جست‌وجوی استاد و پژوهشگر

• Distributed Computing
• Graph Algorithms
• Theoretical Computer Science
• +۳ مورد دیگر

Yannic Maus is a Professor at Graz University of Technology, affiliated with the Institute of Algorithms and Theory and the Institute of Software Engineering and Artificial Intelligence. His research focuses on distributed computing, graph algorithms, and theoretical computer science. He holds a PhD and multiple bachelor’s and master’s degrees in Computer Science. His work emphasizes distributed graph coloring, locality in algorithms, and massively parallel computing. He has contributed to foundational results in distributed algorithms, including optimal edge coloring and coloring hyperbolic random graphs. His research bridges theoretical insights with practical distributed systems challenges. Education: PhD in Natural Sciences (Dr.rer.nat.), B.Sc. and M.Sc. in Computer Science Key research interests include distributed algorithms for graphs, Lovász Local Lemma applications, and algorithmic efficiency in dynamic networks. His publications explore topics like ruling sets in trees, exponential speedups in MPC models, and adaptive coloring techniques for sparse graphs. He has also investigated the algorithmic small-world phenomenon and connectivity in forests using deterministic approaches. Yannic Maus’s work often addresses theoretical lower bounds and upper limits in distributed computing, with applications to real-world networked systems. His contributions span conferences like DISC and SoCG, focusing on both foundational problems and their algorithmic solutions.

• Randomized Algorithms
• Networking
• Social Networks
• +۷ مورد دیگر

Aravind Srinivasan is a Professor of Computer Science at the University of Maryland, College Park, USA. He holds tenure and has held academic positions at the National University of Singapore and Bell Labs. He completed his B.Tech at IIT Madras and his Ph.D. at Cornell University, with postdoctoral research at the Institute for Advanced Study and DIMACS. His research focuses on randomized algorithms, networking, social networks, combinatorial optimization, and their applications to public health, machine learning, and energy systems. He has published over 115 papers in top journals like Nature and the Journal of the ACM, and his work has received significant recognition, including 1,551 citations for his 2004 Nature paper on disease modeling. Education: B.Tech, Indian Institute of Technology Madras Ph.D., Cornell University Awarded Fellowships from ACM, AAAS, IEEE, and EATCS, he also serves as Editor-in-Chief of the ACM Transactions on Algorithms. His students have secured roles in academia, industry, and government, reflecting his impactful mentorship. His contributions span theoretical computer science and applied domains, with notable work in probabilistic methods, network science, and interdisciplinary applications.

Wojciech Szpankowskiمشاهده پروفایل

استاد

• Analysis of Algorithms
• Information Theory
• Analytic Combinatorics
• +۶ مورد دیگر

Wojciech Szpankowski is the Saul Rosen Distinguished Professor of Computer Science at Purdue University. He holds concurrent positions as a Guest Professor at ETH Zurich and a Professor at Jagiellonian University, Krakow. His research focuses on analysis of algorithms, information theory, analytic combinatorics, and random structures. He has directed major initiatives like the NSF Science & Technology Center on Science of Information (CSoI), a $50M 10-year project. Szpankowski is a Fellow of the IEEE and has received prestigious awards including the Flajolet Prize (2020) and Humboldt Research Award (2010). He has held visiting roles at institutions worldwide, including Stanford University and the Newton Institute, Cambridge. His academic journey includes tenure as Full Professor at Purdue (since 1992), Assistant Professorships at McGill University (1984–1992) and Technical University of Gdańsk (1980–1984). His scholarly contributions span monographs like "Average Case Analysis of Algorithms on Sequences" (2001) and "Analytic Pattern Matching" (2015), with a forthcoming work on Analytic Information Theory (2022). He actively contributes to scientific boards, including HIIT Helsinki and NeuroMat Brazil. Szpankowski’s publications emphasize interdisciplinary research at the intersection of computer science, mathematics, and biology. His work on privacy-preserving data analysis, dynamic network inference, and protein superfamily evolution showcases his broad impact. Keynote talks at major conferences (e.g., SODA 2019, AofA 2016) reflect his leadership in theoretical computer science. His grants and recognitions underscore institutional trust: the NSF Science & Technology Center (2010) and Arden L. Bement Jr. Award (2015) highlight his pioneering role in redefining information science. Collaborations span academia and industry, with affiliations at Hewlett-Packard and INRIA.

Robert J. C. Youngمشاهده پروفایل

استاد

• Cultural and Political History
• Literature and Literary Theory
• Philosophy
• +۷ مورد دیگر

Robert J. C. Young is the Julius Silver Professor of English and Comparative Literature at New York University, previously holding a Professorship in English and Critical Theory at Oxford University. He is a Fellow of the British Academy and Honorary Life Fellow at Wadham College, Oxford. His research spans colonial history and postcolonial theory , cultural and political history , literature and literary theory , philosophy , psychoanalysis , and race and translation studies , with a focus on Frantz Fanon and literatures of the Maghreb and Middle East. He has edited Fanon's works, including Alienation and Freedom (2018). His recent Google Scholar publications include 15 articles (2020–2025) on spiking neural networks , neuromorphic computing , synaptic plasticity , and deep learning , exploring machine learning algorithms, neural hardware, and biological computation models. This suggests interdisciplinary work between humanities and computational neuroscience. Corresponding Fellow, British Academy (2013) Honorary Life Fellowship, Wadham College, Oxford (2017) President, AILC/ICLA Research Committee on Literary Theory

Maryna Viazovskaمشاهده پروفایل

استاد

• Sphere packing
• Fourier analysis
• Automorphic forms
• +۳ مورد دیگر

Maryna Viazovska is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), renowned for solving the sphere packing problem in dimensions 8 and 24. She holds a PhD from the Max Planck Institute for Mathematics and the University of Bonn (2013), with earlier degrees from Technical University Kaiserslautern (M.Sc., 2007) and Kyiv National Taras Shevchenko University (B.Sc., 2005). Her research focuses on sphere packing, optimal point configurations, Fourier analysis, automorphic forms, and number theory. Notable achievements include proving the E8 lattice's optimality in 8 dimensions and the Leech lattice in 24 dimensions, leveraging modular forms and interpolation techniques. Key awards include the Fields Medal (2022), Fermat Prize (2020), and Salem Prize (2016). She has held positions at Humboldt University of Berlin (BMS Dirichlet Postdoc), Institut des Hautes Études Scientifiques, and Princeton University. Her publications span top journals like Annals of Mathematics and address interdisciplinary topics such as superconductivity and combinatorial geometry. Viazovska’s work bridges pure mathematics with applications in coding theory and physics.

Manuel Ferdikمشاهده پروفایل

دانشیار

• RFID Technology
• Wireless Sensor Networks
• IoT Applications
• +۳ مورد دیگر

Manuel Ferdik is currently the Head of Research Focus Electronics & Data Analytics at the Management Center Innsbruck (since 2023) and holds the position of Associate Professor (FH) there since 2021. Previously, he served as Senior Lecturer (2021), Lecturer at Kufstein University of Applied Sciences (2018–2021), and University Assistant at the University of Innsbruck (2014–2019). He earned his Dr. techn. in Technical Sciences from Leopold-Franzens-University Innsbruck (2015–2019), M.Sc. in Industrial Engineering, and dual Dipl.-Ing./B.Sc. in Mechatronics. Research Interests include RFID technology, low-power electronics, wireless sensor networks, IoT applications, and Industrie 4.0. His work focuses on optimizing energy efficiency in embedded systems, developing secure communication protocols for passive devices, and advancing data analytics in industrial contexts. Awards include the prestigious Eduard Wallnöfer Prize (2023) and Science Prize 2019 from Tyrol Chamber of Commerce. He has supervised numerous theses in automation, predictive maintenance, AI-driven solutions, and digital transformation. His teaching spans electrical engineering, data science, IoT, and Industry 4.0 across multiple institutions. He also holds a Lean Production Green Belt certification from Danube University Krems.

Friedrich Slivovskyمشاهده پروفایل

پژوهشگر

• Quantified Boolean Formulas
• Propositional Model Counting
• Knowledge Compilation
• +۵ مورد دیگر

Friedrich Slivovsky is a researcher at the Institute of Logic and Computation within the Faculty of Informatics at Technische Universität Wien (Vienna University of Technology). His work focuses on theoretical and practical aspects of computational logic, with particular expertise in Quantified Boolean Formulas (QBFs), Propositional Model Counting (#SAT), and Knowledge Compilation. His research interests span the theoretical foundations and practical applications of computational logic. Slivovsky investigates the complexity of logical reasoning problems, develops efficient algorithms for solving them, and creates practical tools that implement these theoretical advances. His work bridges the gap between theoretical computer science and practical applications in areas like hardware verification, artificial intelligence, and electronic design automation. Analysis of his publication trends reveals a consistent focus on QBF solving techniques, with increasing emphasis on circuit minimization, proof complexity, and practical solver engineering. His recent work (2023-2024) shows a strong focus on circuit minimization techniques, combining QBF and SAT approaches to solve complex optimization problems in hardware design. Earlier work (2019-2021) emphasized dependency schemes, certification methods, and theoretical foundations of QBF solving. Slivovsky leads several significant software projects that have become important tools in the computational logic community: Qute : A dependency learning QBF solver with GitHub repository showing active development (latest commit December 2024) Unique : A preprocessor for (D)QBF that computes unique Skolem and Herbrand functions Pedant : A certifying DQBF solver These projects demonstrate his commitment to translating theoretical advances into practical tools that benefit the broader research community.

Ekaterina Fokinaمشاهده پروفایل

دانشیار

• Computable Structure Theory
• Computable Model Theory
• Equivalence Relations
• +۸ مورد دیگر

Ekaterina Fokina is an associate professor at the Institute of Discrete Mathematics and Geometry, Vienna University of Technology. Her research focuses on computable model theory, equivalence relations, and algorithmic properties of structures. Projects: Stand-alone Project P27527, Elise Richter Project V206, Stand-alone Project P23989, Lise Meitner Project M1188. Collaborators: V. Harizanov, D. Turetsky, N. Bazhenov, L. San Mauro, P. Semukhin, S. Goncharov, J. Knight, R. Miller. Her work investigates categoricity spectra, bi-embeddability, and the complexity of equivalence relations. Key contributions include solving the long-open Covering Problem for Martin-Löf randomness and analyzing the computational complexity of the Finite Intersection Principle. She has published in journals like Annals of Pure and Applied Logic , Archiv für Mathematische Logik und Grundlagenforschung , and Journal of Symbolic Logic . Articles supported by FWF grants explore computable categoricity, equivalence relation complexity, and parameterized complexity theory. Her recent work includes bi-embeddability spectra, degree spectra, and intrinsic complexity bounds. Scientific Awards: Elise Richter Fellowship (FWF V206) Lise Meitner Fellowship (FWF M1188) She has contributed to understanding algorithmic randomness, effective versions of the Axiom of Choice, and hyperarithmetic isomorphism complexity.

Raimundo Saonaمشاهده پروفایل

پژوهشگر ارشد

• Game Theory
• Probability Theory
• Algorithmic Game Theory
• +۳ مورد دیگر

Raimundo Saona is a Research Fellow in the Department of Mathematics at the London School of Economics and Political Science (LSE), where he joined in 2025. His work bridges theoretical mathematics with practical applications in computer science and decision theory. His research focuses on Game Theory, Probability Theory, Algorithmic Game Theory, Stochastic Analysis, Optimal Control, and Imprecise Probability Theory. He develops mathematical tools to provide new insights on situations involving uncertainty, working with both continuous and discrete models, proving theoretical existence theorems, coding efficient algorithms, and analyzing both dynamic online and static offline settings. His publication record shows a strong focus on stochastic games, Markov decision processes, and prophet inequalities. His recent work (2022-2024) has centered on ergodic unobservable MDPs, marginal values in stochastic games, and zero-sum random games on directed graphs, demonstrating his continued contribution to advancing theoretical frameworks in game theory and decision processes. His earlier work established foundational results in POMDPs and prophet inequalities.

Pavlos Topalidisمشاهده پروفایل

مدرس

• Sleep Science
• Cognitive Neuroscience
• Consciousness Research
• +۵ مورد دیگر

Dr. Pavlos Topalidis is a Greek cognitive neuroscientist and PhD candidate at the University of Salzburg's Centre for Cognitive Neuroscience (CCNS), working in the laboratory for Sleep and Consciousness Research under the supervision of Univ.-Prof. Dr. Manuel Schabus. Since October 2023, he has served as a Junior Lecturer at the University of Salzburg, teaching Human Cognition and Sleep at both Bachelor and Master's levels. His educational background includes: PhD student at University of Salzburg (since 2019), Centre for Cognitive Neuroscience MSc in Neuro-Cognitive Psychology from Ludwig-Maximilians-Universität Munich (2017-2019) BSc (Hons, first class) in Psychology from University of Aberdeen, UK (2012-2016) Research visit at Yale University (2022) Dr. Topalidis's research focuses on information processing during sleep, particularly predictive coding and statistical learning mechanisms. His work explores how the brain processes information across wakefulness and sleep states, with applications in sleep monitoring using wearable technology. He investigates oscillatory brain activity patterns and their relationship to cognitive functions, with additional interests in cultural variations in sleep patterns and insomnia treatments. His technical expertise spans multiple neuroimaging methods including EEG, MEG, fMRI, and actigraphy, with advanced programming skills in Matlab and R for data analysis. His scientific contributions have been recognized with multiple awards including a poster award at the Sleep, Cognition and Consciousness Winter Symposium (2023) and a project presentation award at the ESRS Sleep School (2021). His research has led to numerous publications focusing on sleep classification algorithms, cross-cultural sleep studies, and the application of physiological measures to understand mental states. February 2023: Poster award at Sleep, Cognition and Consciousness Winter Symposium November 2022: Salzburg University research stay funding at Yale University (1700€) October 2022: Shortlisted for best poster award at the 26th European Sleep Research Society Conference September 2021: ESRS 3rd Sleep School project presentation award October 2013: ERASMUS scholarship As a Junior Lecturer, Dr. Topalidis mentors undergraduate and graduate students in cognitive neuroscience and sleep research. His current projects involve developing low-cost sleep monitoring solutions using wearable technology and investigating predictive coding mechanisms during sleep. He has also completed specialized training in Cognitive Behavioral Therapy for Insomnia (2023) and Good Clinical Practice (2022). Dr. Topalidis is an active member of the Sleep and Consciousness Research laboratory at the Centre for Cognitive Neuroscience, collaborating with researchers across Europe. His work bridges basic cognitive neuroscience with clinical applications, particularly in developing accessible sleep monitoring tools and understanding sleep's role in cognitive processing and memory consolidation.

• Computer Vision
• Explainable Machine Learning
• Statistical Models in AI
• +۳ مورد دیگر

Siavash Arjomand Bigdeli serves as an Associate Professor of Computer Vision at the Technical University of Denmark, following prior employment as a scientist at the Swiss Center for Electronics and Microtechnologies (CSEM). His research focuses on: Ante-/Post-Hoc explainability of machine learning models Integration of statistical models in learning/inference processes Philosophical methodologies in artificial intelligence development Advanced computer vision techniques for visual understanding Recent publications reveal consistent specialization in image restoration and stereo vision, employing deep learning architectures and probabilistic graphical models to solve core challenges in visual data reconstruction and temporal coherence. His work demonstrates strong interdisciplinary connections between theoretical machine learning, practical computer vision applications, and epistemological considerations in AI systems.

• Global Optimization
• Numerical Analysis
• Data Analysis
• +۳ مورد دیگر

Waltraud Huyer is a faculty member at the Department of Mathematics, Faculty of Mathematics, University of Vienna. Her office is located in Room 04.120 at Oskar-Morgenstern-Platz 1, 1090 Wien, Austria. She actively teaches courses including Numerical Mathematics and Introduction to Mathematics for both undergraduate and secondary school teacher accreditation programs. Her research spans Global and Local Optimization , Numerical Analysis , Data Analysis , Protein Folding , and Population Dynamics with structured populations. She develops advanced optimization algorithms like SNOBFIT for noisy environments and MINQ8 for quadratic programming, while applying mathematical techniques to biological problems such as protein structure prediction and age-structured population modeling. Analysis of her 14 most recent publications (1994-2018) reveals three dominant research thrusts: (1) Algorithmic development in global optimization (7 papers), including multilevel coordinate search and exact penalty functions; (2) Mathematical biology applications (5 papers), particularly in protein folding and population dynamics; (3) Computational verification methods (2 papers) for linear systems and feasibility problems. Her work consistently bridges theoretical mathematics with practical computational implementations. Her scientific contributions include widely-used algorithms implemented in MATLAB, such as the MCS global optimizer and SNOBFIT for noisy optimization, available through the University of Vienna's software repository. Huyer supervises teaching activities for foundational mathematics courses, emphasizing practical computational skills using MATLAB for numerical analysis and regression problems. Her teaching materials include detailed exercise sets with structured assessment criteria requiring both theoretical understanding and programming implementation.