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Malcolm HeywoodView profile

Professor

• Genetic Programming
• Coevolution
• Reinforcement Learning
• +12 more

Dr. Malcolm Heywood is a Professor in the Faculty of Computer Science at Dalhousie University, Halifax, Canada. He leads the Network Information Management and Security (NIMS) Lab and is actively involved in research on genetic programming, coevolution, reinforcement learning, and big data analytics. His research interests span: Genetic Programming and Evolutionary Computation Coevolution and Competitive Learning Problem Decomposition and Hierarchical Models Streaming Data Analysis and Anomaly Detection Network Security and Insider Threat Detection Reinforcement Learning in Games (Atari, ViZDoom, Dota 2) Dr. Heywood's recent publications focus on emergent behaviors in reinforcement learning using Tangled Program Graphs (TPG), benchmarking genetic programming for streaming data, and applications in cybersecurity and computational finance. His work demonstrates a strong trend toward scalable, efficient evolutionary models for complex, real-world problems. His scientific awards include: Silver placed at Human-Competitive (Humies) Competition (2018) Best Paper at EuroGP (2017) Best Paper at DETA track, ACM GECCO (2017) Best Paper at RWA track, ACM GECCO (2018) Nomination for Best Paper at DETA track, ACM GECCO (2019) He has supervised numerous graduate students, including PhD and Master's candidates, many of whom have continued research in evolutionary computation. His lab has developed open-source code distributions for Tangled Program Graphs and Symbiotic Bid-Based GP. Dr. Heywood teaches courses in Computer Organization, Introduction to AI with Gaming Applications, and Genetic Algorithms and Programming.

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Discrete Optimization
• +7 more

Nikhil Bansal holds the prestigious Patrick C. Fischer Professorship of Theoretical Computer Science in the Department of Computer Science & Engineering at the University of Michigan's College of Engineering. His research program has established him as a leading figure in theoretical computer science, with significant contributions to algorithm design and analysis, particularly in discrete optimization problems. Bansal's research focuses on theoretical computer science with emphasis on design and analysis of algorithms for discrete optimization problems. His work spans multiple areas including discrepancy theory, approximation algorithms, randomized algorithms, combinatorial optimization, complexity theory, machine learning theory, and probability. He has made significant contributions to understanding the limits of approximation algorithms and developing novel techniques for combinatorial optimization problems. Analysis of Bansal's recent publications reveals a strong focus on discrepancy theory, online algorithms, and combinatorial optimization. His work often bridges theoretical computer science with discrete mathematics and probability theory. A recurring theme across his publications is the development of novel algorithmic techniques for solving NP-hard problems with provable guarantees. His research has evolved from foundational work in approximation algorithms to more recent contributions in quantum computing complexity and stochastic optimization. Patrick C. Fischer Professor of Theoretical Computer Science Bansal has advised numerous PhD students including Marek Elias, Shashwat Garg, and Greg Koumoutsous, as well as mentoring several postdoctoral researchers. He has served on editorial boards for top journals including Journal of the ACM, Theory of Computing, and Stochastic Models, and has been active on program committees for major conferences such as STOC, FOCS, SODA, and ICALP, including serving as chair for ICALP 2021. Bansal has organized multiple academic workshops including the STOC 2020 Workshop on Recent Advances in Discrepancy and Applications, several SDP Days at CWI Amsterdam, and the Semester on Bridging Continuous and Discrete Optimization at UC Berkeley in Fall 2017.

Timo EhmkeView profile

Professor

• Educational science
• Empirical educational research
• Teacher education
• +5 more

Prof. Dr. Timo Ehmke is Full Professor and holder of the Professorship for Educational Research, in particular Empirical Educational Sciences at Leuphana University of Lüneburg . He leads an extensive research program centered on empirical educational science, teacher education, assessment, and mathematics education. Research Interests Design and evaluation of evidence-based teacher-training programs, especially in mathematics Adaptive learning support and competency-oriented instruction Impact of linguistic complexity on student performance in realistic mathematical tasks Assessment instruments for inclusive subject teaching and second-language learners Large-scale educational studies (TIMSS, NEPS) and comparative measurement of competencies Research Output & Impact Across 183 peer-reviewed publications, Prof. Ehmke’s work reveals a consistent focus on translating empirical findings into practical tools for teachers. His recent articles explore how linguistic demands affect mathematical problem-solving and how adaptive instructional strategies can close achievement gaps. The research integrates psychometrics, educational psychology, and subject-didactics to inform both policy and classroom practice. Awards & Distinctions Leuphana Transfer Award 2023 – Recognised for outstanding knowledge transfer from research to educational practice. Projects & Funding Prof. Ehmke has coordinated or co-coordinated 17 major projects since 2011, securing funding from the German Federal Ministry of Education and Research (BMBF) and the German Research Foundation (DFG) . Flagship initiatives include: LERN-IF (2021-2026): Learning-process diagnostics and feedback in inclusive subject teaching (BMBF) Effects and Interaction of Linguistic and Subject-Specific Requirements (2019-2023, DFG) Boundary-Crossing II : Transdisciplinary evaluation framework for teacher-education collaborations (BMBF) Leuphana Teacher Training 2020 : Concept development for future-oriented teacher education (BMBF) DaZKom-Video : Performance-oriented assessment of German-as-a-second-language competency among pre-service teachers (BMBF) Laboratories & Teams He heads an active research team embedded within Leuphana’s research focus on education and participates in university-wide teacher-education networks, fostering collaboration between educational researchers, subject didacticians, and school practitioners.

Rudi A. PendavinghView profile

Assistant Professor

• Combinatorics
• Matroid Theory
• Graph Theory
• +3 more

Rudi A. Pendavingh is an Assistant Professor at Eindhoven University of Technology's Mathematics and Computer Science department, specializing in Combinatorial Optimization. He earned his PhD at the University of Amsterdam in topological graph theory and has since contributed to diverse areas of combinatorics and geometry, with recent focus on matroid theory. His teaching spans mathematical programming topics including linear, integer, and semidefinite optimization. Education: PhD in Topological Graph Theory (University of Amsterdam) His research integrates combinatorial structures with geometric and algebraic methods, particularly in matroid theory, graph embeddings, and tropical geometry. Key publication themes include optimization algorithms, excluded matroid minors, and geometric invariants. Collaborations extend to institutions in mathematics and applied sciences, with notable academic output (67 research items) and external partnerships. Recent research outputs (2022-2025) highlight his work on the Colin de Verdière parameter, Dressian bounds, and tropical amoebas. While no explicit awards are mentioned in the provided text, his contributions to combinatorial optimization and network collaborations underscore his academic impact. He has supervised 29 students and contributed to 7 courses, including Discrete Optimization Modeling and Mathematics II.

Francesco MalaspinaView profile

Professor

• Vector Bundles
• Projective Algebraic Geometry
• Commutative and Non-Commutative Algebra
• +3 more

Francesco Malaspina is a Full Professor at the Department of Mathematical Sciences (DISMA) of the Polytechnic University of Turin. His research focuses on vector bundles , projective algebraic geometry , and ACM (Arithmetically Cohen-Macaulay) bundles , particularly on varieties like quadrics, Grassmannians, and multiprojective spaces. He has contributed extensively to splitting criteria for vector bundles, cohomology properties, and moduli space classification. His work bridges abstract algebraic geometry with applications in mathematical physics and topological methods. Key research areas : Vector bundles, Ulrich bundles, instanton bundles, Castelnuovo-Mumford regularity, cohomology vanishing, projective varieties. Publications include studies on Ulrich bundles on Segre-Veronese varieties, instanton bundles on flag varieties, and cohomological properties of vector bundles. His articles often explore the interplay between algebraic structures and geometric intuition, emphasizing aesthetic-driven mathematical inquiry. Teaching spans linear algebra, geometry, and advanced topics for aerospace and pure/applied mathematics programs. He has also engaged in science communication, notably through his book Seven Simple Lessons in Mathematics; on Love, Death, Football, Meringues, and Geometry , which connects abstract math to humanistic themes.

Patricia D. BrackinView profile

Professor

• Engineering Design Methodology
• Creativity and Innovation in Engineering
• Sustainability Education
• +3 more

Patricia "Patsy" D. Brackin is Professor of Mechanical Engineering at Rose-Hulman Institute of Technology, where she also serves as Director of the Engineering Design Program. She is the architect of the Home for Environmentally Responsible Engineering (HERE) living-learning community and previously directed the Operation Catapult outreach program for eleven years. Education PhD, Mechanical Engineering, Georgia Institute of Technology, 1997 MS, Mathematical Sciences, University of Memphis, 1988 MS, Nuclear Engineering, University of Tennessee, 1975 BS, Nuclear Engineering, University of Tennessee, 1974 Research Interests Dr. Brackin’s scholarship centers on engineering design methodology and creativity , with particular emphasis on embedding design experiences across all four undergraduate years. She investigates how sustainability and humanitarian engineering mindsets can be cultivated through curricular interventions such as first-year sustainability modules and capstone design courses. Additional work applies Six Sigma principles to manufacturing and medical-device design processes, informed by her industry sabbaticals with Cummins, Inc. and Eli Lilly. Her recent publications reveal a consistent focus on capstone design pedagogy , formative assessment of student teams , and professional identity formation . Collectively, these works advance evidence-based strategies for mentoring multidisciplinary engineering teams and assessing complex design outcomes. Honors & Awards ABET Fellow (2020) ASME Fellow (2016) ASME Dedicated Service Award (2015) ASEE Best Paper Awards (2012, 2010) Kern Family Foundation Fellow (2006–2007) Rose-Hulman Rosie Award (1997, 2001) Advising, Grants & Programs While specific grant amounts are not disclosed, Dr. Brackin has spearheaded several high-impact initiatives. She directs the campus-wide Engineering Design Program, integrating design experiences across multiple disciplines. She founded and continues to lead the HERE program, a living-learning community focused on sustainability and humanitarian engineering. Over an 11-year span, she directed Operation Catapult, a summer outreach program that introduces high-school seniors to engineering. These efforts collectively engage hundreds of students annually and are sustained through institutional and external partnerships. Labs, Teams & Professional Service Dr. Brackin maintains active collaboration with industry partners (Cummins, Eli Lilly) and professional societies, especially ASME and ASEE. Her leadership roles extend to ABET accreditation activities, where her expertise in design assessment informs national standards for engineering education quality.

John P. SwensenView profile

Associate Professor

• Medical Robotics
• Soft Robotics
• Steerable Needle Technology
• +3 more

John P. Swensen is an Associate Professor at Washington State University's School of Mechanical and Materials Engineering, directing the M3 Robotics Lab. His research focuses on medical robotics, particularly steerable needle technology and tunably compliant mechanisms using smart materials. Ph.D., Johns Hopkins University (2012) M.S., Mechanical Engineering, Johns Hopkins University (2009) B.S., Electrical Engineering, Utah State University (2003) Research areas include: Medical robotics and surgical devices Compliant and steerable mechanisms Smart material applications in robotics Kinematic modeling and control algorithms Recent work demonstrates waterjet-assisted needle technology achieving unprecedented curvature control and reduced tissue damage in soft tissue phantoms. Collaborations with graduate students Mahdieh Babaiasl, Fan Yang, Emily Allen, and Lee Taylor have resulted in multiple IEEE publications and conference presentations at IROS, BioRob, and ISMR.

Peter BursensView profile

Professor

• European Union Studies
• European Integration
• Multilevel Governance
• +2 more

Peter Bursens is a full professor of Political Science at the Department of Political Science, Faculty of Social Sciences, University of Antwerp, a position held since 2010. He is a senior member of the Politics and Public Governance Research Group (P&PG) and affiliated with the GOVTRUST Center of Excellence focusing on trust in multilevel governance systems. His academic roles extend to teaching at the Antwerp Management School and the Institute for Sustainable Development and Environment. He obtained his Ph.D. in Political Science from the University of Antwerp in 1999. Professor Bursens' research centers on European decision-making processes, Europeanization dynamics, federalism structures, and democratic legitimacy within multilevel political systems. As holder of a Jean Monnet Chair on 'skills teaching in European Union Studies', he develops simulation games and assessment tools for political science curricula. His work is embedded in the GOVTRUST Center of Excellence examining trust mechanisms across governance levels. Jean Monnet Chair (European Commission) He served as program director and vice-dean for education from 2012-2018, teaching European integration and multilevel political systems across Bachelor and Master programs in Political Science and International Relations. His extensive administrative involvement includes chairing the Examination Board for Bachelor Political Science and serving on the Education Committee of the Faculty of Social Sciences. Professor Bursens maintains governance roles across 15+ committees including the Faculty Council of Social Sciences, Departmental Council of Political Sciences, and Council of the Institute for Environment and Sustainable Development, reflecting deep institutional engagement.

• Cyber Security
• Federated Learning
• Network Security
• +5 more

Jonathan White serves as a Senior Lecturer in Cyber Security within the College of Arts, Technology and Environment at the University of the West of England (UWE). With over 23 years of prior industry experience in telecommunications critical infrastructure systems, he joined UWE in January 2020 after transitioning from roles as software developer, product specialist, and management leader in real-time embedded systems. His educational background includes an M.Sc. in Cyber Security (with Distinction) and B.Sc. in Computing for Real-time Systems, both from UWE, where he is currently pursuing a PhD focused on Federated Learning security tradeoffs. White's research centers on Federated Learning applications for IoT security, container security analysis, and machine learning-driven threat detection in home networks. Analysis of his publication record reveals a strong focus on practical security implementations, particularly in containerized environments (Docker security analysis, cyber ranges) and Federated Learning security frameworks. His work consistently bridges theoretical machine learning concepts with tangible security applications for IoT and edge devices, emphasizing privacy-performance tradeoffs in distributed systems. Scientific Recognition: Fellow of the Higher Education Academy (FHEA) White actively contributes to cyber security education through innovative teaching methods including the 'Cyber Funfair' immersive learning platform and Scalextric-based physical system hacking demonstrations. His industry background in telecommunications critical infrastructure informs his practical approach to security education and research, particularly regarding real-time system vulnerabilities and high-availability network security requirements. His technical expertise spans C and Python programming, network security protocols, and specialized knowledge in securing containerized environments and IoT ecosystems. Current research includes longitudinal analysis of container image vulnerabilities and development of modular cyber range infrastructure for security training.

Stylianos P. TsitsosView profile

Professor

• Wireless Radiocommunications
• Microwave Engineering
• Telecommunication Networks
• +2 more

Professor Stylianos P. Tsitsos is a distinguished academic at the Technological Educational Institute of Serres, Greece, where he serves in the Department of Informatics and Communications within the School of Technological Applications. With a career spanning over two decades in academia and industry, he has established himself as an expert in microwave engineering and telecommunications. His educational background includes a first-class Honors degree in Electrical Engineering from Democritus University of Thrace (1989), a Master's in Telecommunications and Digital Electronics from UMIST, UK (1991), and a PhD in Microwave Engineering from UMIST (1994). His research interests focus on Wireless Radiocommunications, Microwave Engineering, Telecommunication Networks, Numerical Methods in Microwave Devices, and Telecommunications Systems Simulation. Professor Tsitsos' publication record demonstrates consistent contributions to microwave filter design and analysis, with particular emphasis on ceramic monoblock filters for PCS and UMTS mobile communication systems. His work shows a progression from fundamental electromagnetic analysis techniques to practical filter design applications, reflecting both theoretical depth and engineering relevance in the telecommunications field. As a dedicated researcher, he has led multiple significant projects including the ARCHIMEDES II program focused on developing new methods for microwave filter analysis and design, and has collaborated with international organizations including TDK Corporation (Japan) and EPSRC (UK). Throughout his academic career, Professor Tsitsos has held significant administrative responsibilities, serving as Department Head from 2006-2010 and as Acting Director of the School of Technological Applications from 2009-2010, demonstrating his commitment to educational leadership alongside his research activities.

Stavros VologiannidisView profile

Assistant Professor

• Control Theory
• Robotics
• Machine Learning
• +3 more

Stavros Vologiannidis serves as an Assistant Professor in the Department of Informatics, Computer and Telecommunications Engineering at the International University of Greece. His academic career spans both teaching and research in control theory, robotics, and machine learning applications. Previously, he was associated with the Mathematics Department at Aristotle University of Thessaloniki where he completed his education and conducted postdoctoral research. Education: B.Sc. in Mathematics from Aristotle University of Thessaloniki (1997) Ph.D. in Control Theory from Aristotle University of Thessaloniki (2005) with dissertation titled 'ALGEBRAIC-POLYONYMICAL COMPUTING METHODS IN CONTROL THEORY' Dr. Vologiannidis' research focuses on Classical and Intelligent Control Theory, Robotics, and Machine Learning, with particular expertise in polynomial matrices and automatic control systems. His work bridges theoretical mathematics with practical engineering applications, especially in educational robotics and industrial control systems. He has developed several educational platforms including EUROPA, a ROS-based educational robot for teaching sensor integration and data acquisition. His publication record shows a clear evolution from theoretical control systems research toward applied machine learning and educational technology. Recent work demonstrates increasing focus on practical applications of AI in education, urban feature recognition, industrial monitoring, and robotics education across multiple educational levels from middle school through university. His research combines mathematical rigor with real-world implementation. Scientific Recognition: Excellence Scholarship in the 'Excellence Scholarships 2010' program of the Research Committee Total citations exceeding 250 with Scopus H-index of 9 Dr. Vologiannidis has secured numerous research grants and led multiple projects including 'Rapid Earthquake Damage Assessment Consortium – REDACt', 'Predictive Maintenance 4.0', and 'Development of computational methods for optimization of eigenvalue assignment problems'. He has collaborated extensively with institutions across Europe including UTIA Foundation in Prague and has participated in EU-funded projects like GALENOS and GN4-1 GÉANT Research and Education Networking. His laboratory work centers around the EUROPA educational robotics platform and the StreetScouting urban feature detection system, both of which integrate hardware, software, and educational applications. These projects demonstrate his commitment to translating theoretical research into practical educational and industrial tools.

Krisztian BalogView profile

Professor

• Information Retrieval
• Natural Language Processing
• Machine Learning
• +4 more

Krisztian Balog is a Professor of Computer Science at the University of Stavanger and a Staff Research Scientist at Google DeepMind. His work focuses on advancing AI-driven information retrieval, natural language processing, and machine learning for user-centric systems. Key affiliations include co-organizing the Sim4IA 2025 Workshop at SIGIR, leading tutorials on user simulation in generative AI, and directing the NorwAI research center’s PhD project on LLMs for recommendations. Research Interests: User simulation, conversational AI, transparency in recommender systems, and simulation frameworks like SimIIR 3 . Scientific Recognition: Recipient of the Karen Spärck Jones Award (2018) and Best Resource Paper Award at CIKM’23 . Leadership: Serves on program committees for SIGIR, WSDM, WWW, and ECIR. Co-organized workshops and tutorials at SIGIR, AAAI, and WWW. Recent Publications highlight advancements in user simulation methodologies, generative AI applications, and open web infrastructure (e.g., SimIIR 3 , OpenWebSearch.eu ). His work bridges theoretical models (e.g., Markov Decision Processes) with practical toolkits for synthetic data generation and system evaluation.

Lyne MoserView profile

Research Fellow

• Algebraic Topology
• Higher Category Theory
• Homotopy Theory
• +3 more

Lyne Moser is a Postdoc at the University of Regensburg, working in the group of Denis-Charles Cisinski as part of the DFG-funded Collaborative Research Centre Higher Invariants . She previously held a postdoctoral position at the Max Planck Institute of Mathematics in Bonn and completed her PhD at EPFL under Jérôme Scherer and Kathryn Hess. PhD : EPFL, 2021 Master Thesis : Johns Hopkins University (supervised by Emily Riehl) BSc and MSc : EPFL Her research focuses on algebraic topology, higher category theory, and homotopy theory, particularly the development of (∞,n)-categories. Key projects include the study of universal properties like (∞,n)-limits, adjunctions, and Kan extensions, leveraging connections between enriched and internal categories. She also explores higher algebraic structures and their applications to topological quantum field theory. Recent publications include work on model structures for double categories, homotopy coherent nerves, and ∞-categorical straightening-unstraightening. She received a Doc.Mobility grant from the Swiss National Foundation for her participation in the MSRI program Higher categories and categorification in 2020. Scientific Awards Swiss National Foundation Doc.Mobility grant (2020) She organized a seminar on Topics in (∞,2)-categories during the Summer 2023 at Regensburg, covering models of (∞,2)-categories, Gray tensor products, and applications in derived algebraic geometry and K-theory.

• Communication
• Rhetoric
• Writing Studies
• +5 more

Melissa Ianetta is the Class of 1958 Professor of Communication and Executive Director of the Writing and Communication Program at the School of Literature, Media, and Communication, Georgia Institute of Technology . She has co-authored foundational texts like The Oxford Guide for Writing Tutors and received awards for editorial and leadership excellence. Education: PhD in Rhetoric and Composition, The Ohio State University Her research focuses on disciplinarity , peer tutoring , writing program administration , and academic editing , with a strong emphasis on rhetoric, communication, and pedagogical innovation. Her recent work explores postdoctoral teaching fellowships in English Studies and classical rhetorical models in writing center administration. Scientific Awards: Phoenix Award for Significant Editorial or Design Achievement (Writing Center Journal) Ron Maxwell Leadership Award (National Council for Peer Tutoring in Writing, 2020) Marion Barry Distinguished Graduate Alumni Award (Bridgewater State University, 2020) Assistant Chair of the Conference on College Composition and Communication (2024-2025) Dr. Ianetta has edited College English (2017-2022) and co-edited the Writing Center Journal . She teaches courses on peer tutoring and first-year writing seminars, integrating empirical research with writing culture. Her work bridges classical rhetoric, modern pedagogy, and interdisciplinary collaboration.

Yuè LiView profile

Professor

• Computational Biology
• Machine Learning
• Population Genetics
• +4 more

Yuè Li is a Professor in the Department of Computer Science at McGill University, where he leads the Li Lab focused on machine learning applications in genomics and healthcare. His research develops computational methods for analyzing electronic health records (EHR), single-cell multi-omics data, and population genetics. Dr. Li teaches core courses including Applied Machine Learning (COMP 551), Machine Learning in Genomics and Healthcare (COMP 565), and Computer Programming for Life Sciences (COMP 204). His research interests span: AI methods for computational biology and translational healthcare Multi-modal EHR integration and clinical topic modeling Time-series health forecasting and trajectory analysis Single-cell transcriptomics and epigenomics Polygenic risk modeling and causal variant inference Regulatory genomics and functional annotation integration Publications demonstrate strong focus on transformer architectures for healthcare forecasting, Bayesian methods for genomic inference, and neural topic models for clinical phenotyping. Recent work emphasizes foundation models for single-cell data and federated learning for EHR analysis. Scientific Awards: KDD HealthDay2022 Best Paper Award for seed-guided topic modeling Dr. Li mentors graduate students and postdoctoral researchers working on machine learning applications in biomedical domains. Current lab members include Master's students Bo-Hong Wang, Claris Gu, Neda Esfehani, and Ruilin Wang, along with postdoctoral researcher Dr. Jun Bai. The Li Lab operates within McGill's School of Computer Science, developing computational frameworks to integrate heterogeneous biomedical data for improved disease understanding and clinical decision support.