جستجوی استاد راهنمای دانشگاهی

Mehtaab Sawhneyمشاهده پروفایل

استادیار

• combinatorics
• probability
• analytic number theory
• +۱ مورد دیگر

Mehtaab Sawhney is a Clay Research Fellow and a tenure-track assistant professor at Columbia University specializing in combinatorics, probability, analytic number theory, and theoretical computer science. His academic journey began at the University of Pennsylvania where he enrolled in a Bachelor of Engineering in Computer Science (2016-2017), then continued at MIT where he earned a Bachelor of Science in Mathematics with Minor in Computer Science (2017-2020), followed by a Doctor of Philosophy in Mathematics (2020-2024) under the advisorship of Yufei Zhao. His research spans probabilistic combinatorics, random matrix theory, additive number theory, and theoretical computer science. Sawhney's work bridges theoretical mathematics with computational applications, focusing on random structures, additive combinatorics, and spectral properties of discrete objects. His publications demonstrate a strong interdisciplinary approach that connects number theory with probabilistic methods to solve complex combinatorial problems. The analysis of his publication record reveals a consistent focus on foundational mathematical structures with applications across multiple domains. His work on random graphs, additive bases, and arithmetic progressions has established him as a leading researcher in modern combinatorics, often collaborating with prominent mathematicians including Ashwin Sah, Yufei Zhao, and Vishesh Jain. His research output shows remarkable depth and breadth, with contributions to both pure mathematics and theoretical computer science. 2024 Clay Research Fellow 2021 Frank and Brennie Morgan Prize for Outstanding Research in Mathematics by an Undergraduate Student (joint with Ashwin Sah) Churchill Scholar 2020 Best Student Paper STOC 2021 (Joint with Ryan Alweiss, Yang Liu) Best Student Paper ITCS 2022 (Joint with Yang Liu, Ashwin Sah) 2023 Hartley Rogers Jr. Prize 2022 Charles W. and Jennifer C. Johnson Prize (joint with Ashwin Sah) NSF Graduate Fellowship Sawhney has established a robust research program with significant contributions across multiple mathematical disciplines. His frequent collaborations with top researchers worldwide indicate an active and influential research network. While specific advisees aren't listed in available information, his extensive publication record with numerous co-authors suggests active mentorship of junior researchers through collaborative projects.

Andrea Waltherمشاهده پروفایل

استاد

• Nonlinear Optimization
• Algorithmic Differentiation
• Mathematical Optimization
• +۳ مورد دیگر

Andrea Walther is a Professor of Mathematical Optimization at the Humboldt University of Berlin, holding a position within the Faculty of Mathematics and Natural Sciences. She leads the Mathematical Optimization research group at the Institute of Mathematics, focusing on algorithmic differentiation, nonlinear optimization, and applied mathematics. Her academic journey includes a Diploma in Business Mathematics (1996, University of Bayreuth), a PhD (1999, TU Dresden), and habilitation (2008, TU Dresden). She has held roles such as Junior Professor at TU Dresden (2007–2008) and Professor at the University of Paderborn (2009–2019) before joining Humboldt in 2019 as a MATH+ Professor. Education : 1991–1996: Studies in Business Mathematics, University of Bayreuth 1996: Diploma in Business Mathematics, University of Bayreuth 1999: PhD in Mathematics, TU Dresden 2008: Habilitation, TU Dresden Her research interests center on optimization methods, particularly algorithmic differentiation (e.g., ADOL-C software), nonsmooth optimization, and applications in engineering and machine learning. She leads initiatives like the Cluster of Excellence MATH+ and contributes to projects such as the Transregio 154. Key Projects: Co-PI of DFG Project 'Mixed-integer non-smooth optimization for gas market problems' (2020–2022) Principal Investigator in MATH+ Projects (EF3-7, AA2-7) Co-developer of ADOL-C, a widely used tool for algorithmic differentiation Notable awards include being a SIAM Fellow. Her work bridges theoretical advancements and practical applications, with contributions to energy sector optimization, inverse problems, and computational frameworks for solving complex systems.

Martin Skovgaard Andersenمشاهده پروفایل

دانشیار

• Optimization
• Signal Processing
• Machine Learning
• +۱۲ مورد دیگر

Martin Skovgaard Andersen is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), where he specializes in Scientific Computing. His research integrates numerical methods, optimization, and machine learning to solve complex computational problems in engineering and data science. Education: Ph.D., University of California, Los Angeles (2006–2011) M.Sc., Aalborg Universitet (2001–2006) Postdoc, Linköping University, Sweden (2011–2012) His research interests include optimization (particularly conic and stochastic programming), numerical algorithms, signal processing, system identification, and fast solvers for integral equations. He works extensively on matrix analysis, regularization, and low-rank approximations, contributing to both theoretical and applied advancements in computational mathematics. The recent publications highlight a strong trend in developing efficient numerical algorithms for large-scale optimization and solving integral equations. His work emphasizes preconditioning, matrix truncation, and Bayesian inversion, with applications in electromagnetics, structural health monitoring, and network identification. There is a consistent focus on improving computational efficiency and scalability of solvers. Scientific Awards: No specific awards mentioned in the provided text. Andersen actively supervises PhD students and leads multiple research projects, including those on non-symmetric conic optimization, data-sparse models, and fast direct solvers. He is the Principal Investigator (PI) on projects related to physics-informed structural health assessment. His collaborative network spans Denmark and international institutions, particularly in computational mathematics and engineering. Labs and Research Teams: He is affiliated with the Scientific Computing section at DTU, which focuses on high-performance computing, numerical algorithms, and mathematical modeling. His work is embedded in a collaborative environment involving researchers in optimization, control theory, and computational electromagnetics.

J. Garrett Morrisمشاهده پروفایل

پژوهشگر

• Programming Languages
• Type Systems
• Functional Programming
• +۴ مورد دیگر

J. Garrett Morris is a researcher and teacher at the University of Iowa's Department of Computer Science, with previous affiliation to the University of Kansas. His work focuses on programming languages, type systems, and formal verification. Active contributor to conferences like POPL, ICFP, and Haskell Recognized for research in session types, linear logic, and functional programming His publications span topics including Exceptional Asynchronous Session Types , Partial Type Constructors , and Constrained Type Families . While no specific awards or students are mentioned in the scraped data, his academic activities include committee roles and keynote sessions.

• Deductive Verification
• Interactive Theorem Proving
• Automated Reasoning
• +۴ مورد دیگر

Yong Kiam Tan is a research scientist at the Institute for Infocomm Research (A*STAR, Singapore) and holds a joint appointment as a Nanyang Assistant Professor at the College of Computing and Data Science, Nanyang Technological University (NTU, Singapore). He earned his PhD in Computer Science (Pure and Applied Logic) from Carnegie Mellon University, supported by a National Science Scholarship (BS-PhD) from A*STAR, Singapore. His research focuses on Deductive verification and interactive theorem proving Applications in automated reasoning, compilers, formalized mathematics, hybrid systems, and cybersecurity (cryptography) Development of verified tools like the CakeML compiler and KeYmaera X for hybrid systems His recent work spans formal verification of machine learning models, cryptographic protocols, and hybrid systems, with a strong emphasis on tool development and practical applications. Notable trends include integrating theorem proving with SAT solving and model-counting techniques for security verification. Scientific awards include: CMU SCS Distinguished Dissertation Award 2022 Distinguished Paper Award at CAV 2024 Best Paper and Best Repeatability Evaluation Awards at HSCC 2022 Peter Landin Prize at IFL'15 Best Tool Paper Award at FM'19 He actively recruits students and postdocs for fully funded positions at NTU and A*STAR, and collaborates with researchers such as Wei-Lin Wu (A*STAR) Joe Watt (A*STAR) Ciaran McCreesh (University of Glasgow) Magnus Myreen (Chalmers University)

• Formal Methods
• Satisfiability (SAT)
• Satisfiability Modulo Theories (SMT)
• +۱۱ مورد دیگر

Enric Rodríguez Carbonell is a faculty member at the Department of Computer Sciences within the Faculty of Computer Science at Universitat Politècnica de Catalunya (UPC). He is a key member of the LOGPROG - Lògica i Programació research group, focusing on formal methods, automated reasoning, and combinatorial optimization. Research Interests: His work centers on satisfiability (SAT), satisfiability modulo theories (SMT), and their applications in program verification, constraint solving, and optimization. He investigates techniques such as conflict-driven learning, invariant generation, and Max-SMT for proving termination and safety. His research bridges theoretical foundations with practical applications in software analysis and industrial problem-solving. Publication Trends: His recent publications (2020–2024) show a sustained focus on enhancing SAT and SMT solvers, particularly in pseudo-Boolean reasoning, integer linear programming, and multi-conflict analysis. Earlier works established contributions in non-linear arithmetic, termination proofs, and efficient encodings for cardinality constraints, reflecting a long-term commitment to foundational and applied aspects of automated reasoning. Scientific Awards: Best student paper award at SAT 2024 Advising and Grants: Rodríguez Carbonell has contributed to multiple competitive R+D+i projects under Spain’s State Research Plans, indicating active grant involvement. He has co-authored doctoral theses and educational initiatives like Jutge.org, demonstrating engagement in academic supervision and pedagogical innovation. Labs and Teams: He is a core researcher in the LOGPROG group at UPC, which specializes in logic and programming, with strong collaborations across formal methods, verification, and constraint technologies.

Ruzica Piskacمشاهده پروفایل

استاد

• Software Verification
• Security and Applied Cryptography
• Automated Reasoning
• +۴ مورد دیگر

Ruzica Piskac is a Professor of Computer Science at Yale University, where she leads the Rigorous Software Engineering (ROSE) group. She has made significant contributions to the fields of software verification, security, automated reasoning, and code synthesis, focusing on improving software reliability and trustworthiness through formal techniques. Dr. Piskac received her PhD from the Swiss Federal Institute of Technology (EPFL) in 2011, where her dissertation won the Patrick Denantes Prize. Prior to joining Yale, she led an independent research group at the Max Planck Institute for Software Systems in Germany (2012-2013). Her research spans several key areas: symbolic execution for Haskell (G2), privacy-preserving formal methods (PPFM), functional reactive synthesis, verification of configuration files, and analysis of software updates. Her work consistently bridges theoretical formal methods with practical applications in real-world systems. Dr. Piskac's recent publications demonstrate a strong trend toward applying formal verification techniques to emerging challenges including large language models, quantum computing security, legal accountability of automated systems, and cyber-physical systems. Her research increasingly intersects with AI, cryptography, and legal domains while maintaining strong foundations in formal methods. Her scientific achievements have been recognized with numerous prestigious awards: Multiple Amazon Research Awards Yale University's Ackerman Award for Teaching and Mentoring Facebook Communications and Networking Award Microsoft Research Award for the Software Engineering Innovation Foundation (SEIF) Patrick Denantes Prize for her PhD dissertation Dr. Piskac has graduated five PhD students, four of whom have gone on to become assistant professors of computer science. She has served as Program Chair of the 37th International Conference on Computer Aided Verification and is on the Steering Committee of the Formal Methods in Computer-Aided Design conference. She leads the Rigorous Software Engineering (ROSE) group at Yale, which focuses on several key projects including: Symbolic Execution Engine for Haskell (G2) Privacy Preserving Formal Methods (PPFM) Functional Reactive Synthesis Verifications for Configuration Files Analysis of Software Updates and Configuration Files

• Economic Model Predictive Control
• Stability of Nonlinear Systems
• Chemical Reaction Networks Theory
• +۵ مورد دیگر

David Angeli is a Professor of Nonlinear Network Dynamics in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. Affiliations: Control and Power Research Group Energy Futures Lab His research focuses on Economic Model Predictive Control, Stability of Nonlinear Systems, Chemical Reaction Networks Theory, Systems Biology, and Control of Smart Grids. He develops theoretical frameworks for networked systems with applications in energy infrastructure and biological processes, emphasizing robustness and scalability in distributed settings. Recent publications (2023-2025) highlight work on distributed control algorithms, Lyapunov-based stability certification, and small-gain theorems for interconnected systems. His research bridges control theory, game theory, and machine learning to solve problems in cyber-physical systems, particularly in resilient consensus protocols and economic optimization for heterogeneous networks. As a core member of the Control and Power Research Group and Energy Futures Lab, he contributes to sustainable energy solutions and advanced control methodologies for complex networked systems.

• Static Analysis
• Logic Programming
• Program Verification
• +۴ مورد دیگر

Manuel V. Hermenegildo is a Professor at the Universidad Politécnica de Madrid, Spain. He is a prominent researcher in the field of programming languages and static analysis, with significant contributions to logic programming, program verification, and formal methods. His work focuses on advancing static analysis techniques, compiler optimization, and energy-efficient computing. He has co-authored numerous papers and organized international conferences such as LOPSTR and SAS, demonstrating his leadership in academic and research communities. His research explores topics including abstract interpretation, runtime checking, and parallel logic programming systems. He is a key contributor to the Ciao Prolog system, emphasizing comprehensive tool integration and formal methods. His research interests span static analysis frameworks, program verification, resource usage analysis, and energy efficiency in computing. He has developed methodologies for optimizing program performance while ensuring correctness, with applications in both theoretical and applied domains. His work often bridges the gap between high-level program analysis and low-level hardware constraints, particularly in embedded systems. Recent trends in his publications include advancements in static cost analysis, dynamic inference of invariants, and tools for incremental assertion checking. His collaborations with institutions like the University of Copenhagen and the University of Kent reflect a global network in advancing computational logic and software engineering. He has been actively involved in academic service, including editorial roles for conference proceedings and journals. His contributions highlight a commitment to both foundational research and practical tools for the programming language community.

Aida Todri-Sanialمشاهده پروفایل

استاد

• Energy-Efficient Circuits
• Quantum Computing
• Neuromorphic Computing
• +۴ مورد دیگر

Aida Todri-Sanial is a Full Professor in the Integrated Circuits group of the Electrical Engineering department at Eindhoven University of Technology (TU/e). She leads the NanoComputing Research Lab and is affiliated with the Center for Quantum Materials and Technology Eindhoven (CQMT-E), EAISI, and the Integrated Circuits group. Her research focuses on energy-efficient circuits, novel computing paradigms (e.g., 3D integration, neuromorphic computing, quantum computing), and nanotechnology-driven architectures. Education: PhD in Electrical and Computer Engineering, University of California Santa Barbara (2009) Bardeen Fellow at Fermi National Accelerator Laboratory (2009–2010) Scientist/Research Director at CNRS (2011–2021) Visiting Fellow at the University of Cambridge (2016–2017) Research Interests: Dr. Todri-Sanial’s work integrates physics and electronics to design unconventional computing systems. Key areas include: Physical design optimization for energy efficiency Oscillatory neural networks (ONNs) for edge AI Quantum computing hardware and error mitigation 3D integration and monolithic-3D architectures Nanomaterials (e.g., VO₂, MoS₂) for neuromorphic and sensing applications Awards & Grants: ERC Consolidator Grant THERMODON (2023) NWO AiNed Fellowship (2024) NWO Quantum Technology Grant (2024) CNRS Bronze Medal (2016), IBM Quantum Open Science Prize (2021), and IEEE Distinguished Lecturer (2022) Labs & Teams: Principal Investigator of the NanoComputing Research Lab Lead researcher in EAISI (Eindhoven Artificial Intelligence Systems Institute) Collaborator with global institutions (e.g., IBM, STMicroelectronics)

Malte Helmertمشاهده پروفایل

استاد

• Automated Planning
• Combinatorial Search
• Artificial Intelligence
• +۷ مورد دیگر

Malte Helmert is a Professor at the University of Basel in the Department of Mathematics and Computer Science. He previously worked at the University of Freiburg's Research Group on the Foundations of Artificial Intelligence from 2001 to 2011. His research focuses on intelligent problem-solving , particularly in automated planning , combinatorial search , constraint satisfaction , and NP-hard graph problems . Helmert has made significant contributions to classical planning, including the development of the Fast Downward planning system and its derivatives. Education : Diploma in Computer Science (M.Sc.) from the University of Freiburg (2001) Ph.D. in Computer Science from the University of Freiburg (2006) Research interests encompass the theoretical and practical aspects of automated planning, including heuristic search , optimal planning , abstraction techniques , and domain-independent planning . His work explores merge-and-shrink abstractions , landmark progression , and cost partitioning algorithms for classical planning systems. Recent publications analyze advancements in pseudo-Boolean proof logging , higher-dimensional potential heuristics , and correlation complexity in planning domains. These works often integrate mathematical modeling, algorithm design, and empirical benchmarking. Scientific awards include the AAAI Fellow (2021), EurAI Fellow (2020), multiple Best Paper Awards at ICAPS and SoCS conferences, and the Computers and Thought Award (2011). He also received the VDI-Förderpreis for his Master’s thesis. Software contributions include the Fast Downward planning system, MIPS (now maintained by Stefan Edelkamp), and COVER (a vertex cover solver). Helmert has organized tutorials at ICAPS and AAAI conferences on topics like landmark progression , abstraction heuristics , and LP-based heuristics .

Konstantin Korovinمشاهده پروفایل

دانشیار

• Automated Theorem Proving
• Formal Methods
• Verification
• +۳ مورد دیگر

Konstantin Korovin is an Associate Professor and Reader in Formal Methods at the University of Manchester. He leads the Formal Methods Research Group and is a core developer of the iProver theorem prover, a tool for automated reasoning in first-order logic with applications to verification, neuro-symbolic systems, and machine learning integration. His work focuses on combining automated reasoning techniques with machine learning, particularly in areas like premise selection, neural architecture for term synthesis, and hybrid verification systems. Affiliations: Centre for Digital Trust and Society, SCorCH Project (Secure Code for Capability Hardware) Research Beacons: Digital Futures Key research interests include automated theorem proving, verification of machine learning models, non-linear constraint solving, and neuro-symbolic reasoning. He has contributed to tools like ESBMC (for C++ program verification) and SMLP (a symbolic machine learning prover). His work spans theoretical advancements in superposition calculus and practical applications in hardware verification and systems biology. Collaborations include projects on DNA-based computing, robotic scientific discovery (e.g., Genesis), and formal methods for industrial hardware verification. Korovin’s research is supported by grants from the Engineering and Physical Sciences Research Council (EPSRC) and industry partnerships.

Andrew Mackenzieمشاهده پروفایل

استاد

• Condensed Matter Physics
• Quantum Materials
• Superconductivity
• +۲ مورد دیگر

Andrew Mackenzie is a Professor at the University of St Andrews' School of Physics and Astronomy, specializing in condensed matter physics, quantum materials, and superconductivity. His research investigates strongly correlated electron systems, unconventional superconductors (notably Sr2RuO4), and quantum transport phenomena. Mackenzie directs PhD students on projects involving electron irradiation effects, elastocaloric measurements, and quantum material synthesis. He holds dual affiliations with the Max Planck Institute for Chemical Physics of Solids in Dresden. Research spans: Quantum criticality in oxide metals Anomalous electron transport regimes Strain engineering of superconductors Low-temperature material properties Awards include Fellowships from the Royal Society (2014), Royal Society of Edinburgh (2004), and American Physical Society (2011).

Thomas W. Repsمشاهده پروفایل

استاد

• Program analysis
• Abstract interpretation
• Model checking
• +۷ مورد دیگر

Thomas W. Reps is the J. Barkley Rosser Professor & Rajiv and Ritu Batra Chair in the Computer Sciences Department of the University of Wisconsin-Madison, where he has been a faculty member since 1985. He is also President of GrammaTech, Inc., which he co-founded in 1988 to commercialize research on programming environments. Reps received his Ph.D. in Computer Science from Cornell University in 1982, winning the ACM Doctoral Dissertation Award. His research spans program analysis, abstract interpretation, model checking, programming languages, and computer security. Reps's most influential work includes pioneering program slicing techniques with Susan Horwitz, development of the Cornell Program Synthesizer and Synthesizer Generator with Tim Teitelbaum, and significant contributions to interprocedural dataflow analysis. His recent work extends into quantum computing and advanced program synthesis techniques. The analysis of his publications reveals consistent focus on program analysis techniques, with recent papers exploring quantum circuit verification, abstract transformer synthesis, and program synthesis. His work bridges theoretical foundations with practical applications, often addressing scalability challenges in program analysis. NSF Presidential Young Investigator Award (1986) Packard Fellowship (1988) ACM Fellow (2005) ACM SIGPLAN Programming Languages Achievement Award (2017) Elected foreign member of Academia Europaea (2013) Multiple best paper awards including ETAPS (2004, 2008) Reps has advised numerous students, several of whom have received departmental and national recognition. His work on the Wisconsin Program-Slicing Tool led to commercial products through GrammaTech. He has served on advisory boards for significant projects including Year 2000 remediation for the Department of Defense and F/A-22 avionics software integration.

Elsa Silvaمشاهده پروفایل

استادیار

• Operations Research
• Cutting and Packing Problems
• Combinatorial Optimization
• +۲ مورد دیگر

Elsa Silva serves as Assistant Professor in the Department of Production and Systems at the School of Engineering, University of Minho, and holds a dual appointment as Senior Researcher and coordinator of the SEOR (Systems Engineering and Operational Research) group at the ALGORITMI research centre. Her academic foundation includes a PhD in Industrial and Systems Engineering (2012) and a degree in Applied Mathematics, both from the University of Minho. Her educational credentials comprise: PhD in Industrial and Systems Engineering, University of Minho (2012) Degree in Applied Mathematics, University of Minho Dr. Silva's research centers on Operations Research with pioneering contributions to Cutting and Packing Problems , where she develops hybrid algorithms combining mathematical programming with heuristics for industrial applications. Her work spans combinatorial optimization in logistics (prisoner transportation, fishing fleet routing), retail operations (shelf-space management, grocery backroom layout), and manufacturing (textile cutting, plasma processing), often addressing uncertainty and real-world constraints. She emphasizes bridging theoretical advances with practical implementations across sectors. Her recent publications (2021-2025) reveal evolving trends toward integrating uncertainty modeling with cutting stock problems, advancing 3D guillotine cutting frameworks, and solving complex logistics challenges like cross-docking and container loading. A consistent theme is the development of flexible matheuristics that balance computational efficiency with solution quality, as demonstrated in her Floating-Cuts model and adaptive sequence-based approaches. These works appear in top journals including European Journal of Operational Research and Omega , reflecting her impact on both theoretical and applied operations research. Her scientific recognition includes: Finalist for the 2015 Daniel H. Wagner Prize (INFORMS) Runner-up for the 2019 ITOR Best Paper Prize Diploma of Recognition of Pedagogical Merit (2021) Dr. Silva has supervised one post-doctoral researcher, two PhD theses, ten MSc dissertations (as supervisor/co-supervisor), and mentored three PhD students. Her academic service encompasses: Organizing two international conferences and three EURO conference streams Serving on examination boards for 5 PhDs (2 abroad) and 51 MSc theses (2 abroad) Providing 50+ peer reviews for international journals Scientific committee membership for EURO/ROADEF 2018 challenge Editorial board service for Portuguese Association for Operational Research bulletin (2022-23) As SEOR group coordinator at ALGORITMI, she leads a dynamic team developing optimization solutions for industrial partners in manufacturing, logistics, and retail. The group focuses on translating cutting-edge research into practical tools for waste reduction, logistics efficiency, and operational decision-making, maintaining strong industry-academia collaboration channels.