness, and Ramsey theory, followed by industry experience in algorithmic development. Rajko’s research interests revolve around combinatorics, with a focus on probabilistic methods, random graphs, extremal graph theory, and Ramsey theory. His work bridges foundational combinatorics with practical applications in computer science, particularly in algorithm design and computational complexity. His recent publications explore topics like hypergraph universality, container theorems, and extremal subgraph counting. These contributions highlight advancements in probabilistic combinatorics and structural graph theory. No scientific awards or grants are explicitly listed in the provided information. His career transition from academia to industry and back underscores his interdisciplinary expertise in theory and applied computing.

François Pirotمشاهده پروفایل

دانشیار

• Graph Theory
• Combinatorics
• Probabilistic Method
• +۴ مورد دیگر

François Pirot is an Associate Professor (Maître de Conférences) at Université Paris-Saclay since September 1, 2021. He conducts research at the LISN laboratory within the GALaC team and teaches at the Faculty of Science of Orsay. PhD in Mathematics (Radboud University) and Computer Sciences (Université de Lorraine), 2019 Postdoctoral experience: ULB (2019), G-SCOP (2019-2020), Inria Sophia Antipolis (2020-2021) His research focuses on graph coloring problems in diverse contexts such as graph powers, locally sparse graphs, and distributed algorithms, utilizing probabilistic methods and connections to bio-informatics through circular codes. He has advanced bounds for h -conflict-free coloring, acyclic coloring, and dichromatic numbers in oriented graphs, with applications to minor-closed families and geometric group theory. Scientific contributions include: Asymptotically tight bounds for chromatic numbers in sparse graphs Efficient fractional coloring algorithms for K_t-minor-free graphs Structural analysis of comma-free and mixed circular codes in genetic alphabets Charles Delorme Prize for outstanding thesis in Graph Theory (2019) Collaborations span institutions like ULB, G-SCOP, Inria, and cross-disciplinary fields from computer science to mathematical biology.