Petra Mutzel is a Professor of Computer Science at the University of Bonn. Her research focuses on graph algorithmics, temporal networks, and combinatorial optimization with applications in data science and bioinformatics. She holds a PhD in Computer Science from the University of Cologne (1994) and a Diplom in Mathematics from the University of Augsburg (1990). Her work emphasizes algorithmic solutions for complex graph problems, including temporal graph analysis, graph learning, and optimization frameworks for real-world networks. She has contributed to open-source libraries like Tglib for temporal graph processing and frameworks like Scaffold Hunter for medicinal chemistry. Her research spans theoretical foundations and practical implementations, with notable contributions to graph drawing, vehicle routing optimization, and protein complex analysis. Mutzel’s recent publications (2022-2025) explore temporal network dynamics, robust combinatorial optimization, and scalable graph kernel methods. She actively engages in academic leadership, organizing conferences such as WALCOM 2022, and serves on editorial boards for journals in algorithms and computational geometry.
Stefano Di Stefano is a Full Professor of Organic Chemistry at the University of Rome La Sapienza, Department of Chemistry. He holds a PhD (2000) and undergraduate degree from the same institution. His academic career spans postdoctoral research at La Sapienza, progressing through Researcher, Associate Professor roles before achieving Full Professorship in 2007. He has conducted research at Universidad Autónoma de Madrid (Spain) and Albrecht Christian Universität Kiel (Germany). Research : Focuses on supramolecular chemistry, dynamic combinatorial chemistry, and non-heme metal catalysis for C-H bond oxidation. Key projects include dissipative systems (fuel-driven molecular machines), supramolecular catalyst design, and understanding macrocyclization equilibria. Collaborates with researchers from Tor Vergata Rome, Parma, Bologna, Eindhoven, Cambridge, Girona, Manchester, and Mainz. Teaching : Teaches Organic Chemistry II, IV, and specialized courses for Chemical Sciences. Awarded the Excellent University Teaching Prize four times (2014, 2017, 2018, 2021) for his instruction in Physical Organic Chemistry. Awards : Recipient of the Italian Chemical Society's 2020 national prize for methodological advances in organic chemistry. Recognized for pioneering work in chemical fuels for molecular machines and dissipative systems. Laboratory : Based in Cannizzaro Building (office/lab 329/324), his group develops novel catalytic systems and fuel-driven devices. Recent work includes transient polymers, pH-responsive nanodevices, and biomimetic oxidation catalysts.
Dr. Chun-Long Chen is a senior research scientist at Pacific Northwest National Laboratory (PNNL) with over 80 publications and three U.S. patents. His work bridges synthetic chemistry and materials science to develop sequence-defined synthetic polymers that mimic natural proteins, focusing on biomimetic mineralization and porous materials for clean energy . Education: PhD in Physical Inorganic Chemistry, Sun Yat-Sen University (2005) BS in Chemistry, Nanchang University (2000) Affiliations: Materials Research Society American Chemical Society His research interests include peptoid synthesis and self-assembly , biomimetic mineralization , in situ AFM imaging , and chemical biology . The 15 most recent articles highlight trends in nanoparticle assembly , 2D nanomaterials , and biomimetic design for energy and biomedical applications. Scientific Awards: DARPA Fold F(x) Program Award (2014, Co-PI) LDRD Award (2013, PI) Young Investigator Award (2010, ICCBMT) Best Poster Award (2010, ACCGE-West) Nanyue Award (2005, Guangdong Province) Kaisi Fellowship (2004, Sun Yat-Sen University) Samsung Award (2003, Sun Yat-Sen University) Dupont Award (2002, Sun Yat-Sen University) Dr. Chen's work involves collaborations with institutions like University of Washington and Sun Yat-Sen University , with grants from programs such as the LDRD and DARPA . His publications emphasize nanostructure control via peptoid engineering and interdisciplinary approaches to materials design.
Benoit Hudson is an Assistant Professor at the Toyota Technological Institute at Chicago, specializing in computational geometry and algorithm design with theoretical guarantees. His work bridges practical implementation and theoretical analysis in mesh refinement, with applications to scientific computing and computer graphics. He has also contributed to auction theory and hybrid systems simulation. Research interests include: Computational geometry Mesh refinement algorithms Scientific computing Data structures Algorithm design His recent publications analyze: Volume mesh size complexity Linear-time surface reconstruction Delaunay refinement guarantees Dynamic mesh updating Parallel mesh generation He maintains the sparse-meshing.com resource and previously worked on spacecraft diagnosis systems at NASA Ames Research Center. His academic advisors included Gary Miller (Carnegie Mellon University) and Tuomas Sandholm during early PhD years.
Kathrin Hanauer is an Assistant Professor at the University of Vienna, where she is affiliated with the Research Group Theory and Applications of Algorithms and the Research Network Data Science. She conducts research in the design, analysis, and experimental evaluation of fast algorithms, with a focus on Algorithm Engineering connecting theoretical foundations with practical implementations. Her research interests include: Algorithm Engineering for practical algorithm implementation Dynamic algorithms for efficiently handling changing data Graph algorithms and network analysis Reachability problems on directed graphs Ranking problems, particularly the NP-hard Feedback Arc Set problem Network analysis, motif search, and subgraph counting Dr. Hanauer's recent publications demonstrate a strong focus on dynamic graph algorithms, with significant contributions to reachability queries, subgraph counting, and datacenter network optimization. Her work spans both theoretical algorithm design and practical implementation, often with C++ software projects. Notable contributions include the O'Reach algorithm for faster reachability queries in large graphs and several dynamic algorithms for subgraph counting and network analysis. Her scientific contributions: O'Reach: A novel approach to reachability queries in large graphs that outperforms previous methods Dynamic algorithms for four-vertex subgraph counting with efficient update operations Work on demand-aware link scheduling for reconfigurable datacenters Interdisciplinary research on normative reasoning with Aristotelian diagrams Dr. Hanauer actively supervises student research, with numerous completed theses focusing on dynamic graph algorithms, geometric algorithms, and reachability problems. Her lab maintains several software projects related to graph algorithms, including a modular algorithms library for dynamic graphs written in C++ and specialized implementations for reachability queries and subgraph counting.
Jeffrey Linderoth is a Professor in the Department of Industrial & Systems Engineering at the University of Wisconsin-Madison, within the College of Engineering. His research focuses on large-scale optimization problems, including integer programming and stochastic programming, with an emphasis on high-performance algorithms and software development. He holds a PhD from Georgia Institute of Technology (1998) and has been recognized with numerous awards, including INFORMS Fellow (2016) and multiple best paper awards in optimization journals. Linderoth is actively involved in teaching optimization courses such as COMP SCI 524 and I SY E 524, and mentors pre-dissertation and thesis research. Education: PhD (1998), MS (1994) – Georgia Tech; BS (1992) – University of Illinois Research Interests: Linderoth specializes in high-performance computing for optimization, numerical methods, and distributed algorithms. His work addresses challenges in computational grids, combinatorial optimization, and applications in fields like energy systems and computational biology. He has developed influential software tools like Minotaur for mixed-integer nonlinear programming. Recent Achievements: His 2024 work on stochastic integer programming and dual decomposition methods, as well as contributions to autocatalytic networks in origin-of-life studies, highlight his interdisciplinary impact. Linderoth has also been honored multiple times for teaching excellence, including the University Housing Honored Instructor Award (2019, 2016, 2008). Awards: Over 20 awards spanning best papers, teaching excellence, and early career recognition Grants/Projects: Includes Department of Energy funding and collaborations on optimizing power systems and minimizing cascading failures Linderoth leads research teams and contributes to academic organizations, advancing both theoretical and applied aspects of optimization science.
Dr. Sam Thompson is an Associate Professor in the School of Chemistry at the University of Southampton. His research focuses on using organic synthesis to address challenges in biology, medicine, and materials science, with a particular emphasis on protein-protein interaction inhibition, molecular recognition, and foldamer design. He holds a Senior Fellowship of the Higher Education Academy and has taught at the Universities of Cambridge, Oxford, and Southampton. Education: MChem from the University of Oxford (2004), PhD from the University of Cambridge (2008). Postdoctoral research at the University of Oxford (2009–2010), followed by Junior Research Fellowships at Pembroke College and Lady Margaret Hall (2010–2016). Joined the University of Southampton in 2016 as a Lecturer in Chemical Biology and Medicinal Chemistry, promoted to Associate Professor in 2023. Research interests include chemical biology, organic synthesis, and medicinal chemistry. Current projects involve developing peptidomimetics to disrupt protein interactions linked to diseases like breast cancer and Parkinson’s. Funded by EPSRC and BBSRC grants. Teaching experience includes lectures and small-group tutorials in chemistry and chemical biology across undergraduate programs. Supervises four PhD students in chemistry and related fields. Leading collaborations with interdisciplinary teams in Southampton’s Institute for Life Sciences and other research groups. Active in developing precision therapeutics and drug discovery methodologies.
Jochen Koenemann is a Professor & Chair in the Department of Combinatorics & Optimization at the University of Waterloo. He holds a Ph.D. in Algorithms, Combinatorics & Optimization from Carnegie Mellon University (2003) and completed a postdoc at La Sapienza University of Rome (2003-2004). His research focuses on Approximation Algorithms , Algorithmic Game Theory , and Combinatorial Optimization . Notable contributions include work on stable matchings, nucleolus computation, and network design algorithms. He has organized major events like the Hausdorff Summer School and IPCO'17 in Waterloo. Academic leadership roles include chairing conferences and serving on program committees such as EC'18, APPROX'17, and SODA'14. Teaching highlights include courses on Combinatorial Optimization , Game Theory , and Algorithmic Game Theory . He co-authored an undergraduate textbook on optimization with B. Guenin and L. Tuncel. Current advisees include M. Rundstrom, H. Sun, W. Toth, and M. VanDyk. His work frequently addresses interdisciplinary challenges, such as collaborations with SickKids Hospital on algorithmic solutions for medical applications. Professional activities include editorial roles and international collaborations. Recent research trends emphasize algorithmic frameworks for game-theoretic problems and improving approximation bounds for classical combinatorial challenges. Awards and recognitions are not explicitly listed, but his extensive program committee participation underscores his academic influence.
Professor Rhydian Lewis is a distinguished academic at Cardiff University's School of Mathematics, holding a Personal Chair since 2023. Previously, he served as a Reader (2019-2023), Senior Lecturer (2015-2019), and Lecturer (2008-2015) at the same institution, with earlier appointments at Cardiff Business School (2006-2008) and Edinburgh Napier University (2003-2006). He is a Fellow of the Higher Education Academy and serves as an Associate Editor for the International Journal of Metaheuristics. His research spans algorithmic graph theory, combinatorial optimization, and operational research, with specific expertise in graph coloring, vehicle routing, shortest path algorithms, school bus routing, automated timetabling, and metaheuristics. Lewis has made significant contributions to both theoretical and applied aspects of these fields, developing practical solutions for real-world problems in transportation, agriculture, healthcare scheduling, and network analysis. His recent publications demonstrate a strong trajectory in graph theory applications, particularly in street network analysis, payment channel networks, and livestock routing. The research shows increasing interdisciplinary connections between theoretical computer science, operations research, and practical applications in urban planning, financial technology, and agricultural engineering. His work often bridges theoretical algorithm development with practical implementation, as evidenced by his GCol Python library for graph coloring. Fellow of the Higher Education Academy Associate Editor, International Journal of Metaheuristics Guest Editor, Special Issue on Algorithms for Graphs and Networks (Algorithms, 2020) Program Committee Member for EVOCOP, PATAT, and GECCO conferences Professor Lewis actively supervises PhD students in combinatorial optimization, algorithmic graph theory, and transportation problems. His current supervisees include Monique Sciortino, Daniel Hambly, and Lukas Dijkstra, while his past students have completed research on score-constrained packing, dynamic graph coloring, dynamic arc routing, urban transportation networks, operating theatre schedules, and vehicle routing problems. His collaborative work spans multiple institutions and disciplines, particularly with researchers like P. Corcoran, J. Thompson, and D. Thiruvady. Lewis maintains active research teams focused on graph algorithms and operational research applications, with strong connections to industry through projects like the European Consortium for Mathematics in Industry. His work on school transport systems demonstrates practical impact in community applications.
Sophie Beeren is a Professor at the Department of Chemistry , Technical University of Denmark , with a research focus on Supramolecular Chemistry and non-covalent interactions in aqueous environments. Her work bridges Inorganic Chemistry , Organic Chemistry , and Physical Chemistry to engineer adaptive materials, host/guest systems, and functional nanostructures. Education: BSc. Honours (1st Class) in Chemistry (University of New South Wales, 2005), PhD in Chemistry (University of Cambridge, 2010) Her research emphasizes enzyme-mediated dynamic combinatorial chemistry for synthesizing cyclodextrins, including studies on pH-responsive templates , photocontrolled systems , and anion regulation in dynamic libraries. Recent work explores δ-cyclodextrin applications in nanoparticle stabilization and fluorescent probes. Her publications highlight trends in Cyclodextrin synthesis , Molecular recognition , and Dynamic systems , with collaborations spanning Carbohydrate chemistry , Nanochemistry , and Biotechnological synthesis . Scientific Awards: Carlsberg Foundation Young Researcher Fellowship (2019), Novo Nordisk Foundation Project Grant (2019), Villum Young Investigator Award (2017), L’Oreal UNESCO For Women in Science Prize (2016) Sophie leads a research group at DTU, mentoring PhD students like Nikolai Bjørn Akselvoll , Andreas Nilsson , and Juliane Sørensen . She has secured grants from the Carlsberg Foundation and Novo Nordisk Foundation , advancing applications in biotechnology and materials science.
Giacomo Nannicini is an Associate Professor in the Daniel J. Epstein Department of Industrial & Systems Engineering at the University of Southern California's School of Advanced Computing, with a courtesy appointment in the Ming Hsieh Department of Electrical & Computer Engineering. His research focuses on optimization broadly defined, with particular interests in algorithms, software, models of computation, and quantum computing applications. His research interests span optimization theory , quantum algorithms , computational methods , and mixed-integer programming . Nannicini has made significant contributions to both classical optimization techniques and emerging quantum computing approaches, developing algorithms that bridge theoretical foundations with practical applications in various domains. Nannicini has received numerous prestigious awards including the 2021 Beale–Orchard-Hays prize, the best paper award at IEEE QCE 2021 (quantum algorithms track), the 2016 COIN-OR Cup, the 2015 Robert Faure prize, and the 2012 Glover-Klingman prize. His publication record demonstrates consistent high-impact contributions across top journals in operations research, computer science, and quantum computing. He has successfully advised multiple PhD students who have gone on to prominent positions including research scientists at Saint-Gobain and SINTEF, as well as tenure-track faculty positions. Nannicini actively recruits PhD students interested in computational optimization, quantum optimization, GPU-enabled computational optimization, and mixed-integer derivative-free optimization.
Morten Peter Meldal is a distinguished Professor of Chemistry at the University of Copenhagen's Department of Chemistry, where he has been a faculty member since 2011. He also serves as the head of the Center of Evolutionary Chemical Biology and was previously the Vice-Institute Director of Teaching (2019-2020). His academic career includes leadership roles at the Carlsberg Laboratory as Professor & Director of the SPOCC Centre (1988-2011). Dr. Meldal's educational background features a PhD in Organic Chemistry from the Technical University of Denmark (1983), an M.Sc. in Chemical Engineering from DTU (1981), and postdoctoral training at Cambridge University and the H. C. Ørsted Institute at the University of Copenhagen. Meldal's research spans multiple cutting-edge fields at the intersection of chemistry and biology. His pioneering work in combinatorial chemistry and click chemistry has revolutionized chemical biology approaches. He has made seminal contributions to peptide synthesis, polymer chemistry, organic synthesis automation, and the development of artificial receptors and enzymes. His expertise extends to nano-scale analytical techniques including MS and NMR, biomolecular recognition, enzyme activity studies, cellular assays, and molecular immunology. The breadth of his research portfolio demonstrates his ability to bridge fundamental chemical principles with biological applications, particularly in developing novel tools for biomedical research. His specialties include computational chemistry, chemical biology, organic chemistry, polymer science, combinatorial chemistry, enzymology, protein chemistry, GPCRs, structural chemistry, immunology, molecular recognition, catalysis, and nanomaterials. His recent publications reveal a strong focus on Alzheimer's disease research, particularly on $$\text{A}\beta$$ peptide behavior and potential therapeutic interventions. There's also significant work on proteinase activity monitoring, peptide synthesis methodologies, and sustainable chemistry approaches. These publications demonstrate continued innovation in applying chemical principles to address challenging biological questions, particularly in neurodegenerative diseases and protease-related pathologies. Dr. Meldal's scientific excellence has been recognized with numerous prestigious awards: Nobel Prize in Chemistry (2022) Vincent du Vigneaud Award, American Peptide Society (2011) Ralph F. Hirschmann Award, American Chemical Society (2009) Niels Bjerrum Gold Medal in Chemistry, Denmark (1996) The Leonidas Zervas Award, European Peptide Society (1996) Throughout his career, Meldal has secured substantial research funding from major organizations including the Lundbeck Foundation, Novo Nordisk Foundation, Danish National Research Foundation, Danish Cancer Society, and various EU research programs. He has founded multiple companies including Combio A/S (2000), Versamatrix A/S (2002), and Betamab APS (2019), where he serves as CSO. His leadership extends to founding the Society of Combinatorial Sciences and organizing major international symposia in peptide research, including the 31st European Peptide Symposium (2010). Meldal leads a dynamic research group focused on evolutionary chemical biology, with particular emphasis on developing novel chemical tools and methodologies. His Center of Evolutionary Chemical Biology serves as a hub for interdisciplinary research bridging chemistry, biology, and medicine. He has published more than 300 publications, holds 21 patents, and has mentored numerous students and researchers throughout his career. His work on click chemistry has had profound implications across multiple scientific disciplines, earning him the highest recognition in science with the 2022 Nobel Prize in Chemistry.
Cunxi Yu is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) at the University of Maryland, College Park, and an affiliated faculty member in the Department of Computer Science (CS). He holds a Ph.D. from UMass Amherst (2017) and has held postdoctoral positions at Cornell University and EPFL. His research focuses on novel algorithms, systems, and hardware designs for computing and security, with notable contributions in formal verification, logic synthesis, and optical neural networks. He has received prestigious awards including the NSF CAREER Award (2021) and Best Paper Awards at ASPLOS (2025) and DAC (2023). Dr. Yu's academic journey includes prior roles at the University of Utah and industry collaborations with IBM Research. He advises a dynamic research group with PhD students in ECE and CS, and mentors undergraduate researchers. His work bridges formal methods with machine learning, emphasizing practical tools like BoolE (Best Paper Nomination, DAC 2025) and SmoothE (Best Paper Award, ASPLOS 2025). He actively contributes to conferences such as ASAP, ICCAD, and DAC through organizing committees and TPC roles. Key research areas include: - Formal Verification: Algebraic techniques for arithmetic circuits, equivalence checking, and e-graph-based reasoning. - Optical Computing: Design frameworks like LightRidge for diffractive optical neural networks. - Hardware Automation: Reinforcement learning for logic synthesis (e.g., MapTune, Gamora) and EDA tool development. - Security: Reverse engineering of camouflaged circuits and cryptographic hardware verification. His grants include a $900K NSF grant (2024) with Prof. Zhiru Zhang (Cornell) for hardware synthesis. Recent milestones include NVIDIA Academic Research Awards (2025) and DARPA funding for combinatorial optimization.
Ulrike Stege is an Associate Professor and Director of the Master of Engineering in Applied Data Science (MADS) at the University of Victoria's Faculty of Engineering and Computer Science. She holds a PhD from the Swiss Federal Institute of Technology (ETH Zurich). Her research spans computational biology, parameterized complexity, algorithm design, graph theory, and cognitive psychology. She leads initiatives in quantum computing frameworks and educational tools, including projects like SCOOP (quantum optimization) and QGrover (quantum algorithm visualization). Her work also addresses RNA pseudoknot structure prediction and the integration of quantum computing into combinatorial optimization software. Key educational contributions include developing browser-based quantum learning tools (e.g., QNotation and QuantumCrypto) and promoting computational thinking in K-12 education. Her research bridges theoretical computer science with practical applications in biology and quantum systems, emphasizing algorithmic innovation and interdisciplinary collaboration. Her publications focus on advancing quantum computing frameworks, optimizing bioinformatics algorithms, and creating accessible educational resources. Recent work addresses quantum annealing for constrained optimization, structural biochemistry of viral RNA, and hybrid quantum-classical problem-solving methods.
Rakesh Mukherjee is a postdoctoral research associate at the Principles of Biomolecular Systems group, Imperial College London . His research focuses on autonomous, enzyme-free molecular templating systems using DNA strands to enable sequence-specific catalytic assembly with minimal product inhibition. Imperial College London (Current: Postdoctoral Research Associate) EPFL (Postdoc: Cyclic Peptide Inhibitors) Ben-Gurion University (PhD: Peptide Replication Networks) Indian Institute of Technology Guwahati (MSc: Organic Chemistry) Research Interests span DNA nanotechnology , molecular replication , and non-covalent/covalent bond engineering . Key work demonstrates: DNA-based catalytic dimerization with weak product inhibition through toehold/handhold displacement Scaling to trimerization and covalent bond formation using copper-catalyzed click chemistry Information propagation in non-biological contexts via sequence-specific templating Applications include: Diagnostics and molecular biophysics through DNA strand displacement circuits Labelled oligomers for downstream tasks like selective binding and gel formation Combinatorial libraries of biologically functional molecules via DNA-templated synthesis
