Find Academic Supervisors

• Computational Social Science
• Collective Intelligence
• Network Science
• +5 more

Dr. Henry Kudzanai Dambanemuya serves as an Assistant Instructional Professor in Computational Social Science at the University of Chicago, teaching core computational methods courses and electives in collective intelligence, large-scale online experiments, and digital peacebuilding. His interdisciplinary approach bridges computer science, communication, and international peace studies to examine complex systems through computational lenses. His educational foundation includes: B.A. in Computer Science and Conflict Studies (double major) from DePauw University M.A. in International Peace Studies from the University of Notre Dame’s Kroc Institute M.Sc. and Ph.D. in Technology and Social Behavior from Northwestern University Dr. Dambanemuya's research pioneers methodological innovations in computational social science through big data mining, online experiments, and machine learning applications. His work advances theoretical frameworks for collective intelligence while developing novel techniques in network science and social computing, with significant implications for humanitarian aid, peacebuilding, and digital society. Analysis of his 2019-2025 publications reveals consistent interdisciplinary rigor across computational social science, network analysis, and peace studies. Key thematic clusters include crowdfunding dynamics (signaling theory, collective decision-making), crisis informatics (vaccine misinformation, humanitarian violence detection), and conflict modeling (agent-based simulations, peace accord efficiency). His methodological signature combines natural language processing with network science to decode complex human behaviors in digital ecosystems. His research has been presented at premier venues including IC2S2, NetSci, ICA, ACL, ACM, IEEE, and AAAI conferences, with publications spanning WebSci, CSCW, CHI, and EMNLP proceedings. This demonstrates sustained impact across computational social science and human-computer interaction communities. Dr. Dambanemuya actively mentors students in academic and industry career development, leveraging prior industry experience at Microsoft, Dataminr, and Liberty Mutual to bridge theoretical research with practical applications. His commitment to student success extends beyond classroom instruction to professional pathway guidance.

• Geoinformatics
• 3D/4D City Modeling
• Digital Twins
• +5 more

Prof. Thomas H. Kolbe is a full-time faculty member at the Technical University of Munich , holding the Chair of Geoinformatics . His research focuses on spatial-temporal-semantic modeling and 3D/4D urban environments , with expertise in digital twins , CityGML standards , and smart city infrastructure . Initiator of international standards CityGML and IndoorGML Co-author of 15+ peer-reviewed publications (2025-2024) on 3D city modeling Key projects: 3DCityDB , Smart District Data Infrastructure His work bridges geospatial information science with urban simulation and indoor navigation , emphasizing semantic interoperability and urban sustainability . He leads teams at the Leonhard Obermeyer Center and Munich Data Science Institute .

• Automatic text analysis
• Information search
• IT project management
• +2 more

Natalia Sergeevna Belova is an Associate Professor in the Department of Software Engineering at the Faculty of Computer Science, National Research University Higher School of Economics (HSE University) in Moscow. She has been working at HSE since 2012 with 13 years of scientific and teaching experience. Education: 2010: Candidate of Technical Sciences from Moscow State University of Instrument Engineering and Computer Science, specialty 05.13.11 "Mathematical and software support for computing machines, complexes and computer networks" 2009: Postgraduate study from Moscow State University of Instrument Engineering and Computer Science 2005: Engineer qualification in "Computers, complexes, systems and networks" from Moscow State Academy of Instrument Engineering and Computer Science Research Interests: Dr. Belova's research focuses on automatic text analysis, information search, IT project management, embedded databases, and project-based learning in engineering education. Her work bridges theoretical computer science with practical applications in software engineering education and industry. She has made significant contributions to pattern recognition, face identification systems, and the development of computationally efficient methods for intelligent systems processing multimedia information. Publications Trend: Dr. Belova's research has evolved from foundational work on embedded databases to more recent contributions in computer vision, affect recognition, and AI applications. Her early work (2009-2013) focused on database systems reliability and project-based learning methodologies. Since 2015, her research shifted toward computer vision, pattern recognition, and deep learning applications. Her most recent publications (2022-2025) demonstrate expertise in AI applications across various domains including transportation systems and video analysis. Scientific Achievements: Recipient of the Grant of the President of the Russian Federation for young doctors of science MD-306.2017.9 (2017-2018) Gratitude from the Vice-Rector of HSE University (February 2025) Gratitude from the Faculty of Computer Science, HSE University (July 2023) Multiple publication bonuses for journals in List A and international peer-reviewed publications (2016-2025) Best Teacher award for 2016-2017 Member of the High Professional Potential Group (HSE personnel reserve) Teaching and Mentoring: Dr. Belova has supervised over 25 bachelor's theses on diverse software engineering topics including mobile applications, web platforms, biometric identification systems, and educational software tools. She teaches courses on "Group Dynamics and Communications in Professional Software Engineering Practice" and "Economics of Software Engineering." Her commitment to project-based learning methodology is evident in both her research and teaching practice. Professional Development: Dr. Belova actively participates in advanced training programs, including recent courses on modernization of educational programs in software engineering (2025) and problems of training modern specialists in software engineering (2024).

Giorgio AusielloView profile

Professor

• Theoretical Computer Science
• Algorithms
• Graph Theory
• +3 more

Giorgio Ausiello is a Full Professor at Sapienza University of Rome, where he is a member of the Algorithm Design and Engineering research group. His office is located in room A101, and his contact telephone number begins with 005. His research spans theoretical computer science with a strong emphasis on graph algorithms, online algorithms, and approximation techniques. Key contributions include foundational work on graph vitality, resilient graph spanners, and combinatorial optimization, particularly in planar and st-planar graphs. His methodological approach integrates theoretical rigor with practical network analysis applications. Analysis of his recent publications reveals dual research trajectories: ongoing technical innovation in graph algorithms (e.g., max-flow vitality computations) and significant historical contributions documenting the evolution of theoretical computer science in Italy and the EATCS society. This combination of algorithmic research and historical scholarship defines his unique academic profile. Scientific awards: No specific awards were mentioned in the provided source materials. Advising and grants: The source materials do not specify any graduate students, postdoctoral researchers, or external research grants. He actively participates in the Algorithm Design and Engineering research group at Sapienza University of Rome, which focuses on both theoretical foundations and practical implementations of algorithmic solutions for complex computational problems.

Domenico LemboView profile

Professor

• Knowledge Representation and Reasoning
• Description Logics
• Ontology-Based Data Access
• +6 more

Domenico Lembo is a Full Professor at Sapienza University of Rome, affiliated with the Department of Computer, Automatic and Management Engineering. He is a leading figure in Knowledge Representation and Reasoning, focusing on Description Logics, Semantic Web, and Ontology-Based Data Access (OBDA). His research spans information integration, inconsistency-tolerance, and controlled query evaluation, with significant contributions to theoretical and applied data management. Academic Roles: Full Professor (since 2004), Program Committee Chair for major AI/DB conferences (IJCAI, AAAI, ISWC), Co-founder of OBDA Systems startup Leadership: Head of CAIRNE Rome Office (since 2023), General Chair of SEBD 2025, Vice-President of RR Conference Steering Committee Research Interests: Lembo's work bridges Description Logics with database theory, enabling efficient query answering over inconsistent data. He pioneered DL-Lite framework for tractable ontologies, developed tools like MASTRO and Graphol for visual ontology modeling, and advanced controlled query evaluation with epistemic policies for privacy-preserving systems. Awards: 2021 AAAI Classic Paper Award for DL-Lite 2024 IJCAI Distinguished Paper Award 2020 ISWC Best Poster/Demo Award Exceptional Guest Editor, Semantic Web Journal (2014) Teaching: He teaches courses on databases, data science, and computer science fundamentals. Currently coordinating 'Fondamenti di Programmazione I' and 'Data Management for Data Science', with extensive experience in course design and educational innovation.

• Quantum Computation
• Quantum Programming
• Formal Methods
• +6 more

Professor Mingsheng Ying (University of Technology Sydney) is a Distinguished Professor specializing in quantum programming , quantum verification , and the foundations of artificial intelligence . He leads the Centre for Quantum Software and Information and co-founded the Quantum Lab . His work bridges quantum computation with formal methods and reasoning under uncertainty. Education : Mathematics, Fuzhou Teachers College (1981) Research Interests His research spans: Quantum programming languages and verification techniques Model checking quantum systems and cryptographic protocols Quantum machine learning robustness Entanglement theory and distributed quantum computation Recent Publications Key contributions include: Quantum error correction verification frameworks Quantum register machine architecture Hamiltonian simulation parallelization Symbolic execution for quantum debugging Robustness tools like VeriQR Awards & Editorial Roles NSF China Distinguished Young Scholar Award (1997) China National Science Award (2008) Co-Editor-in-Chief, ACM Transactions on Quantum Computing Vice President, International Fuzzy Systems Association (2005) Leadership & Grants He oversees 14 active grants (2010–2029) from: Australian Research Council (ARC Discovery Projects) National Natural Science Foundation of China Sydney Quantum Academy Baidu Contract Research His grants fund research in quantum program verification, entanglement classification, and distributed quantum protocols.

Eleazar LealView profile

Associate Professor

• Spatial Databases
• Stream Databases
• Database Algorithms
• +3 more

Eleazar Leal serves as an Associate Professor in the Swenson College of Science and Engineering at the University of Minnesota Duluth, where he advances research and education in database systems and high-performance computing. His academic work bridges theoretical computer science with practical data-intensive applications. His research program focuses on optimizing database technologies for modern hardware architectures, with particular emphasis on: Spatial database systems for geographic information processing Real-time analytics in stream database environments Parallel algorithm design for multicore processors GPU acceleration techniques for database operations Scalable data mining methodologies Hardware-aware query optimization These interconnected research areas address critical challenges in big data processing, enabling efficient handling of complex spatial and temporal datasets through innovative hardware-software co-design approaches. Dr. Leal maintains active collaborations with industry partners to translate theoretical advances into practical database solutions, with ongoing work exploring the integration of machine learning techniques into next-generation database engines. Professional correspondence should be directed to eleal@d.umn.edu or via telephone at +1 218 726 8452, with appointments scheduled exclusively through email consultation.

• High Performance Computing (HPC)
• Cloud Computing
• Interconnection Networks
• +3 more

Dr. Ernst Gunnar Gran is an Affiliated Researcher at the Simula Research Laboratory , specializing in the Department of High Performance Computing . With a career spanning over a decade, his research focuses on optimizing network performance in large-scale computing environments. PhD in Congestion Management in Lossless Interconnection Networks (2008) Co-developer of the NorNet Core multi-homed research testbed Research Focus Gran’s work addresses critical challenges in: InfiniBand hardware optimization and congestion control Self-adaptive networking for HPC-cloud integration Resource management in multi-tenant clusters Efficient routing algorithms for fat-tree architectures Real-time anomaly detection in time-series data Edge-cloud ecosystem performance modeling Publication Trends His recent research (2020-2022) emphasizes: Distributed traffic prediction using LSTM customization Lightweight anomaly detection frameworks Integration of mobile edge computing with multi-cloud systems Prior work (2015-2018) established foundational advancements in: Fat-tree reconfiguration algorithms Virtualized HPC network architectures Fault-tolerant routing strategies for complex topologies SR-IOV vSwitch implementations Technical Contributions Developed patented network reconfiguration systems Created dynamic cloud architectures with SA query caching Advanced partition-aware routing techniques Optimized load-balancing mechanisms for HPC environments

• information-theoretic privacy and security
• quantum error-correction
• distributed machine learning

Eirik Rosnes is a Chief Research Scientist and Head of the Department of Information Theory at Simula UiB. His research spans information-theoretic privacy and security, quantum error-correction, and distributed machine learning. Research Interests Information-theoretic privacy and security Quantum error-correction Distributed machine learning Recent Publications His work focuses on quantum error-correcting codes, private information retrieval protocols, and coding strategies for DNA storage and federated learning. Notable trends include advancements in generalized quantum Tanner codes, concatenated codes for DNA sequencing channels, and privacy-preserving distributed computing techniques. Scientific Awards None mentioned in the provided text. Current Role Head of the Department of Information Theory at Simula UiB, with expertise in coding theory, privacy, and quantum computing applications.

Danny HuckeView profile

Researcher

• Data Compression
• Grammar-Based Compression
• Empirical Entropy
• +3 more

Danny Hucke is a researcher affiliated with the University of Siegen, Department of Electrical Engineering and Computer Science. His work focuses on advanced data compression techniques, algorithmic complexity, and formal verification of streaming systems. Education: PhD in Grammar-based compression for strings and trees (University of Siegen, 2019) Research Interests: Driven by challenges in grammar-based compression, empirical entropy metrics, and formal language processing in streaming environments, his research bridges theoretical computer science and practical algorithm design. Key areas include: Data Compression for Trees and Strings Sliding-Window Algorithms Circuit Complexity Algorithmic Entropy Analysis Scientific Contributions: His work has been recognized with a Best Paper Award at SPIRE 2016. Publications span top-tier venues like IEEE Transactions on Information Theory , ACM TOCT , and conferences including ICALP, STACS, and LATIN. Contact: Department of Electrical Engineering and Computer Science, University of Siegen, Hölderlinstrasse 3, D-57076 Siegen. Email: hucke@eti.uni-siegen.de . Phone: +49-271-740-3415. Office: Room H-A 7104. Collaborations: Conducted research within the group of Prof. Markus Lohrey, collaborating extensively with Moses Ganardi, Louisa Seelbach, and Eric Nöth.

Guy BreslerView profile

Associate Professor

• Information Theory
• Statistical Inference
• Computational Complexity
• +2 more

Guy Bresler is Associate Professor in the Department of Electrical Engineering and Computer Science at MIT, with affiliations in LIDS, Theory of Computation, Center for Statistics, FODSI, and IDSS. He researches the interface of information theory, statistics, theoretical computer science, and probability, developing mathematical models to understand computational tractability of high-dimensional inference. His research characterizes relationships between combinatorial structure and computational tractability in inference problems, with applications in statistical physics, random graphs, and learning theory. Recent work establishes fundamental limits in statistical estimation and develops efficient algorithms for high-dimensional problems. Publications demonstrate consistent focus on computational-statistical tradeoffs across random graphs, Markov chains, neural networks, and graphical models. Techniques involve information-theoretic analysis, reduction methods, and phase transition characterization. He advises doctoral students Kiril Bangachev, Alina Harbuzova, Chenghao Guo, and Brice Huang. Previously advised researchers include Enric Boix-Adserà, Dheeraj Nagaraj, and Mina Karzand. He co-organized the Simons Institute program on computational aspects of high-dimensional inference.

Dariusz DereniowskiView profile

Professor

• Graph Algorithms
• Theoretical Computer Science
• Search and Evacuation in Graphs
• +2 more

Prof. Dariusz Dereniowski serves as a Professor in the Department of Algorithms and Systems Modelling at the Faculty of Electronics, Telecommunications and Informatics, Gdańsk University of Technology. His active research profile is evidenced by recent publications and ongoing projects, with contact maintained via darderen@pg.edu.pl and phone 583471956. His research centers on theoretical computer science, specializing in graph algorithms and computational complexity. Key areas include evacuation strategies in graphs, noisy binary search under error probability, energy-constrained exploration methods, and bicriteria tree-depth optimization. This work addresses fundamental challenges in algorithm design under constraints like congestion avoidance and query inaccuracies. Analysis of his 2023-2025 publications reveals a cohesive research trajectory focused on optimizing graph traversal under physical and informational constraints. These studies advance theoretical foundations while enabling applications in network routing, multi-agent coordination, and combinatorial optimization through novel algorithmic approaches. Prof. Dereniowski leads OPUS-funded projects including "Graph modeling of search processes" (2019-2022, UMO-2018/31/B/ST6/00820) and "Przeszukiwanie struktur grafowych" (2016-2019, UMO-2015/17/B/ST6/01887), demonstrating sustained grant acquisition within the Department of Algorithms and Systems Modelling. Though formal advisees aren't listed, his project management role indicates research team leadership.

• Machine Learning
• Parallel and Distributed Computing
• Graph Theory
• +6 more

Giuseppe Agapito is an Associate Professor and senior research scientist at Magna Graecia University of Catanzaro, working within the Department of Law, Economics and Sociology. His academic profile spans both teaching responsibilities and active research in computational fields. His research focuses on computational intelligence techniques applied to complex real-world problems, particularly in machine learning, parallel and distributed computing, and graph theory. His work demonstrates strong interdisciplinary applications, especially in biology and omics sciences where he develops methods to leverage the vast amounts of data being produced. Agapito has published over 100 papers in international journals and conference proceedings. His recent publications show a strong focus on graph-based machine learning approaches, sentiment analysis techniques, and bioinformatics applications. His research trajectory indicates a progression from bioinformatics applications toward more general machine learning frameworks with applications across multiple domains. As an active member of the academic community, he serves as a reviewer for scientific journals and participates as chair and program committee member for national and international conferences. His editorial work for PeerJ Computer Science demonstrates his standing in the academic community. His teaching responsibilities include courses on Computer Science and Data Analysis within the Department of Law, Economics and Sociology, suggesting an interdisciplinary approach that applies computational methods to social sciences domains.

Christian Wulff-NilsenView profile

Associate Professor

• Algorithms
• Graph Theory
• Planar Graphs
• +5 more

Christian Wulff-Nilsen is an Associate Professor in the Department of Computer Science at the University of Copenhagen, specializing in algorithms and complexity. His work focuses on theoretical computer science with particular emphasis on graph algorithms and data structures. His primary research areas include: Developing efficient algorithms for general graphs and specialized graphs like planar graphs Graphs excluding fixed minors Dynamic graph problems with focus on dynamic connectivity Classical algorithmic problems including shortest paths and max flow/min cut Light and sparse spanners for general graphs Wulff-Nilsen's research is purely theoretical, with recent publications addressing problems like VC Set Systems in Minor-free Graphs, Exact Distance Oracles for Planar Graphs, and Dynamic Connectivity. His work frequently appears in top theoretical computer science venues including SODA, FOCS, and the Journal of the ACM. His research has accumulated 68 publications with significant citations, demonstrating impact in the theoretical computer science community. He collaborates extensively with international researchers across multiple institutions, contributing to advancements in graph algorithms and computational complexity.

Pascal RichardView profile

Professor

• Real-Time Systems
• Scheduling Algorithms
• Embedded Systems
• +5 more

Pascal Richard is a Full Professor specializing in Real-Time Systems at the Institute of Technology, University of Poitiers. He is affiliated with the LIAS (Laboratoire d'Ingénierie des Applications de la Résolution des Systèmes) laboratory, which has locations at both ENSIP (École Nationale Supérieure d'Ingénieurs de Poitiers) in Poitiers and ISAE-ENSMA (Institut Supérieur de l'Aéronautique et de l'Espace - École Nationale Supérieure de Mécanique et d'Aérotechnique) in Chasseneuil. His research spans over two decades with continuous publication from 1999 through 2023. Professor Richard's primary research interests focus on real-time scheduling theory, embedded systems, and avionics. His work particularly emphasizes AFDX networks , cache-related preemption delays , self-suspending tasks , and worst-case response time analysis . His research bridges theoretical foundations with practical applications in safety-critical systems, particularly in the aerospace domain. He has made significant contributions to the understanding of scheduling anomalies, feasibility analysis, and the development of approximation schemes for complex real-time problems. His publication record demonstrates strong collaboration with researchers across France and internationally, with consistent contributions to major real-time systems conferences including RTSS, ECRTS, and RTNS. His work shows an evolution from foundational scheduling theory toward increasingly complex systems including multiprocessor platforms, mixed criticality systems, and integrated modular avionics architectures. Professor Richard has contributed to the real-time community through numerous journal publications in Real-Time Systems , IEEE Transactions on Computers , and IEEE Transactions on Industrial Informatics , among others. His most recent work continues to address cutting-edge challenges in real-time scheduling for modern computing platforms.