Konstantin Korovin is a Reader at the Department of Computer Science, The University of Manchester. He has held various academic roles including Senior Lecturer (2015-2023), Royal Society University Research Fellow (2007-2015), and Research Associate (2004-2007). Current research focuses on automated theorem proving , machine learning integration , and verification of hardware/software . His work includes developing systems like iProver , iProver-ML , and SMLP , which combine formal methods with ML techniques. Key contributions span non-linear constraint solving , quantified Boolean logic , and DNA computing . He has won over 20 international awards, including SMT-COMP and CASC categories. Scientific Awards : Ackermann Award, Best Thesis Prize, Best Paper at FroCoS'19, CASC and SMT-COMP prizes. He supervises PhD and postdoc researchers, with alumni working at Intel, Google, and MathWorks. His tools are applied in industry, notably by Intel for hardware optimization.
Cordula Löffler serves as a Professor at the University of Education Weingarten (PH Weingarten), specializing in language education and early childhood development. Her research focuses on practical strategies for language acquisition in daycare environments, dialect usage in educational contexts, and factors contributing to educational dropout. Her active research profile includes the WiBeG/InteG transfer project and LAVA research project, which investigate language support methodologies across standard and dialect frameworks. She has authored the practical resource "Strategies for language support in everyday daycare", providing educators with actionable techniques for implementing language development programs in routine childcare settings. Löffler maintains her research documentation through the university's official research database and academic portals, emphasizing applied educational science with direct practitioner relevance.
Cédric Elloumi is a Professor at the CEDRIC Laboratory within Conservatoire National des Arts et Métiers (CNAM), specializing in combinatorial optimization and mathematical programming. With a continuous publication record since 1992, he has established himself as a leading researcher in quadratic programming, binary optimization, and facility location problems. His research interests focus on developing exact and approximate methods for discrete optimization problems, particularly through convex reformulation techniques. Elloumi has made significant contributions to the p-center and p-median problems, quadratic assignment problems, and more recently, quantum-inspired optimization methods. His work bridges theoretical advancements with practical applications in network design, energy systems, and telecommunications. Analysis of his recent publications (2022-2025) reveals a continued focus on facility location problems, with increasing attention to robust optimization under uncertainty and emerging applications in quantum computing. His research demonstrates consistent methodological innovation, particularly in reformulation techniques that transform difficult non-convex problems into tractable forms. Throughout his career, Elloumi has maintained extensive collaborations with researchers including Billionnet, Lambert, Alès, and Plateau, resulting in numerous publications in top-tier optimization journals such as Journal of Global Optimization, Computers and Operations Research, and Mathematical Programming.
Zafeirakis Zafeirakopoulos is a researcher at the National and Kapodistrian University of Athens (Greece) in the ELIDEK project led by Prof. Maria Chlouveraki. His academic career includes roles as an assistant professor at Gebze Technical University (2016-2022) and postdoctoral research at University of Athens (Greece), Galatasaray University (Turkey), and University of Geneva (Switzerland) under the Eccellenza project of Prof. Jehanne Dousse. PhD in RISC - Research Institute for Symbolic Computation (supervised by Prof. Peter Paule and Prof. Matthias Beck) Current affiliations: Mathematics department of National and Kapodistrian University of Athens Service roles: Information Director of ACM SIGSAM, Associate Editor of ACM CCA His research focuses on symbolic computation, discrete mathematics, and computational geometry. He has developed algorithms for parametric curve topology (PTOPO) and linear Diophantine systems (Polyhedral Omega), emphasizing efficiency and geometric interpretations. Recent work involves Julia/Maple implementations for practical applications. Publication trends highlight interdisciplinary work in symbolic algorithms, polyhedral geometry, and combinatorial optimization. He actively contributes to international conferences like ACA 2025 (co-organizer) and SCALE 2022.
Prof. Yossi Bukchin is a Professor in the Department of Industrial Engineering at The Iby and Aladar Fleischman Faculty of Engineering, Tel Aviv University. His research focuses on manufacturing systems, production engineering, and operations research with particular expertise in assembly line design and optimization. His primary research interests include: Assembly systems design Assembly line balancing Facility design Operational scheduling Human factors engineering Warehouse and storage systems Prof. Bukchin's recent work demonstrates a strong focus on puzzle-based storage systems, assembly line optimization, and operations management. His research spans both theoretical developments in scheduling algorithms and practical applications in manufacturing and logistics systems. He has made significant contributions to the understanding of Bucket Brigade systems, puzzle-based storage optimization, and assembly line balancing with mixed-model production. His scholarly output shows evolution from early work on robotic assembly lines to contemporary research on machine learning applications in warehouse systems and advanced optimization techniques for modern manufacturing challenges. Contact information: Email: bukchin@tau.ac.il Phone: 03-6407941 Fax: 03-6407669 Office: Wolfson - Engineering
Rubi Debnath is a researcher at the Technische Universität München (TUM) affiliated with the Department of Embedded Systems and Internet of Things . They focus on Time-Sensitive Networking (TSN) , Machine Learning for TSN , and Optimization of TSN Scheduling Algorithms using heuristics, ILP, and DRL. Specializes in TSN Scheduling , Runtime Reconfiguration , and Wireless-TSN Actively teaches IoT Security , Software Architecture for Distributed Embedded Systems , and System Design for IoT since Winter Semester 2018/2019 Supervised over 15 Master's and Bachelor's theses on TSN, ML, and 5G-TSN integration Developed simulation frameworks like CyclicSim and 5GTQ Research Trends : Recent publications address TSN scheduling optimization , ML-assisted traffic classification , and 5G-TSN integration , with a focus on low-latency communication and industrial automation . Scientific Awards : IEEE ComSoc Four Minute PhD Thesis Competition - Third Prize Winner (Round 2), Round 1 Winner Global Fellows Program - Imperial College London, TUM, and NTU Singapore Advising and Grants : Supervised 15+ theses on TSN, ML, and 5G-TSN. Involved in the 6G Research Hub "6G-Life" and nIoVe cybersecurity framework for IoT.
Ishan Levy is a Research Fellow at the Massachusetts Institute of Technology, set to receive his PhD from MIT in 2024 under the supervision of Professor Michael Hopkins. He is internationally recognized for transformative contributions to homotopy theory, particularly for resolving Ravenel's Telescope Conjecture—a central problem in stable homotopy theory that remained unsolved for over 40 years. His educational background includes: PhD in Mathematics (expected 2024), Massachusetts Institute of Technology, Advisor: Michael Hopkins Levy's research focuses on deep structural problems in homotopy theory, with breakthrough work in algebraic K-theory and stable homotopy. He developed novel techniques that solved Ravenel's Telescope Conjecture by constructing counterexamples with Burklund, Hahn, and Schlank. His collaboration with Burklund established rational convergence of the Waldhausen tower interpolating between K-theory of integers and moduli space A(pt), while joint work with Burklund, Carmeli, Hahn, Schlank, and Yanovski achieved unprecedented estimates for growth rates of stable homotopy groups of spheres. His scientific recognition includes: Clay Research Fellow (2024-2029) Levy collaborates extensively with leading mathematicians including Robert Burklund, Tomer Schlank, Jeremy Hahn, Shaul Barkan, and Yuval Yanovski on foundational problems in algebraic topology. While no formal advising relationships or grant portfolios beyond the Clay Fellowship are documented, his research program represents a significant advance in understanding high-dimensional manifold structures through homotopy-theoretic methods. His current work centers on extending K-theoretic techniques to solve remaining challenges in stable homotopy theory, with potential implications for geometric topology and mathematical physics.
Alexander Wolff is a Professor at the Chair of Algorithms and Complexity within the Institute of Computer Science at the University of Würzburg. His work focuses on graph drawing, computational geometry, and algorithmic complexity, with applications in geographic information systems and network visualization. Chair of Algorithms and Complexity, Institute of Computer Science, University of Würzburg (since 2009) Managing Director, Institute of Computer Science (2011–2013, 2015–2017) Editorial roles in journals like JoCG and JGAA Conference leadership in Graph Drawing (GD) and SOFSEM His research explores geometric graph representations, obstacle numbers, and parameterized complexity. Recent publications address level planarity, polyhedral surface adjacency, and metro map visualization. Collaborative projects include algorithmic quality assurance and interactive industrial network visualization. Wolff’s work bridges theoretical graph algorithms with practical applications, such as optimizing public transport schematics and enhancing data accessibility. He has supervised numerous PhD students and co-authored over 100 publications, with editorial and organizational roles in major computational geometry and graph drawing conferences.
Sriram Sankaranarayanan is a Professor in the Department of Computer Science at the University of Colorado Boulder and also serves as Associate Dean for Digital Education in the College of Engineering and Applied Science. Since joining the faculty in 2009, he has built an internationally recognized research program that blends programming languages, formal methods, and control theory to reason about cyber-physical systems. Education: Ph.D. in Computer Science, Stanford University, 2005 (advisers Zohar Manna & Henny Sipma) B.Tech., Indian Institute of Technology Kharagpur (President’s Gold Medal, 2000) Research Interests: Prof. Sankaranarayanan’s work centers on hybrid dynamical systems —models that capture discrete software interacting with continuous physical environments—and on developing formal-methods techniques for their verification, control, and synthesis. Specific themes include control-barrier & Lyapunov function synthesis, neural-network verification, stochastic-game models for human-autonomy interaction, and physics-informed machine learning. Application domains range from autonomous robotics and surgical-task planning to safety-critical medical devices such as the artificial pancreas. Recent Publication Trends (2024-2025): His latest papers advance safe control synthesis (successive control barrier functions, piecewise-affine Lyapunov functions) and trustworthy AI (Taylor-model enhanced physics-informed neural networks), while also exploring game-theoretic anticipation for robotic systems interacting with uncertain human operators. Honors & Awards: NSF CAREER Award (2009) Siebel Scholar (2005) President’s Gold Medal, IIT Kharagpur (2000) CU Boulder Dean’s Award for Outstanding Junior Faculty (2012) CU Boulder Outstanding Teaching Award (2014) CU Boulder Provost’s Faculty Achievement Award (2014) Coursera Outstanding Innovation Award (2022) Student Advising & Grants: He has mentored numerous PhD students; recent graduates include Dr. Emily Jensen, Dr. Monal Narasimhamurthy, and Dr. Kandai Watanabe (2024). His group regularly publishes at top venues such as HSCC, POPL, PLDI, CAV, and WAFR, supported by NSF, NIH, and industry grants. Group & Teaching: Prof. Sankaranarayanan leads activities within the Programming Languages & Verification group and teaches graduate and undergraduate courses on programming languages, algorithms, optimization, and formal methods. He is active in conference organization (e.g., PC Chair VMCAI 2025) and maintains open-source courseware and research notebooks on GitHub.
Ariane Fazeny is a Doctoral Researcher at SFB Transregio 154 since 2022, focusing on mathematical modeling, simulation, and optimization using Wasserstein metrics for gas networks. She also works as a Software Engineer for Siemens Mobility in Erlangen, contributing to powertrain technology and brake control systems validation. Educational Background Bachelor of Science (2017-2020) : Mathematics and Economics at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), with a thesis on mixed integer programs for air traffic fleet and crew assignment. Master of Science (2020-2022) : Mathematics and Economics at FAU, introducing generalized definitions for gradient, adjoint, and p-Laplacian operators on hypergraphs. Research Interests Mixed Integer Optimization Game Theory Cryptography Space Travel Fusion Power Mathematical Modeling Gas Network Optimization Hypergraph Theory Contact Email: ariane.fazeny@desy.de Affiliations Helmholtz Imaging at DESY (Notkestrasse 85, D-22607 Hamburg) SFB Transregio 154 subproject C06 LinkedIn profile
Dr. Markus Hilbert is a researcher at FernUniversität in Hagen's Faculty of Business Administration and Economics within the Department of Business Administration, especially Quantitative Methods and Business Mathematics. Since May 2018, he has conducted research and supervised student theses while completing his doctorate in May 2024 on energy-flexible production planning. He earned a Master of Science in Business Mathematics from TU Dortmund University (2017), where his thesis investigated integrated reporting in Europe and his mathematical focus centered on optimization techniques. Hilbert's research targets sustainable industrial production through model-driven analysis of energy and emission savings, developing innovative methods like the Center of Gravity indicator for sustainability assessment. His work specializes in multi-criteria optimization for eco-energy-efficient scheduling, lot-sizing, and demand response systems, directly addressing climate targets by reducing industrial CO₂ footprints. His publication portfolio reveals a concentrated trend toward operationalizing sustainability in production systems, with 5 of 6 articles (2023-2024) advancing tri-criteria optimization frameworks that balance economic, energy, and environmental objectives in real-world manufacturing contexts. Key scientific recognition includes: Best Dissertation Award at Dies Academicus 2024 Outstanding Scientific Paper Award for Young Scientists at Dies Academicus 2024 Hilbert actively mentors students on optimization topics including machine learning in metaheuristics, digital twins, and robust scheduling while leading the Applied Optimization research group. This team advances projects like drone-based vehicle routing, nurse rostering for dialysis clinics, and waste-to-energy facility management under the university's Energy, Environment & Sustainability research focus. He contributes to the Management of energy-flexible factories (MaXFab) project and the Sustainable Supply Chains research cluster as a member of the Society for Operations Research, bridging theoretical optimization with industrial decarbonization challenges.
Prof. Floris Ernst serves as Professor of Medical Robotics at the Institute for Robotics and Cognitive Systems, University of Lübeck, where he has been faculty since 2017 after joining as a research associate in 2013. He holds significant leadership roles including membership on the Steering Committee of the Graduate School 'Computing in Medicine and Life Sciences' and editorial positions with IEEE Robotics and Automation Letters and Frontiers in Robotics and AI. His research spans medical robotics , signal processing for biomedical applications , sensors for robotics , and augmented reality in surgery . Key projects include SonoBox (robotic ultrasound for pediatric fracture diagnosis), TWIN-WIN (digital supertwin technology), and robotics applications in rescue medicine. His work consistently bridges theoretical algorithm development with clinical implementation, focusing on real-world medical challenges. Prof. Ernst's recent publications (2023-2025) demonstrate strong activity across medical imaging, rescue robotics, and navigation systems. Trends show increasing focus on deep learning applications in medical imaging, real-time motion tracking for radiosurgery, and autonomous systems for emergency response. His work frequently appears in top robotics and medical imaging venues including IEEE conferences and journals. IEEE Senior Member Associate Editor, IEEE Robotics and Automation Letters (Medical Robotics) Associate Editor, Frontiers in Robotics and AI (Biomedical Robotics) As an active supervisor, Prof. Ernst guides students through courses like Medical Robotics (CS4270) and Bachelor/Master projects, with numerous publications co-authored with students. His lab maintains strong industry and clinical collaborations, particularly in medical device development and clinical robotics applications. The Robotics Laboratory (RobLab) serves as the primary research environment for his team's work on medical and rescue robotics systems.
Daniel Kráľ is an Alexander von Humboldt Professor for Discrete Mathematics at Leipzig University and an affiliated member of the Max Planck Institute for Mathematics in the Sciences (MPI MiS). Previously, he held the Donald Ervin Knuth Professorship at Masaryk University in Brno and is also an honorary professor at the University of Warwick, where he was a professor of mathematics and computer science and a member of the Centre for Discrete Mathematics and its Applications (DIMAP). His research addresses various topics at the interface of mathematics and computer science, with primary focus on structural and extremal graph theory, discrete algorithms, and combinatorial limits. The theory of combinatorial limits is an emerging area that provides analytic methods to study large graphs such as social networks, establishing new links between analysis, combinatorics, ergodic theory, group theory and probability theory. His work has been supported by prestigious ERC grants including the CCOSA Starting grant and LADIST Consolidator grant. Dr. Kráľ's scholarly output includes over 150 journal research papers and numerous conference contributions. His recent publications demonstrate continued leadership in extremal combinatorics, graph limits, and structural graph theory, with significant contributions to understanding quasirandomness, Turán densities, and the coloring of complex graph structures. Scientific Recognition: SIAM Fellow (2024) Fellow of the American Mathematical Society (2020) Philip Leverhulme Prize in Mathematics and Statistics (2014) European Prize in Combinatorics (2011) ERC Consolidator grant LADIST (2015-21) ERC Starting grant CCOSA (2010-15) Professor Kráľ has supervised numerous PhD students and postdoctoral fellows throughout his career. His editorial service includes Editor-in-Chief of SIAM Journal on Discrete Mathematics (2017-2022), Co-Editor-in-Chief of Journal of Combinatorial Theory (since 2025), and Managing editor of Advances in Combinatorics (since 2018). He has organized multiple international workshops and conferences including Oberwolfach workshops on Graph Theory and the European Conference on Combinatorics, Graph Theory and Applications (EUROCOMB'23).
Prof. Dr. Hans-Peter Lenhof holds the Chair for Bioinformatics at Saarland University since 2000, where he leads research in computational biology and disease mechanism analysis. His career includes: Postdoctoral research at Max Planck Institute for Informatics (1993-1999) Research Group Leader at MPI (1999-2000) Professor at Saarland University (2000-Present) His group develops innovative bioinformatics methods with three primary focus areas: Personalized Cancer Therapy : Creating AI/ML approaches to optimize drug selection from over 200 cancer therapeutics, addressing tumor heterogeneity through predictive modeling of treatment efficacy. Diagnosis & Prognosis : Pioneering blood-based diagnostic methods using autoantibody and miRNA profiles that demonstrate high clinical sensitivity for multiple cancers and neurological disorders through collaborative studies. Pathogenic Mechanism Analysis : Employing graph-based network models to visualize and analyze deregulated biological processes, particularly signaling cascades in cancer progression. The lab maintains active collaborations with Andreas Keller's Clinical Bioinformatics group and Eckart Meese's Human Genetics team. Computational tools developed include BALLView for molecular visualization, GeneTrail for high-throughput data analysis, and specialized frameworks for therapy optimization (MERIDA) and miRNA networks (miRTargetLink).
