جست‌وجوی استاد و پژوهشگر

Ola Svenssonمشاهده پروفایل

دانشیار

• Approximation Algorithms
• Combinatorial Optimization
• Computational Complexity
• +۳ مورد دیگر

Ola Svensson is an Associate Professor at the School of Computer and Communication Sciences , EPFL. His research spans approximation algorithms, combinatorial optimization, computational complexity, and scheduling. He holds an ERC Consolidator Grant (2023–) and previously received an ERC Starting Grant (2014–2019) and SNF grant (2019–2023). Education: PhD in Computer Science from IDSIA, Università della Svizzera italiana (2009) M.Sc. from Uppsala University (2005) Research Focus: Svensson develops novel techniques for NP-hard problems, with emphasis on primal-dual methods, LP/SDP hierarchies, and hardness proofs. His work applies to clustering, scheduling, network design, and submodular optimization. Publications: His 15 most recent works (2018–2021) focus on learning-augmented algorithms, robust optimization, and improved approximations for clustering/TSP. Key trends include integration of ML with classical algorithms and quasi-polynomial methods for combinatorial problems. Awards: Best Paper Awards at FOCS (2011, 2017) and STOC (2018) I&C Teaching Award at EPFL Advising & Grants: He advises 6 current PhD students and graduated 8 others. Major grants include ERC Starting Grant 'OptApprox' (€1.4M) and ERC Consolidator Grant 'POTCO' (€2M). Teaching: Leads courses in Advanced Algorithms, Computational Complexity, and Approximation Algorithms. He developed pedagogical frameworks for scribe notes and project-based learning in theoretical computer science.

Ayşe Nihan AVCIمشاهده پروفایل

استادیار

• Lighting Design
• Health and Well-Being in Interior Spaces
• OLED Lighting Technology
• +۴ مورد دیگر

Dr. Ayşe Nihan AVCI is an Assistant Professor at the Department of Interior Architecture, Faculty of Architecture at Çankaya University. She holds a PhD in Design (2022), Master's in Interior Architecture (2017), and Bachelor's in Interior Architecture (2010) from the same institution. Her research focuses on lighting design's impact on health and well-being, biophilic design principles, and OLED/LED lighting technologies. She has been a full-time faculty member since 2015, progressing from Research Assistant (2015-2022) to Doctoral Researcher (2022-2024) before her current role. Education: PhD in Design, Çankaya University (2017-2022) MSc in Interior Architecture, Çankaya University (2014-2017) BSc in Interior Architecture, Çankaya University (2005-2010) Research Interests: Her work integrates lighting science with human-centric design principles, emphasizing: Salutogenic lighting strategies for health promotion OLED technology's circadian rhythm effects Biophilic daylighting in historical buildings Visual comfort in workplaces Publications: Over 15 peer-reviewed articles (2016–2025) focus on OLED/LED lighting applications, circadian rhythms, and daylighting in heritage buildings. Recent work explores salutogenic design in coffee shop environments and workplace environmental quality. Awards: No specific awards listed, but active in academic service: Member of Aydınlatma Türk Milli Komitesi since 2017 Member of TMMOB İç Mimarlar Odası since 2010 Reviewer for journals including PLANARCH Grants & Projects: Led a university-supported research project (2020–2021) on lighting design's health impacts. Currently teaches courses on lighting design, materials science, and interior design fundamentals.

Xuezhe Maمشاهده پروفایل

استادیار

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Xuezhe Ma is an Assistant Professor in the Department of Computer Science at the University of Southern California's Viterbi School of Engineering. Previously, he was a Ph.D. student at Carnegie Mellon University's Language Technologies Institute, where he worked under the supervision of Professor Eduard Hovy. His academic journey includes a Master's degree from Shanghai Jiao Tong University's Center for Brain-like Computing and Machine Intelligence and a Bachelor's degree in Computer Science from the same institution. Ph.D. in Computer Science, Carnegie Mellon University (completed ~2020) M.S. in Brain-like Computing, Shanghai Jiao Tong University B.S. in Computer Science, Shanghai Jiao Tong University Dr. Ma's research spans multiple areas at the intersection of Natural Language Processing and Machine Learning, with particular focus on structured prediction, syntactic and semantic parsing, machine translation, language generation, and deep generative models. His recent work has expanded into vision-language models, large language model architectures, and applications across computer vision tasks. His research combines theoretical foundations with practical implementations, as evidenced by his development of tools like NeuroNLP2 and MaxParser. His publication record shows a clear trajectory from foundational NLP work during his PhD (including papers on dependency parsing and sequence labeling) to more recent contributions in generative models and large language systems. The 15 most recent publications reveal a strong focus on addressing fundamental challenges in generative modeling, context handling, and multimodal integration, with applications spanning literary translation, medical imaging, and news diffusion analysis. AI2 Outstanding Intern Award (2018) Dr. Ma has secured research funding supporting his work in generative models and language technologies, with projects focusing on improving the efficiency and capabilities of large language models. His research group at USC is actively working on next-generation language understanding and generation systems, with particular emphasis on context-aware modeling and multimodal integration. He has established collaborations with industry partners including the Allen Institute for AI and has contributed to open-source projects like Texar. At USC, Dr. Ma leads research in the Information Sciences Institute, directing projects on efficient large language model architectures and multimodal reasoning systems. His lab focuses on developing novel approaches to context handling, model efficiency, and multimodal integration, with applications across diverse domains including healthcare, literary analysis, and news media.

Ben Greenمشاهده پروفایل

استاد

• Additive Combinatorics
• Analytic Number Theory
• Harmonic Analysis
• +۳ مورد دیگر

Ben Green is the Waynflete Professor of Pure Mathematics at the University of Oxford and a Fellow of Magdalen College. His work spans additive combinatorics, analytic number theory, harmonic analysis, ergodic theory, discrete geometry, and group theory, with a focus on interdisciplinary approaches. Research Interests: Additive combinatorics and its applications to primes Analytic number theory (prime distribution, L-functions) Harmonic analysis (Fourier methods, spectral theory) Ergodic theory and its combinatorial applications Discrete geometry (ordinary lines, convex structures) Group theory (approximate groups, expansion) Article Trends: His recent work emphasizes multiplicative functions, Ramsey-type problems in number theory, expansion in finite groups, and extremal set theory. Themes include prime gaps, arithmetic progressions, and interactions between analysis and algebra. Scientific Awards: Clay Research Award (2004) Ostrowski Prize (2005) Whitehead Prize (2005) Leverhulme Prize (2007) European Mathematical Society Prize (2008) Royal Society Fellow (2010) Sylvester Medal (2014) Senior Whitehead Prize (2019) Advising: Ben has supervised numerous D.Phil students across additive combinatorics, analytic number theory, and related fields. Past students hold postdoctoral and academic positions globally.

Frederick A. A. Kingdomمشاهده پروفایل

استاد

• Perception
• Cognition and Cognitive Neuroscience
• Spatial Vision
• +۸ مورد دیگر

Frederick A. A. Kingdom is a Professor in the Department of Ophthalmology at McGill University's Faculty of Medicine, focusing on Perception, Cognition and Cognitive Neuroscience . His research explores the interplay between early visual feature detection (edges, bars) and intermediate stages forming contours, textures, and surfaces through spatial vision, color vision, stereopsis, texture perception, brightness/lightness perception, and transparency studies . Email: fred.kingdom@mcgill.ca Key research domains include: Perceptual Mechanisms : Lateral inhibition, contrast normalization, spatial bandpass filters, and their role in brightness/lightness perception and illusions like simultaneous brightness contrast. Color Vision : Red-green vs blue-yellow system distribution, chromatic contrast requirements for stereopsis, color-based depth processing limitations, and color-shading effects that parse surfaces vs illumination. Texture Analysis : Detection thresholds for orientation/frequency/contrast modulated textures, co-circularity in texture perception, and texture statistical sensitivity (e.g., kurtosis importance). Shape Processing : Shape-frequency/shape-amplitude aftereffects, global vs local shape coding, and contour inflection adaptation. His work combines psychophysics , fMRI , image processing , and computational modeling to dissect visual system architecture, particularly how color and luminance signals are integrated/separated in early cortical processing.

Clyde Kruskalمشاهده پروفایل

دانشیار

• Parallel Computing
• Algorithms
• Computer Architecture
• +۳ مورد دیگر

Clyde Kruskal is an Associate Professor in the Department of Computer Science at the University of Maryland, College Park. His research focuses on parallel architectures, models, and algorithms. He earned a Ph.D. from New York University in 1981 and a bachelor’s degree from Brandeis University in 1976. His work includes foundational contributions to parallel computing, such as the read–modify–write concept in distributed systems. Kruskal’s research spans topics like interconnection networks, synchronization mechanisms, and algorithm design for parallel systems. Education: Bachelor’s Degree: Brandeis University, 1976 Master’s Degree: New York University (Courant Institute), 1978 Ph.D.: New York University (Courant Institute), 1981 Research Interests: Parallel computing architectures, parallel algorithms design, multiprocessor synchronization, interconnection networks, and computational geometry problems like graph coloring and visibility analysis. His work emphasizes theoretical foundations and practical implementations in parallel systems. Notable Contributions: Kruskal co-authored the book Problems With A Point: Exploring Math And Computer Science (2019), and his research includes foundational papers on parallel prefix operations, sparse matrix algorithms, and synchronization protocols. His publications span over three decades, reflecting sustained contributions to parallel computing theory and practice. Advising & Outreach: He has mentored students through programs like the Summer Combinatorial Algorithms REU at UMD, fostering undergraduate research in algorithm design and parallel computing.

Kostas Daniilidisمشاهده پروفایل

استاد

• Computer Vision
• Robotics
• Machine Learning
• +۵ مورد دیگر

Kostas Daniilidis is the Ruth Yalom Stone Professor at the University of Pennsylvania in the School of Engineering and Applied Science , specifically the Department of Computer and Information Science . He is also affiliated with the GRASP Laboratory and Archimedes, Athena Research Center, Greece . Education : PhD in Computer Science (1992) from the University of Karlsruhe with Hans-Hellmut Nagel Diploma in Electrical Engineering (1986) from the National Technical University of Athens Research Interests : Kostas Daniilidis is a leading researcher in Computer Vision and Robotics , with significant contributions to event-based vision , equivariant learning , 3D human pose estimation , and hand-eye calibration . His work spans neural rendering , dynamic scene modeling , and low-latency sensing systems . Article Trends : Daniilidis’s recent publications focus on event cameras for low-light and high-speed applications, Gaussian splatting for real-time 3D reconstruction, and equivariant neural architectures for robust motion estimation. His work bridges deep learning with geometric vision , emphasizing human mesh recovery and multi-agent coordination . Scientific Awards : Best Conference Paper Award at ICRA 2017 IEEE Fellow (2012) Teaching : He has taught courses such as CIS580: Machine Perception and CIS121: Data Structures , alongside advanced topics in robotics and computer vision. Lab & Collaborations : As director of the GRASP Laboratory (2008–2013), he fostered interdisciplinary research in robotics, and currently collaborates with institutions like the Athena Research Center in Greece.

Nichole Bauerمشاهده پروفایل

دانشیار

• Political Communication
• Gender and Politics
• Electoral Politics
• +۳ مورد دیگر

Nichole Bauer is an Associate Professor of Political Communication at Louisiana State University (LSU), jointly affiliated with the Manship School of Mass Communication and the Department of Political Science. Her research focuses on gender and politics, particularly how strategic communication influences voter perceptions of women in political roles. Bauer’s work has been published in top journals like the Journal of Politics and Political Psychology, and she authored The Qualifications Gap: Why Women Must be Better than Men to Win Political Office , exploring the challenges women face in political elections. She also co-edited Politicking While Female , a collection examining barriers for women in politics, stemming from the Reilly Center’s 2019 Breaux Symposium. Her research interests include gendered stereotypes in political messaging, voter responses to female candidates, and the intersection of race and gender in campaigns. Bauer’s work frequently addresses how candidates navigate societal expectations and stereotypes to gain electoral support. She has also investigated media coverage of female candidates, fundraising strategies in congressional races, and the evolving abortion policy landscape post-Dobbs. Bauer’s interdisciplinary approach bridges political science, communication studies, and gender studies. Her recent publications analyze topics such as emotional appeals by women of color, gendered differences in judicial elections, and the structural ambivalence voters exhibit toward female candidates. Bauer’s contributions highlight systemic biases and the nuanced strategies women must employ to succeed in male-dominated political spheres. She is a sought-after scholar in gendered electoral dynamics and has advised on policy and communication strategies for political organizations.

Zhenhong Liمشاهده پروفایل

مدرس

• Physical Human-Robot Interaction
• Rehabilitation Robotics
• Brain-Computer Interface
• +۴ مورد دیگر

Zhenhong Li is a Lecturer in Robotics and Control at the University of Manchester, holding an EPSRC Fellowship in physical human-robot interaction. He earned his B.Eng. from Huazhong University of Science and Technology (2013), and M.Sc. and Ph.D. in Control Engineering from the University of Manchester (2014 and 2019). Before joining Manchester in 2023, he was a Research Fellow in Rehabilitation Robotics at the University of Leeds (2019–2023). His research focuses on control technologies for human-robot systems, with applications in healthcare and industry. Key areas include physical human-robot interaction for rehabilitation, brain-computer interfaces, and neuromusculoskeletal modeling. He leads the Neurorobotics Lab (NRL) at Manchester and collaborates with healthcare professionals, industries, and designers via EPSRC/STFC/Wellcome Trust funding. Notable achievements include the 2019 Best Paper Award for Unmanned Systems and the 2020 EPS International Academic Pump-priming Award. In 2025, he was elected as a Senior Member of the IEEE. He actively organizes conferences and special issues, including the 2025 IEEE UK Robotics Conference and a Frontiers special issue on intelligent rehabilitation technology. Dr. Li supervises PhD candidates in robotics and control, emphasizing interdisciplinary approaches to human-robot interaction. His lab develops cutting-edge technologies like assistive exoskeletons and adaptive control systems for healthcare and industrial applications.

Ivan Grigorievمشاهده پروفایل

مدرس

• Russian Politics
• Business-State Relations
• Constitutional Courts
• +۳ مورد دیگر

Dr. Ivan Grigoriev is a Lecturer in Russian Politics at King’s Russia Institute, part of the School of Politics & Economics within the Faculty of Social Science & Public Policy at King’s College London. His research focuses on judicial politics, business-state relations in Russia, post-Soviet reforms, and constitutional dynamics. He teaches courses such as 7YYR0002, 6YYR0002, and 4YYR0001, and supervises PhD studies on Russian political topics like federalism, elections, and business-state interactions. Grigoriev’s research interests span constitutional courts under authoritarianism, the structure of Russian society, and international organizations’ roles in post-Soviet governance. His work appears in journals like Post-Soviet Affairs , Russian Politics , and Democratization . His recent publications analyze topics such as elite dynamics in color revolutions, EU leadership programs in Eurasia, and the role of law clerks in Russia’s Constitutional Court. While no specific awards are mentioned, his contributions were noted at King’s annual awards events in 2024. Grigoriev’s advising focuses on Russian political phenomena, including authoritarian modernization and labor reforms. His research often bridges theoretical frameworks with empirical analysis of institutional adaptations under autocracy.

Michela Becchiمشاهده پروفایل

دانشیار

• Computer Architecture
• Systems Software
• Heterogeneous Computing
• +۵ مورد دیگر

Michela Becchi is an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University. She specializes in computer architecture, systems software, and applications, with a focus on heterogeneous systems, parallel algorithms, and acceleration techniques for bioinformatics, pattern recognition, and quantum computing. Her work spans multi-core CPUs, GPUs, FPGAs, and distributed clusters, emphasizing the boundary between hardware and software design. Dr. Becchi holds a Ph.D. and Master’s degree in Computer Engineering from Washington University in St. Louis (2009) and a Bachelor’s degree in Computer Engineering from Politecnico di Milano, Italy (2000). Her research has been recognized with prestigious awards, including the NSF CAREER Award (2015) and the University of Missouri System President Award for Early Career Excellence (2016). Her research interests include compiler and runtime techniques for heterogeneous systems, acceleration of bioinformatics algorithms, and high-speed networking applications. She has pioneered frameworks for efficient data transformation, GPU-accelerated compression, and memory-efficient graph algorithms for quantum computing. Her work also explores thread coarsening, mixed-precision auto-tuning, and secure multi-core processor design. Key contributions include the PILOT runtime system for GPU memory management, the GPU-FPtuner auto-tuner for floating-point applications, and innovative approaches to automata processors for genomic analysis. Her publications emphasize reproducible accuracy in scientific simulations and the optimization of irregular applications on many-core platforms.

Jung Hanمشاهده پروفایل

استاد

• Wide bandgap semiconductor materials
• Optoelectronic devices
• Nanoscale materials and devices
• +۴ مورد دیگر

Jung Han is the William A. Norton Professor of Electrical & Computer Engineering at Yale University, affiliated with the School of Engineering & Applied Science. He holds a Ph.D. from Purdue University and leads the Optoelectronics Materials and Devices Group, focusing on interdisciplinary research in III-nitride semiconductors, optoelectronics, and power electronics. His work bridges fundamental materials science with practical applications in solid-state lighting, energy harvesting, and next-generation electronics. Research interests include wide-bandgap semiconductor materials (e.g., GaN), nanoscale device fabrication, and epitaxial growth techniques. He pioneered nanoporous GaN distributed Bragg reflectors (DBRs) for high-efficiency LEDs and lasers, as well as selective-area growth methods for power electronics. His lab explores green energy technologies, flexible electronics, and hybrid organic-inorganic semiconductors. Publications emphasize advancements in GaN-based vertical-cavity surface-emitting lasers (VCSELs), SWIR detectors, and micro-LED displays. Recent work addresses challenges in defect control, scalability of III-nitride devices, and integration with emerging materials. His group collaborates across engineering, applied physics, and chemistry to advance sustainable energy and high-performance optoelectronics. Notable contributions include wafer-level integrated white-LEDs with quantum dots, damage-free in-situ GaN etching via TBCl, and stacking-fault-free GaN growth on foreign substrates. His research has been recognized in high-impact journals like Advanced Materials and Applied Physics Letters .

Artur Czumajمشاهده پروفایل

استاد

• Theoretical Computer Science
• Design and Analysis of Algorithms
• Randomized Algorithms
• +۹ مورد دیگر

Artur Czumaj is a Professor in the Department of Computer Science at the University of Warwick and serves as the Director of the Centre for Discrete Mathematics and its Applications (DIMAP). He is a member of the Division of Theory and Foundations (FoCS) and holds affiliations with the Alan Turing Institute, the Warwick Data Science Institute (WDSI), and the Warwick Centre for Doctoral Training in Mathematics of Real-world Systems (MathSys). Previously, he served as Head of Department and President of the European Association for Theoretical Computer Science (EATCS) from 2020 to 2024. His research lies at the core of theoretical computer science, focusing on the design and analysis of algorithms, particularly randomized, sublinear, parallel, and distributed algorithms. His work spans graph theory, combinatorics, computational geometry, algorithmic game theory, and property testing. He has led major research initiatives funded by EPSRC, IBM, the Royal Society, and Weizmann-UK grants. The trends in his recent publications highlight a strong emphasis on sublinear algorithms, dynamic graph algorithms, and property testing, with recurring themes in randomized methods, graph processing, and efficient data structures. His work bridges foundational theory with applications in data summarization, network analysis, and computational geometry. EPSRC grants: EP/D063191/1, EP/G064679/1, EP/G069034/1, EP/J021814/1, EP/N011163/1, EP/V01305X/1, EPSRC studentship IBM Faculty Award Royal Society International Exchanges Scheme Weizmann-UK Making Connections Grants on combinatorial and algorithmic primitives and the interplay between algorithms and randomness Peter Davies received the 2020 Warwick Faculty of Science Thesis Prize under his supervision Artur Czumaj has supervised numerous PhD students, including Anna Adamaszek, Michal Adamaszek, Sam Coy, Peter Davies, Michail Fasoulakis, Jan Hladky, Wang Xin, and Hairong Zhao. His research has been supported by sustained grant funding, reflecting his leadership in theoretical computer science. He has organized major workshops at Dagstuhl, Oberwolfach, Simons Institute, and the University of Warwick, and has served on the steering committees of HALG and as PC Chair for SODA 2018 and ICALP 2020. He is actively involved in organizing key research events, including the Simons Institute Special Semester on Sublinear Algorithms (2024), the Workshop on Sublinear Graph Simplification (2024), and the Computational Complexity Conference (CCC 2023) at Warwick. He also co-organizes the Warwick-Weizmann workshops and the IGAFIT Algorithmic Postdocs Workshop, fostering international collaboration in algorithms research.

Sabine Süsstrunkمشاهده پروفایل

استاد

• Computational Imaging
• Computational Photography
• Color Image Processing
• +۴ مورد دیگر

Sabine Süsstrunk is a Full Professor and Director of the Images and Visual Representation Laboratory (IVRL) at EPFL's School of Computer and Communication Sciences. She holds a BS in Scientific Photography from ETH Zürich, MS from Rochester Institute of Technology, and PhD from University of East Anglia. Her career includes positions at Hewlett-Packard Labs and Corbis Corporation. Her research explores computational imaging, computational photography, color processing, computer vision, and image quality. Key interests include near-infrared applications, multispectral imaging, and computational aesthetics. Her work bridges hardware and software solutions for imaging challenges. Publications demonstrate consistent focus on advancing generative models (diffusion models, neural cellular automata), 3D reconstruction (NeRF variants), and media integrity (DeepFake detection). Recent trends show increased emphasis on 3D vision, robustness in generative AI, and video analysis. Awards & Honors: IS&T/SPIE Electronic Imaging Scientist of the Year (2013) Raymond C. Bowman Teaching Award (2018) EPFL AGEPoly IC Polysphere Award (2020) 8 Best Paper/Demo Awards Fellowships: IEEE, IS&T, ELLIS, AIIA She leads the IVRL lab and advises PhD candidates while serving as President of the Swiss Science Council. Research is supported through competitive grants and industry collaborations.

Tobias Müllerمشاهده پروفایل

استاد

• Combinatorics
• Probability Theory
• Random Graphs
• +۵ مورد دیگر

Prof. Tobias Müller is a Professor at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen. His academic journey includes previous positions at Utrecht University, CWI (Centrum Wiskunde & Informatica), Tel Aviv University, and Eindhoven University of Technology, with a doctorate from the University of Oxford under Colin McDiarmid. His research focuses on combinatorics, probability theory, random graphs, percolation, discrete and stochastic geometry, and combinatorial game theory. He has contributed extensively to understanding complex networks, hyperbolic models, and geometric random structures. Research Interests: Random Graphs and Percolation Theory Discrete and Stochastic Geometry Hyperbolic Network Models Probabilistic Combinatorics Geometric Probability Graph Algorithms and Connectivity Notable Contributions: Analysis of Voronoi and Poisson-Voronoi percolation in hyperbolic planes. Studies on Mallows random permutations and their cycle structures. Research on component games and logical limit laws in graph theory. Investigations into the geometry and properties of random geometric graphs. Grants & Collaborations: Active in organizing workshops and conferences on random graphs and geometric networks, including the BIRS Workshop on Random Geometric Graphs and the STAR Workshops series. Labs/Teams: Member of the Bernoulli Institute’s research groups, focusing on stochastic studies, combinatorics, and algorithmic methods.