جست‌وجوی استاد و پژوهشگر

Nikhil Shuklaمشاهده پروفایل

دانشیار

• Emerging Devices and Circuits
• Energy-Efficient Computing
• Ferroelectric Materials
• +۵ مورد دیگر

Nikhil Shukla is an Associate Professor at the University of Virginia with a joint appointment in Electrical and Computer Engineering and Materials Science and Engineering. His work bridges emerging hardware technologies with computational paradigms for energy-efficient systems. Education: Ph.D. in Electrical Engineering (University of Notre Dame, 2017), BS in Electronics and Telecommunications (University of Mumbai, 2010) His research focuses on emerging solid-state devices for non-Boolean computing, energy-efficient data storage , and integration of novel materials to redefine computing architectures. Key efforts include co-designing devices, circuits, and system-level solutions for Ising machines and dynamical systems solving combinatorial optimization problems. The 15 most recent articles highlight trends in oscillator-based Ising machines for optimization, ferroelectric and phase-transition materials, and hardware acceleration for NP-hard problems like Max-Cut and MaxSAT. Topics span from device physics (e.g., hafnium oxide endurance) to circuit-level implementations (FPGA accelerators, CMOS-compatible designs). Scientific Awards: IEEE TMSCS Best Paper Award (2017), STARnet LEAST Center Best Publication Awards (2015–2017), J.N. TATA and J.R.D TATA Scholarships (2011) Shukla's work at the Computing Hardware Research Lab emphasizes cross-disciplinary approaches, leveraging synchronized oscillators and correlated materials to push beyond CMOS-era limitations.

Florian Röselمشاهده پروفایل

پژوهشگر

• Optimization under Uncertainty
• Data Science
• Operations Research
• +۴ مورد دیگر

Dr. Florian Rösel is a researcher affiliated with the Department of Data Science at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). He works under the Professorship of Optimization under Uncertainty & Data Analysis led by Prof. Dr. Frauke Liers, focusing on data-driven optimization techniques and their applications in aviation logistics and complex system modeling.

Serge Gaspersمشاهده پروفایل

استاد

• Algorithms and complexity
• Graph algorithms
• Quantum algorithms
• +۸ مورد دیگر

Professor Serge Gaspers is a faculty member in the School of Computer Science and Engineering at the University of New South Wales (UNSW), specializing in algorithms for computationally intractable problems. His research focuses on parameterized algorithms, quantum algorithms, and graph theory, with applications in computational social choice and constraint satisfaction. He joined UNSW in 2012 as an ARC DECRA Fellow and later held an ARC Future Fellowship. Gaspers obtained his PhD from the University of Bergen (Norway) in 2008, followed by postdoctoral positions in Montpellier, Santiago, and Vienna. His research interests include algorithms for NP-hard problems, quantum computing, and fair resource allocation. He has been awarded grants totaling over A$2 million, including an ARC Discovery Project (DP210103849) on improved algorithms via random sampling and collaborations with Data61/CSIRO and NICTA. Notable awards include the ARC Future Fellowship (2014), IJCAI 2013 Most Educational Video Award, and DECRA (2012). Teaching: Gaspers teaches COMP6741 - Algorithms for Intractable Problems . His advising spans parameterized algorithms, quantum algorithms, and graph algorithms. Research grants highlight his work in algorithms, with a focus on turbocharging heuristics and computational complexity of resource allocation problems.

Jacques Sternمشاهده پروفایل

استاد

• Cryptography
• Cryptanalysis
• Public Key Encryption
• +۵ مورد دیگر

Jacques Stern is a renowned Professor of Computer Science at the École normale supérieure (ENS) in Paris, France, where he has held a position since 1992. He has also served as Director of the Computer Science Laboratory at ENS from 1996 to 2007 and as Chairman of the Board for Ingenico SA and the Agence Nationale de la Recherche (ANR). His work has significantly advanced cryptology, particularly in areas like public-key encryption, cryptanalysis, and cryptographic protocols. École polytechnique (1968) École normale supérieure (1968–1972) Agrégation de Mathématiques (1971) PhD in Sciences (1975) Jacques Stern's research spans foundational and applied aspects of cryptography. Key interests include complexity theory , public-key encryption , block ciphers , cryptographic protocols , and cryptanalysis . His work on coding theory and smart card applications bridges theoretical and practical security challenges. His publications emphasize cryptanalysis of public-key systems, signature schemes , and security proofs . Notable trends include lattice-based cryptography , algebraic attacks , and provable security frameworks. CNRS Gold Medal 2006 RSA Award for Excellence in Mathematics 2007 CNRS Silver Medal 2005 Prix Lazare Carnot 2003 Prix Science et Défense 2008 Fellow of IACR 2005 Jacques Stern has advised numerous researchers through collaborations with scholars like David Pointcheval, Antoine Joux, and Guillaume Poupard. His leadership roles at ENS, ANR, and ARCEP reflect his influence on national research and cybersecurity policy. He has contributed to cryptographic standards, including evaluations of AES candidates. As Director of the ENS Computer Science Laboratory (1996–2007), he fostered interdisciplinary research. His later advisory roles (e.g., ARCEP, 2012–) continue to shape electronic communications regulation.

Andrew Winslowمشاهده پروفایل

مدرس پاره‌وقت

• Computational Geometry
• Algorithmic Self-Assembly
• Discrete Geometry
• +۳ مورد دیگر

Andrew Winslow is a Part-time Lecturer in the Department of Computer Science at Tufts University, affiliated with the School of Engineering. Previously, he held positions as an Assistant Professor at the University of Texas Rio Grande Valley and worked as a software engineer at Google, Boeing, and Arizona State University. His research interests span computational geometry, algorithmic self-assembly, discrete geometry, computational complexity, and recreational mathematics. He has contributed to theoretical computer science, focusing on self-assembly systems, geometric algorithms, and puzzle complexity analysis. Winslow's work emphasizes algorithm design, with notable contributions to tile assembly models, motion planning, and geometric unfolding problems. His research bridges theoretical foundations with practical applications, such as molecular computing and game puzzle analysis. He has published extensively in venues like the Symposium on Theoretical Aspects of Computer Science (STACS) and the European Symposium on Algorithms (ESA). His academic journey includes roles in both academia and industry, reflecting a commitment to interdisciplinary problem-solving. While no formal awards are listed, his publications indicate recognition within computational geometry and self-assembly communities. Winslow’s advising and grant activities are not detailed in the provided texts, though his research collaborations suggest active participation in academic networks. He maintains a presence at Tufts University’s Department of Computer Science, contributing to education and research in theoretical computer science.

Andrew Druckerمشاهده پروفایل

استادیار

• Computational Complexity
• Theoretical Computer Science
• Kernelization
• +۶ مورد دیگر

Andrew Drucker is an Assistant Professor in the Department of Computer Science at the University of Chicago. He focuses on theoretical computer science, particularly computational complexity, to understand the inherent limits of efficient computation. PhD in EECS from MIT (2012), advised by Scott Aaronson Postdoctoral work at the Institute for Advanced Study (IAS) and University of Edinburgh His research explores algorithmic paradigms for solving NP-hard problems, such as kernelization (preprocessing reductions) and intelligent random guessing , where clever trial-and-error strategies outperform naive approaches. He also investigates non-classical proof systems involving interaction, probabilistic verification, and quantum mechanics, as well as the efficiency gains from joint computation across multiple tasks. Additional interests include prediction , polynomial approximation , and algorithmic insights into human memory . He participates in academic service as a program committee member for conferences like ITCS, FOCS, and CCC. Contact: andy.drucker@gmail.com

Ashutosh Raiمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Parameterized Algorithms
• Fixed-Parameter Tractability
• +۷ مورد دیگر

Ashutosh Rai is an Assistant Professor in the Department of Mathematics at the Indian Institute of Technology Delhi (IIT Delhi). He previously served as an Assistant Professor in the Computer Science Department at IIIT Delhi. His academic journey includes postdoctoral research at Charles University in Prague and the Hong Kong Polytechnic University. He completed his PhD and Master’s at the Institute of Mathematical Sciences (IMSc), Chennai, under the supervision of Prof. Saket Saurabh and Prof. Venkatesh Raman. His research focuses on Theoretical Computer Science, especially parameterized algorithms, fixed-parameter tractability, kernelization, and the complexity of NP-complete problems. His work bridges classical and parameterized complexity, exploring hardness and algorithmic solutions. The 15 most recent publications highlight consistent contributions to parameterized complexity, graph editing, coloring, and optimization problems. His research spans journals like Algorithmica , SIAM Journal on Discrete Mathematics , and Theoretical Computer Science , and top conferences including ICALP, IPEC, ESA, and MFCS. Key themes include kernelization, approximation in parameterized settings, and structural graph problems. He has taught courses such as Analysis and Design of Algorithms, Theory of Computation, Parameterized Algorithms, Operating Systems, and Combinatorics at IIT Delhi, IIIT Delhi, and Charles University. He has also mentored students and collaborated extensively with leading researchers in the field. Email: ashutosh.rai@maths.iitd.ac.in

• Theoretical Computer Science
• Computational Complexity
• Approximation Algorithms
• +۶ مورد دیگر

Per Austrin is a Lecturer at the Royal Institute of Technology (KTH) in the Department of Theoretical Computer Science. He has been actively involved in teaching courses such as Algorithms and Complexity (DD2352) , Advanced Algorithms (DD2440) , and Problem Solving and Programming Under Pressure (DD2458) , serving as examiner and course coordinator for several programs. His research focuses on the foundations of computational complexity, approximation algorithms, and cryptographic barriers. Key areas include hardness of approximation for constraint satisfaction problems (CSPs), combinatorial optimization, and theoretical limits in cryptography and coding theory. His work often intersects with probabilistic methods and quantum computing challenges. Recent publications highlight his contributions to understanding lower bounds in optimization problems, inapproximability thresholds, and complexity in structured combinatorial problems. Detailed information about his work can be found on his personal website: Per Austrin's Website .

Qi Chengمشاهده پروفایل

استاد

• Theoretical Computer Science
• Cryptography
• Computational Number Theory
• +۳ مورد دیگر

Qi Cheng is the Williams Company Foundation Presidential Professor of Computer Science at the University of Oklahoma, where he has been since 2001. His academic roles include leadership in theoretical computer science research and teaching. Education: Ph.D., Computer Science, University of Southern California (2001) M.S., Computer Science, Fudan University (1995) B.S., Computer Science, Nankai University (1992) Research Interests: Focuses on theoretical computer science, cryptography, computational number theory, DNA/molecular computing, and coding theory. His work explores algorithmic self-assembly, lattice-based cryptography, and polynomial system solving over finite fields. Key Contributions: Includes advancements in self-assembly theory, decoding algorithms for Reed-Solomon codes, and complexity analyses of algebraic problems. His NSF CAREER project integrated self-assembly research with educational initiatives. Grants & Awards: Recipient of the NSF Career Award (2003–2008) for self-assembly research, and multiple NSF grants (e.g., CCF-1900820, CCF-1409294) supporting work on sparse polynomials and algebraic codes. Labs/Teams: Leads research groups focused on theoretical computer science and cryptography, collaborating on projects involving post-quantum cryptography and algorithmic number theory.

Abdellah Salhiمشاهده پروفایل

استاد

• Optimization
• Metaheuristics
• Operations Research
• +۳ مورد دیگر

Abdellah Salhi is a Professor at the School of Mathematics, Statistics and Actuarial Science (SMSAS) at the University of Essex. His academic qualifications include a PhD from Aston University and a BSc from the University of Constantine. He specializes in optimization, metaheuristics, and operations research, with applications in logistics, port operations, and mathematical modeling. His research addresses complex problems such as container port scheduling, vehicle routing, and numerical solutions for biological systems. Salhi's work spans optimization algorithms like the Plant Propagation Algorithm, Genetic Algorithms, and hybrid methods for solving real-world challenges. His articles focus on multi-objective optimization, logistics efficiency, and algorithmic advancements. He has supervised numerous PhD students, contributing to academic and industrial research. While grants and funding sections are listed, specific details are not provided in the text. No dedicated labs or teams are mentioned, though collaborations are implied through his extensive publication record.

Veit Elserمشاهده پروفایل

استاد

• Theoretical Condensed Matter Physics
• Biological Physics
• Phase Retrieval Algorithms
• +۵ مورد دیگر

Veit Elser serves as Professor of Physics at Cornell University within the College of Arts and Sciences, holding continuous faculty appointments since 1988 (Assistant Professor 1988-93, Associate Professor 1993-2001, Professor 2001-present). His academic journey includes a visiting professorship at Universität Tübingen (1994-95) following postdoctoral work at ATT Bell Laboratories (1984-88). Education: B.S. from California Institute of Technology (1979) Ph.D. from U.C. Berkeley (1984) Research Focus: Professor Elser pioneers phase retrieval algorithms and image reconstruction techniques for noisy diffraction patterns, particularly in X-ray free electron laser applications (e.g., Linac Coherent Light Source). His work bridges Theoretical Condensed Matter Physics and Biological Physics , with significant contributions to protein folding and optimization of NP-hard problems . Collaborating closely with Sol Gruner's group, he advances ultra low photon flux imaging methodologies. Publication Trends: His interdisciplinary research demonstrates increasing convergence of physics and machine learning, exemplified by neural network applications to computational mathematics like Strassen multiplication. This reflects a strategic expansion from traditional condensed matter physics into algorithmic solutions for complex optimization challenges. Scientific Recognition: William L. McMillan Prize (1988) Alfred P. Sloan Fellow (1989-92) Presidential Young Investigator (1989-94) David and Lucille Packard Fellow (1989-94) Guggenheim Fellow (1994-95) Alexander von Humboldt Fellow (1994-95) Erskine Fellow (2010) Simons Fellow in Theoretical Physics (2015) Academic Leadership: Professor Elser mentors graduate researchers including Avinah Mandaiya and Megan (Renz) Flynn while securing major research funding through prestigious fellowships. His sustained Packard, Sloan, and Simons Fellowships have enabled decade-spanning investigations into computational physics. Current teaching responsibilities include PHYS 2214 (Oscillations, Waves, Quantum Physics), PHYS 4490 (Independent Study), and PHYS 6572 (Quantum Mechanics I) through 2025. Research Infrastructure: He directs an active research group developing reconstruction algorithms, maintaining close ties with experimental teams at facilities like the Linac Coherent Light Source while advancing theoretical frameworks for photon-limited imaging systems.

Juan Núñezمشاهده پروفایل

استاد پژوهشی

• Tunnel Field-Effect Transistors (TFET)
• Low-power electronics
• Emerging semiconductor technologies
• +۶ مورد دیگر

Juan Núñez is a Research Professor at the Microelectronics Institute of Seville (IMSE-CNM), part of the Spanish National Research Council (CSIC). His primary research focus lies at the intersection of emerging semiconductor technologies and novel computing paradigms, with particular expertise in tunnel field-effect transistors (TFETs) and their applications in low-power circuit design. Institution: Spanish National Research Council (CSIC) Research Institute: Microelectronics Institute of Seville (IMSE-CNM) Specialization: TFET, Pipeline, Variability, Low-power, Emerging technologies, RTD, NDR, Emerging devices, Dynamic logic Professor Núñez's research portfolio demonstrates a strong evolution from traditional digital circuit design toward emerging computing paradigms. His early work focused on optimizing conventional CMOS circuits and exploring tunnel transistors as potential successors to traditional MOSFETs. More recently, his research has pivoted toward neuromorphic computing, particularly oscillatory neural networks and Ising machines implemented with emerging devices. His work bridges the gap between device physics, circuit design, and computational applications, with a consistent emphasis on energy efficiency. The trend in his recent publications (2020-2024) shows a significant shift toward neuromorphic computing applications, particularly using phase transition materials and oscillatory networks for solving complex optimization problems. His research on VO 2 (vanadium dioxide) based Ising machines represents cutting-edge work in non-von Neumann computing architectures that could potentially solve NP-hard problems more efficiently than conventional computers.

Aaron Williamsمشاهده پروفایل

دانشیار

• Algorithms
• Combinatorics
• Computational Complexity
• +۳ مورد دیگر

Aaron Williams is an Associate Professor in the Computer Science Department at Williams College. He holds a Ph.D. in Computer Science from the University of Victoria (2009) and prior degrees from the University of Waterloo. Before joining Williams, he served as an Assistant Professor at Bard College at Simon’s Rock (2014–2018) and held postdoctoral positions at Guelph, Carleton, and McGill Universities. His research focuses on algorithms and combinatorics, with a recent emphasis on retrogame archaeology—examining how retro video games managed computational constraints. He collaborates extensively with undergraduate students on topics like puzzle complexity. Williams' educational background includes a BMath (2001) and MMath (2003) in Computer Science from Waterloo, followed by industry experience as a programmer at Corel and Autodesk. His work bridges theoretical computer science with practical applications, particularly in combinatorial generation and Gray codes. He teaches courses at Williams and maintains an active research agenda in computational puzzles and historical game analysis. His research interests span algorithm design, combinatorial enumeration, and the intersection of computer science with retro gaming. He has published widely on topics like universal cycles, de Bruijn sequences, and NP-hard puzzles.

L. Sunil Chandranمشاهده پروفایل

استاد

• Graph Theory
• Combinatorics
• Algorithms
• +۵ مورد دیگر

L. Sunil Chandran is a Professor at the Department of Computer Science and Automation, Indian Institute of Science (IISc), Bangalore. His research spans graph theory, combinatorics, algorithms, and quantum computing, with extensive work on graph coloring, boxicity, rainbow connectivity, and computational complexity. He leads a large research group, advising PhD, MSc, and ME students, many of whom hold faculty positions at premier institutions like IITs, NITs, and international universities. Chandran's research focuses on combinatorial graph algorithms, structural graph theory, and applications in quantum physics. Key areas include approximation algorithms for NP-hard problems, graph representation (boxicity/cubicity), and rainbow coloring variants. His recent work explores quantum entanglement via hypergraphs and parameterized complexity for vertex deletion problems. His publications (15 most recent shown) demonstrate a consistent focus on graph-theoretic problem-solving, with innovations in algorithmic techniques for graph coloring, combinatorial optimization, and quantum-graph intersections. Trends include increased interdisciplinary work bridging computer science, physics, and discrete mathematics. Awards and Recognitions: Adjunct Professorship at NIT Calicut (2023) INSA Fellow (2022) & INAE Fellow (2015) Alexander von Humboldt Fellowship NASI-SCOPUS Young Scientist Award (2012) MSR India Outstanding Young Faculty Award (2009-2010) INSA Young Scientist Award (2007) He has secured grants from DST, UGC, SERB, and NBHM to support postdoctoral researchers and students. Current projects include quantum-graph theory applications and parameterized algorithms. His group maintains active collaborations with institutions globally.

• Evolutionary Algorithms
• Swarm Robotics
• Optimization
• +۳ مورد دیگر

Prof. Ben Paechter is a leading academic at the School of Computing Engineering and the Built Environment , Edinburgh Napier University, specializing in evolutionary algorithms and swarm robotics. As a Professor , he has shaped research directions in computational optimization and adaptive systems for over two decades. Research Themes : Evolutionary Swarm Robotics, Multi-Objective Optimization, Hyper-heuristics, Neural Architecture Search Key Projects : FOCAS (European Commission), KTP: Intelligent Agents (Innovate UK), PerAda (Self-Aware Systems) Collaborations : CAVES Research Group, Centre for Algorithms, Visualisation and Evolving Systems His article trends demonstrate expertise in cross-domain hyper-heuristics, swarm behavior tree evolution, and neural network architecture optimization. Recent works (2023-2024) focus on GPU-accelerated evolutionary algorithms and hierarchical swarm control systems. Scientific Awards : Fellow of the British Computer Society (FBCS) Chartered IT Professional (CITP) GECCO Best Paper Nomination (2018) Advising & Grants : Supervised 5 PhD students including Paul Lapok (planar mechanisms) and Andreas Steyven (swarm diversity). Secured £2.2M+ in funding across 13 projects, including EU FOCAS (£639,999) and Innovate UK grants.