Find Academic Supervisors

Carl Henrik HällView profile

Associate Professor

• Railway and Public Transport
• Transportation Engineering
• Operations Research
• +3 more

Carl Henrik Häll is an Associate Professor at Linköping University's Department of Science and Technology, within the Communications and Transport Systems division. His research focuses on railway and public transport systems, including timetable optimization, freight train rescheduling, dynamic bus lane analysis, and electric vehicle integration. He has collaborated on projects addressing infrastructure modeling, disruption recovery, and sustainable transport solutions. Key research areas include transportation engineering, operations research, and logistics. His work combines mathematical modeling, simulation, and heuristic algorithms to improve traffic flow, resource allocation, and system stability. Notable contributions include developing MILP models for freight train rescheduling and evaluating dynamic bus lane impacts using real-world simulations. Recent publications emphasize railway crew scheduling, electric bus timetabling, and robust train path insertion in non-cyclic networks. He actively participates in interdisciplinary projects, such as B-PREPARED (disaster preparedness) and EAN (electric aircraft networks), and contributes to the Swedish transport research community through conferences like STRC2025. His expertise spans both academic and applied contexts, with a focus on translating research into practical tools for transportation planners and operators.

• Electrical Power Engineering
• Renewable Energy Integration
• Electromagnetic Transients
• +3 more

Mebtu Bihonegn Beza is an Associate Professor at Chalmers University of Technology, Sweden, specializing in Electrical Power Engineering . His research focuses on power electronic converters, grid stability analysis, and HVDC transmission systems, particularly for offshore wind farm integration. Education: M.Sc., Lic.Eng., and Ph.D. in Electrical Power Engineering from Chalmers (2009, 2012, 2015) Key Research Themes: Grid-forming converters, electromagnetic transients, renewable energy system stability, and impedance/resonance analysis Recent publications (2024–2023) analyze advanced control strategies for converters, including small-signal stability, multiport architectures, and inertia emulation techniques. He collaborates on projects related to frequency-based stability tools and PhD programs with Addis Ababa University. Projects: Frequency-based analysis tool for converter-dominated grids (Swedish Energy Agency, 2023–2027) PhD program collaboration with Addis Ababa University (2018–2025) Contact: mebtu.beza@chalmers.se

Ingeborg WaernbaumView profile

Professor

• Biostatistics
• Causal Inference
• Observational Studies
• +11 more

Ingeborg Waernbaum is a Professor at the Department of Statistics, Uppsala University, and a Researcher at the Institute for Evaluation of Labour Market and Education Policy (IFAU). Her work bridges biostatistics, causal inference, and epidemiology, with a focus on observational studies and methodological innovations. Primary Affiliation: Department of Statistics, Uppsala University Secondary Affiliation: IFAU (Institute for Evaluation of Labour Market and Education Policy) Her research centers on: Causal inference methodologies for observational data Propensity score modeling and doubly robust estimation Selection bias bounding and sensitivity analysis Applications to diabetes epidemiology and socioeconomic health disparities Recent publications (2023-2025) highlight her dual focus on theoretical advances in causal effect estimation (e.g., entropy balancing, mediation analysis) and applied biostatistical studies in diabetes and public health. She has developed R packages for selection bias bounding and covariate selection, emphasizing practical tools for researchers. Key methodological contributions include: Clarifying limitations of doubly robust estimators Advancing sensitivity analysis for unmeasured confounding Examining efficiency trade-offs in propensity score methods Applied work spans: Diabetes incidence trends and complications Socioeconomic determinants of health outcomes Fracture risk analysis in pediatric populations She actively engages in: Register data analysis Statistical software development (R packages) Methodological critiques and robustness studies

Roghayeh HajizadehView profile

Lecturer

• Discrete Optimization
• Operations Research
• Mathematical Modeling
• +4 more

Roghayeh Hajizadeh is a University Lecturer at Linköping University's Department of Mathematics (MAI) and Applied Mathematics (TIMA) research group. Her work focuses on discrete optimization techniques for real-world problems like urban snow removal and air traffic control, using mathematical modeling and algorithm development. PhD in Optimization of Snow Removal in Cities (2023) Member of Mathematics and Algorithms for Intelligent Decision Making research group Key projects: Optimization of Snow Removal in Cities (2017-present) and OPT@ATM (2023-present) Research keywords include: Discrete Optimization, Operations Research, Sustainable Urban Planning, Air Traffic Control Algorithms . Teaching includes Combinatorial Optimization for Computer Science/Software Engineering programs and Supply Chain Optimization for Industrial Economics/Mechanical Engineering students. Publications (2020-2024) demonstrate expertise in: Lagrangian relaxation techniques , vehicle coordination algorithms , and tree elimination methods for snow removal; Dantzig-Wolfe decomposition for aircraft scheduling.

Hoomaan MaskanView profile

Researcher

• Signal Processing
• Statistical Learning
• Compressive Sensing
• +5 more

Hoomaan Maskan is a doctoral student at the Department of Mathematics and Mathematical Statistics, Umeå University. His research focuses on Signal Processing , Statistical Learning , and Compressive Sensing with applications in sparsity and spatio-temporal data analysis. His recent publications highlight advancements in high-resolution ODEs for accelerated optimization, nonconvex programming, and super-resolution DOA estimation. Key themes include mathematical modeling, sparse signal recovery, and algorithm design for spatio-temporal data. Research projects include " Compressive Sensing and Statistical Learning with Sparsity " (2019-2024). He is a member of the Mathematical Programming and Statistical Learning and Inference for Spatio-Temporal Data research groups.

Istvan TomonView profile

Associate Professor

• Discrete Mathematics
• Extremal and Probabilistic Combinatorics
• Geometry

Istvan Tomon is an Associate Professor in the Department of Mathematics and Mathematical Statistics at Umeå University in Sweden. His research focuses on discrete mathematics, extremal and probabilistic combinatorics, and geometry. He leads research in combinatorial structures and graph theory, with recent work exploring hereditary families, symmetric chain decompositions, and Zarankiewicz problems. His publications demonstrate broad expertise in combinatorial optimization, hypergraph theory, and geometric combinatorics. Recent articles show consistent focus on extremal problems in set systems, matrix combinatorics, and incidence geometry.

Natalya Pya ArnqvistView profile

Associate Professor

• Statistical Regression Modelling
• Functional Data Analysis
• Shape Preserving Smoothing
• +7 more

Natalya Pya Arnqvist is an Associate Professor in Mathematical Statistics at Umeå University, Sweden. She is affiliated with the Department of Mathematics and Mathematical Statistics and has active roles in research groups focused on Functional Data Analysis, Semiparametric Regression, and Statistical Learning for Spatio-Temporal Data. Her career includes prior positions at Nazarbayev University (2015-2020), University of Bath (2011-2015), and KIMEP University (2000-2005). Education : PhD in Statistics (University of Bath, UK, 2007-2010), CSc in Physical and Mathematical Sciences (Institute for Mathematics, Kazakhstan, 2000-2005). Her research centers on statistical regression modelling and functional data analysis , with significant contributions to shape constrained additive models (SCAMs) and model-based functional clustering . She has developed R packages such as scam , fdaMocca , and nilde for these methodologies. Recent publications highlight applications in applied demography , defect detection , and nonlinear state space modeling , reflecting her focus on bridging statistical theory with industrial and ecological challenges. She teaches undergraduate and graduate courses in probability, regression, and statistical learning.

• Control Systems
• Networked Systems
• Distributed Control
• +3 more

Emma Tegling is a Senior Lecturer (Associate Professor) at the Department of Automatic Control , Lund University , with a Wallenberg AI, Autonomous Systems and Software Program (WASP) professorship. She holds multiple roles including Deputy Head of Department, Project Manager, and Profile Area Member in AI & Digitalization and Natural & Artificial Cognition. Her research focuses on analysis and control of large-scale networked systems , with emphasis on distributed control, power networks, and social/epidemiological networks. Tegling earned her PhD in Electrical Engineering from KTH Royal Institute of Technology (2019) and held postdoctoral positions at MIT IDSS. She has led projects on network controllability, optimization, and societal applications. Notable contributions include scalable control design for vehicular formations and optimal control of linear cost networks. Her work aligns with UN Sustainable Development Goals related to affordable clean energy and industry innovation. Education: PhD in Electrical Engineering, KTH Royal Institute of Technology (2019) M.Sc. and B.Sc. in Engineering Physics, KTH Royal Institute of Technology (2013, 2011) Research Trends: Recent articles emphasize minimax optimal control, compositional design for nonlinear systems, and multipolar opinion dynamics in biased networks. Themes include scalability limits, distributed algorithms, and transients in networked systems. Grants & Projects: Leads WASP-funded projects on learning in networks and dynamic socio-technical systems. Involved in initiatives like the European Control Conference 2024. Supervises PhD students in control systems and network dynamics. Labs & Teams: Active in the Department of Automatic Control research groups focused on network science and AI-driven control solutions, contributing to Lund University's AI and Digitalization profile.

Ema DemirView profile

Researcher

• Educational Leadership
• Teacher Collaboration
• Educational Equity
• +5 more

Ema Demir is an Affiliated Researcher at the Center for Educational Leadership and Excellence and SSE Institute for Research (SIR) at Stockholm School of Economics. Her research examines how school leadership and organizational dynamics influence educational equity and outcomes through teacher collaboration, principal leadership, and AI-driven analysis of Swedish educational reforms. Her academic background includes: PhD in Education, University of Cambridge (2022) Master of Education, Stockholm University (2010) Master of Arts in English, Stockholm University (2010) Bachelor of Social Science (Political Science), Stockholm University (2003) Bachelor of Arts (English), Stockholm University (2001) Demir investigates organizational structures that foster teacher social capital and professional learning, emphasizing how school autonomy impacts student achievement. Her interdisciplinary work integrates policy analysis with computational methods to evaluate decades of educational reforms, particularly focusing on leadership practices that promote equity in Scandinavian contexts. Her publication trends reveal consistent emphasis on systematic reviews of leadership efficacy and school improvement pathways, highlighting non-linear approaches to turnaround success. Recent work analyzes organizational constraints on teacher collaboration and longitudinal impacts of principal preparation programs, demonstrating strong connections between leadership quality and student outcomes. Key recognitions include: Shortlisted for BERA Conference Best Paper Award (2023) Fitzwilliam College Senior Scholarship, University of Cambridge (2021, 2019) Demir mentors Stockholm educators and serves as guest lecturer for SSE's "Developing Teaching Excellence" and "Policy Ventures" PhD courses. Her research receives funding from Forte and IFAU for projects examining timetabling autonomy, principal leadership programs, and AI-driven reform analysis in partnership with Swedish municipalities and the National Library Lab. She collaborates internationally through the Swedish National Library Lab partnership and leads SSE's Literary Agenda group, facilitating cross-disciplinary discussions on literature's societal connections.

Johan HåstadView profile

Professor

• Theoretical Computer Science
• Computational Complexity
• Circuit Complexity
• +3 more

Johan Håstad is a Professor at the Department of Mathematics, School of Engineering Sciences, KTH Royal Institute of Technology. His research focuses on theoretical computer science, particularly algorithms, computational complexity, approximation algorithms, and cryptography. He is funded by the Knut and Alice Wallenberg Foundation through project grants and the Wallenberg AI, Autonomous Systems and Software Program (WASP). External Funding: Knut and Alice Wallenberg Foundation, WASP Editorial Roles: Theory of Computing, TheoretiCS Professional Activities: Cyber Defense Center, Royal Swedish Academy of Sciences (former chairman) Research Interests : • Algorithms and Complexity • Circuit Complexity • Approximation Algorithms • Quantum Computing and Cryptography Scientific Awards : Knut and Alice Wallenberg Foundation Support Labs and Teams : • Involved in KTH's Cyber Defense Center • Editor for key journals in theoretical computer science

Krzysztof MarciniakView profile

Associate Professor

• Integrable Systems
• Nonlinear Differential Equations
• Mathematical Physics
• +6 more

Krzysztof Marciniak is an Associate Professor in the Department of Science and Technology at Linköping University, Sweden. He holds a Docent title in applied mathematics and has been affiliated with the university since 1999. His research focuses on integrable nonlinear differential equations, separability structures, and Hamiltonian systems, with particular emphasis on Stäckel systems, soliton theory, and Painlevé-type equations. He collaborates closely with researchers like Maciej Blaszak and Blazej Szablikowski. Affiliations: Department of Science and Technology (ITN), Linköping University Positions: Associate Professor since 1999, Docent since 2005 Education: Ph.D. in Applied Mathematics (1998, Linköping University) M.Sc. in Theoretical Physics (1991, Adam Mickiewicz University, Poland) Research Interests: Krzysztof's work centers on the analytical and geometric properties of integrable systems, including separability in Hamiltonian systems, Stäckel transforms, and the interplay between differential equations and algebraic structures. He explores applications of these concepts to soliton hierarchies, quantum integrable systems, and Painlevé equations. His methodologies include differential algebra, geometric reduction techniques, and symmetry analysis. Teaching: He teaches courses in linear algebra and dynamical systems at the undergraduate and graduate levels, including international programs at institutions like the University of Rwanda and Makerere University. Recent courses include 'Introduction to Differential Geometry' and 'Calculus of Variations.' Professional Activities: He chairs the Saco-S union at Linköping University and has organized conferences such as the 2004 'State-of-the-art of classical separability theory.'

Katharina JochemkoView profile

Associate Professor

• Geometric Combinatorics
• Discrete Geometry
• Algebraic Combinatorics
• +3 more

Katharina Jochemko is an Associate Professor in the Department of Mathematics at KTH Royal Institute of Technology. She holds a PhD (summa cum laude) from Freie Universität Berlin and a Diplom in Mathematics (with distinction) from LMU Munich. Her research focuses on geometric and algebraic combinatorics, discrete geometry, and the geometry of polynomials, with recent explorations into applications in artificial intelligence. She leads multiple research projects funded by prestigious organizations including the Wallenberg AI, Autonomous Systems and Software Program and the Swedish Research Council. Her academic contributions include groundbreaking work on Ehrhart polynomials, lattice polytopes, and syzygy bundles, as evidenced by her extensive publication record and the Best Paper Award 2018 from TU Wien. She actively supervises PhD students and postdocs, with current advisees including Jon Pål Hamre and Aryaman Jal. She serves as an associate editor for Beiträge zur Algebra und Geometrie and represents the Swedish Mathematical Society at institutional levels. Her teaching includes advanced courses in enumerative combinatorics and graph theory at KTH. She co-organizes international research initiatives like the Polytopes and Friends conference and the MaP-Trop seminar series on matroids and tropical geometry. Her research spans foundational work in geometric combinatorics with interdisciplinary applications.

Jonna GillView profile

Lecturer

• Discrete Mathematics
• Combinatorics
• Algebraic Combinatorics
• +5 more

Jonna Gill is a Lecturer in the Department of Mathematics at Linköping University, affiliated with the research group Algebra, Geometry and Discrete Mathematics (ALGD). Her work bridges combinatorics, discrete optimization, and mathematical biology, particularly through the study of polytopes and phylogenetic tree structures. Her research focuses on discrete mathematical structures, including the k-assignment polytope, permutation patterns, and the geometry of evolutionary tree spaces. These areas lie at the intersection of algebraic combinatorics, geometric modeling, and theoretical computer science, with applications in optimization and phylogenetics. The published articles show a consistent trajectory in combinatorial geometry and its biological applications, particularly in understanding the structure of tree spaces and assignment problems through polyhedral methods. The research is theoretical but has implications in computational biology and discrete optimization. No scientific awards or honors are mentioned in the available texts. There is no information available regarding graduate student supervision, research grants, or external funding. Jonna Gill appears to be actively involved in research and teaching within the mathematics department, with a focus on theoretical contributions to discrete mathematics. No specific laboratory, research team, or collaborative center is mentioned in the provided content.

Valentin GorankoView profile

Professor

• Logic
• Artificial Intelligence
• Multi-agent Systems
• +3 more

Valentin Goranko is a Professor in the Department of Philosophy at Stockholm University, specializing in logic and its interdisciplinary applications across computer science, artificial intelligence, and multi-agent systems. His academic profile reflects a deep integration of philosophical inquiry with practical computational frameworks. Professor Goranko's research centers on the theoretical foundations of logic with specific applications to artificial intelligence, multi-agent systems, game theory, and computer science. His work develops formal frameworks for strategic reasoning, temporal logic, and coalition-based decision making, bridging abstract logical theory with concrete implementation challenges. The research demonstrates methodological sophistication through its combination of theoretical depth with practical verification considerations. Analysis of his recent publications reveals a maturing research program that has evolved from foundational work on temporal logics toward more complex applications involving structural analysis of logical systems and the synthesis of quantitative and qualitative reasoning approaches. His contributions to alternating-time temporal logic (ATL), game-theoretic semantics, and coalition logics have provided new insights into model checking and verification of multi-agent systems, with particular emphasis on socially friendly coalition logic (SFCL) and group protecting coalition logic (GPCL). Professor Goranko has authored several influential textbooks including 'Logic as a Tool' (2016), 'Temporal Logics in Computer Science' (2016), and 'Logic and Discrete Mathematics' (2015), which have become standard references in their respective fields. These works reflect his commitment to making complex logical concepts accessible while maintaining rigorous theoretical standards. At Stockholm University, he teaches Classical Logic (introductory) and Philosophical Logics II (advanced), courses that emphasize both foundational logical principles and their advanced philosophical applications. His teaching approach demonstrates a consistent focus on practical utility of logical reasoning alongside theoretical rigor, preparing students for both academic research and practical applications in computer science and artificial intelligence.

• Stochastic Analysis
• White Noise Analysis
• Non-Gaussian Analysis
• +3 more

Wolfgang Bock is an Associate Professor (Docent) in Stochastic Analysis at Linnaeus University, where he joined as a Senior Lecturer in August 2023 and was promoted to Associate Professor in December 2023. He serves as Program Director for the Master's Program in Mathematics and is a member of the Faculty Board. His academic career spans institutions in Germany, Portugal, and Sweden, with a strong focus on stochastic processes and their applications. His educational background includes: PhD in Stochastic Analysis (2013) from Technische Universität Kaiserslautern, Germany, supervised by Martin Grothaus Postdoctoral fellowship (2013-2014) at the Center of Mathematical Analysis and its Applications (CMAF) in Lisbon, Portugal Lecturer position (2014 onwards) at Technische Universität Kaiserslautern Permanent senior lecturer (Akademischer Rat) from 2015, responsible for Engineering Mathematics Bock's research centers on Stochastic Analysis, with particular expertise in White Noise Analysis, Non-Gaussian Analysis, and Mittag-Leffler Analysis. His work bridges theoretical mathematics with practical applications in epidemiology, especially in disease modeling for dengue and SARS-CoV-2. He has developed novel approaches to random time variation, non-linear Markov processes, and McKean-SDEs, contributing significantly to the understanding of complex stochastic systems. His recent publications demonstrate a consistent focus on extending classical Gaussian analysis to non-Gaussian settings, with increasing applications to real-world problems in epidemiology and physics. The research shows progression from theoretical foundations to practical applications, particularly in disease transmission modeling. Bock leads the Stochastic Analysis and Stochastic Processes research group and is also involved with the Computational Mathematics for Predictive Digital Twins (PreDiTwin) initiative. His research has attracted international collaborations across Europe, reflecting his commitment to enhancing Linnaeus University's international visibility in stochastic analysis.