جست‌وجوی استاد و پژوهشگر

Amirhossein Kardoostمشاهده پروفایل

پژوهشگر

• Image Processing
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Amirhossein Kardoost is a current Ph.D. student and researcher in the Data and Web Science Group at the University of Mannheim, supervised by Prof. Dr.-Ing. Margret Keuper. His work focuses on Computer Vision , Machine Learning , and Image Processing , with specific interests in Image and Video Segmentation and Alignment of Electron Microscopy Images . Education Ph.D. in Computer Science (2017–present), University of Mannheim M.Sc. in Computer Science (2013–2017), Saarland University B.Eng. in Information Technology (2008–2012), Institute for Advanced Studies in Basic Sciences (IASBS) Research Contributions Developed novel solutions for Minimum Cost Lifted Multicut Problems in computer vision Advanced Self-supervised Motion Segmentation techniques Explored Video Segmentation and Tracking using generic cues Applied Graph Partitioning in multiple person tracking Publications Published in top-tier conferences: ACCV 2018, ICPR 2020, ACCV 2020 (2 papers) Collaborated with researchers like Kalun Ho, Peter Ochs, and Janis Keuper Focus areas: Segmentation Algorithms , Multicut Optimization , Motion Analysis

Robert Strzodkaمشاهده پروفایل

استاد

• Parallel algorithms on parallel hardware (GPUs, many-core CPUs, FPGAs)
• Numerical methods (AMG, Krylov, preconditioners, FMM, multilevel methods, SVD)
• Graph algorithms (partitioning, coloring, decomposition, BFS, MST)
• +۷ مورد دیگر

Robert Strzodka is a full professor at Heidelberg University, holding the chair on Application Specific Computing since 2015. He is renowned for pioneering work in GPU-based scientific computing, focusing on optimizing interactions between mathematics, algorithms, and parallel hardware architectures. Current affiliation: Institute of Computer Engineering (ZITI), Heidelberg University Prior roles: NVIDIA (AmgX group), Max Planck Institute (Integrative Scientific Computing), Stanford University (visiting assistant professor) PhD: Numerical mathematics from University of Duisburg-Essen (2004) His research spans parallel algorithms (GPUs, FPGAs), numerical methods (AMG, Krylov, preconditioners), and graph algorithms (partitioning, MST). Publications emphasize GPU acceleration , cache optimization , and mixed precision computing across domains like astrophysics, fluid dynamics, and finite element methods. The 15 most recent articles (2024-2008) demonstrate consistent innovation in parallel computing , GPU algorithms , and numerical methods . Key subfields include stochastic modeling , tridiagonal solvers , level set visualization , and cache-aware algorithms .

• Parallel Computing
• Distributed Systems
• Intelligent Storage Systems
• +۵ مورد دیگر

Cheng Li is an Associate Professor at the School of Computer Science, University of Science and Technology of China , and Director of the Information Computing Platform at the Institute of Artificial Intelligence, Hefei Comprehensive National Science Center. His research focuses on parallel and distributed intelligent computing systems, with an emphasis on optimizing computational efficiency through data-centric approaches. Education: PhD in Computer Science from Max Planck Institute for Software Systems (MPI-SWS) and Saarland University (2016) Bachelor's degree in Computer Science from Nankai University (2009) Research interests include distributed systems, machine learning optimization, database systems, and high-performance computing. Notable contributions include innovations in distributed training of deep neural networks, geo-replicated databases, and efficient graph processing. His work has been published in top-tier conferences like NSDI, AAAI, VLDB, and SOSP. Professional Activities : PC member at OSDI 2025, EuroSys 2024/2025, FAST 2024, and SOSP 2021. Teaching includes Systems Seminar and Compiler Principles at USTC since 2017. Grants : Secured $500k/year funding from Chinese government agencies and collaborations with Huawei/Alibaba. Active in cloud-native systems and AI infrastructure research.

Harald Räckeمشاهده پروفایل

استاد

• Algorithms
• Theoretical Computer Science
• Approximation Algorithms
• +۵ مورد دیگر

Prof. Dr. Harald Räcke is a Professor at the Technische Universität München (TUM) , affiliated with the TUM School of Computation, Information and Technology in the Effiziente Algorithmen department. His research focuses on the design and analysis of algorithms, particularly approximation algorithms, online algorithms, graph partitioning, scheduling, routing in parallel systems, and metric embeddings. He holds a PhD from the University of Paderborn and has held academic positions at institutions including Carnegie Mellon University (USA), Toyota Technological Institute (USA), and the University of Warwick (UK) before joining TUM in 2011. His work has been recognized with prestigious awards, including the Best Paper Awards at STOC 2008 and FOCS 2002. Key research trends in his publications emphasize theoretical computer science and algorithm design, with a focus on optimizing network-related problems such as congestion minimization, balanced partitioning, and oblivious routing. His recent work explores dynamic graph algorithms and sparsification techniques, reflecting advancements in handling large-scale network challenges. Education: PhD in Algorithms and Complexity (2003), University of Paderborn Studies in Computer Science at University of Paderborn Professional Milestones: Postdoc: Carnegie Mellon University (Pittsburgh, USA) and Toyota Technological Institute (Chicago, USA) Assistant Professor at University of Warwick (UK) Joined TUM in 2011 His scientific awards highlight contributions to theoretical computer science: Best Paper Award, 40th ACM Symposium on Theory of Computing (2008) Best Paper Award, 43rd IEEE Symposium on Foundations of Computer Science (2002)

• Computational Geometry
• Algorithms
• Trajectory Analysis
• +۴ مورد دیگر

Prof. Maike Buchin is a Professor of Computer Science at Ruhr-University Bochum, leading the Theoretical Computer Science/Algorithmics department. She serves as Studiendekanin (Dean of Studies) for Computer Science. Her academic journey includes roles as Visiting Professor at TU Dortmund (2017-2019), Junior Professor at Ruhr-University Bochum (2013-2017), and Assistant Professor at TU Eindhoven (2011-2013). She holds a Doctorate in Computer Science from Freie Universität Berlin (2007) and a Mathematics Diploma from the University of Münster (2003). Her research focuses on computational geometry, algorithms, and trajectory analysis. Key interests include Fréchet distance computations, geometric clustering, and applications in geographic information systems. She has contributed to trajectory grouping structures, map construction from subtrajectories, and efficient algorithms for curve analysis. Publications highlight work on Fréchet distance variants, clustering algorithms, and geometric optimization. Recent trends emphasize practical applications of theoretical algorithms in movement data analysis and network extensions. Her research often bridges algorithmic theory with real-world spatial data challenges. No scientific awards or grants are explicitly listed in the provided materials. She advises graduate students through her academic roles and collaborates internationally in computational geometry and related fields.

Michael Palkمشاهده پروفایل

پژوهشگر

• Graph Theory
• Data Science
• Public Transport
• +۴ مورد دیگر

Michael Palk is an external PhD student (since 2024) and former research associate (2019-2023) at the Institute of Information Systems, University of Hamburg under Prof. Stefan Voß. He holds an MSc (2019, Distinction) and BSc (2017) in Business Mathematics from the University of Hamburg. His research focuses on applying graph theory, data science, and optimization techniques to public transport and energy systems, alongside social media analytics. Key contributions include advancements in graph neural networks for combinatorial optimization and bilingual sentiment analysis frameworks. He has published 3 peer-reviewed articles in IEEE Access, Information Systems Frontiers, and international workshops. Education 2017-2019: MSc Business Mathematics (Distinction), University of Hamburg 2012-2017: BSc Business Mathematics, University of Hamburg Research Graph neural networks for NP-hard problems Social media analytics for product events Optimization models for power distribution networks Affiliations Institute of Information Systems Faculty of Business Administration

• Database Systems
• Graph Databases
• Route Planning
• +۴ مورد دیگر

Dr. Theodoros Chondrogiannis is a Post-doctoral Researcher at the University of Konstanz's Database and Information Systems group. He holds a PhD from the Free University of Bozen-Bolzano (2017) and previously worked as a postdoc there until joining Konstanz. His research focuses on route planning, graph database query processing, and spatial network analysis. He leads a DFG-funded project on multi-criteria path queries and teaches 'Graph Data Management and Analysis' annually. Education: BSc (Computer Science, University of Peloponnese, 2009), MSc (Advanced Information Systems, National Kapodistrian University of Athens, 2013), PhD (Free University of Bozen-Bolzano, 2017). Research interests include algorithm design for transportation networks, graph database systems, and geosocial network analysis. His work bridges theoretical foundations with practical applications in urban mobility and query optimization. He will assume an Associate Professor role at NTNU's Department of Computer Science (IDI) starting January 2025. Notable service roles include publicity chair for SSTD 2023 and co-chair for ACM SIGSPATIAL Student Research Competitions (2019-2020).

Dominik Mehlemمشاهده پروفایل

پژوهشگر

• Point Cloud Compression
• Data Compression
• 3D Graphics
• +۴ مورد دیگر

Dominik Mehlem is a Researcher at the Institute of Communications Engineering (RWTH Aachen University), specializing in point cloud compression and video coding . He contributes to the ISO/IEC MPEG standardization process for 3D data compression. Research Focus : Development of compression algorithms for point cloud data, analysis of Versatile Video Coding (VVC) vs. HEVC in video-based point cloud compression (V-PCC), and inter-frame prediction techniques like 3D motion compensation in geometry-based point cloud compression (G-PCC). Email : mehlem@ient.rwth-aachen.de Office Hours : Mon-Thu, 10:00–12:00 and 14:00–16:00 (by appointment) Key Publications : Recent works in Visual Communications and Image Processing (VCIP) and International Picture Coding Symposium (PCS) , focusing on entropy coding, graph-based methods, and VVC optimization for point cloud compression.

• Computational Complexity
• Cryptography
• Zero-Knowledge Proofs
• +۵ مورد دیگر

Boaz Barak is a Professor at the Weizmann Institute of Science in the Department of Computer Science, Faculty of Mathematics and Computer Science. With an h-index of 64 and over 17,301 citations, he is a leading researcher in theoretical computer science with significant contributions spanning computational complexity, cryptography, and machine learning theory. His research interests include: Computational Complexity Cryptography Zero-Knowledge Proofs Program Obfuscation Interactive Proofs Privacy-Preserving Computation Machine Learning Theory Barak's publication record reveals a trajectory from foundational work in theoretical computer science to contemporary research at the intersection of theory and practice. His early work established impossibility results for program obfuscation and advanced techniques for zero-knowledge proofs beyond black-box simulation. His influential textbook "Computational Complexity: A Modern Approach" has become a standard reference in the field. More recently, his research has expanded into machine learning phenomena like double descent and scaling laws for language models, demonstrating the evolving nature of his theoretical contributions. His work consistently bridges deep theoretical insights with practical implications for computing. His notable collaborations include extensive work with Sanjeev Arora (77 publications, 6,879 citations), David Steurer (95 publications, 4,945 citations), and Oded Goldreich, among others. Professor Barak leads a research group at the Weizmann Institute focused on theoretical aspects of computer security and complexity theory. His work has been consistently supported by major research funding, enabling significant contributions to the theoretical foundations of computer science. He maintains an active research program with publications spanning over two decades, demonstrating sustained impact in multiple subfields of theoretical computer science.

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

Soheil Behnezhadمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Algorithms for Big Data
• Sublinear Time Algorithms
• +۷ مورد دیگر

Soheil Behnezhad is an Assistant Professor in the Department of Computer Science at Khoury College of Computer Sciences, Northeastern University. He previously served as a Motwani Postdoctoral Fellow at Stanford University and received his PhD from the University of Maryland (UMD) and BSc from Sharif University. Research Interests: His work centers on theoretical computer science, particularly the design and analysis of algorithms for large-scale data. Key areas include sublinear-time algorithms, dynamic algorithms, streaming algorithms, parallel computation (MPC), and graph sparsification, with a strong emphasis on matching, coloring, and clustering problems. Recent Trends in Publications: His recent publications (2023–2025) highlight groundbreaking work in dynamic and sublinear algorithms. He has made significant advances in maximum matching, edge coloring, and correlation clustering, often providing tight bounds or breaking longstanding approximation barriers. His work connects theoretical models with combinatorial structures such as Ruzsa-Szemerédi graphs and explores practical implications in massive data settings. Scientific Awards: NSF CAREER Award Google Research Award Best Paper Award at STOC'25 Best Paper Award at SODA'23 Charles A. Caramello Distinguished Dissertation Award Larry S. Davis Doctoral Dissertation Award Multiple invitations to TALG and HALG Advising and Grants: He advises multiple PhD students including Amir Azarmehr, Mohammad Saneian, and Alma Ghafari. His research is supported by an NSF CAREER Award and a Google Research Award, reflecting both federal and industry recognition of his impactful work. Labs and Teams: He co-organizes the Graph Simplification reading group with Ronitt Rubinfeld and Madhu Sudan and is a key member of the Theory Group at Northeastern University, fostering a collaborative environment for theoretical research.

• Probability Theory
• Random Planar Maps
• Scaling Limits
• +۷ مورد دیگر

Nicolas Curien is a Professor in the Probability and Statistics Team at Université Paris-Saclay, where he leads the M2 "Mathematics of Randomness" program and heads the ERC-funded project "SuPerGRandMa". His office is located in Building 307, Orsay. Curien has been a faculty member since 2014, following positions as a CNRS researcher at LPMA (Paris) and teaching assistant at ENS Paris. He completed his PhD under Jean-François Le Gall in 2011. Curien's research spans probability theory , random geometry , and statistical physics , with focus areas including: Scaling limits of random planar maps and hyperbolic geometries Percolation theory on random lattices Growth-fragmentation processes and branching structures Metric properties of stochastic trees and surfaces His work frequently combines combinatorial probability with continuous stochastic processes to analyze phase transitions and universal behavior. Analysis of Curien's recent publications reveals consistent themes: rigorous treatment of scaling limits in random geometries (especially maps and trees), critical phenomena in percolation models, and probabilistic aspects of hyperbolic surfaces. Approximately 80% of his 2021-2024 papers involve phase transitions or universality classes , with methods drawing from Lévy processes, peeling explorations, and multi-scale analysis. Significant awards recognizing his contributions include: ERC Consolidator Grant (SuPerGRandMa, 2023) Prix Marc Yor (2022) Prix Jacques Herbrand (2019) Rollo Davidson Prize (2015) He was elected Junior Member of the Institut Universitaire de France in 2016. Curien maintains an extensive research group, having supervised over 20 PhD students and postdoctoral researchers since 2013. Notable former students include Thomas Budzinski (CNRS researcher), Alice Contat (CNRS researcher), and Cyril Marzouk (Assistant Professor at École Polytechnique). His ERC project currently supports 4 early-career researchers. He collaborates internationally with labs including LPMA (Paris), University of Vienna, and EPFL. Curien also participates in the gastronomic societies "Tasteurs de Fourmes du Cantal" and "Gousteurs de Kirsch de Fougerolles".

Frank Kammerمشاهده پروفایل

پژوهشگر

• Computer Science
• Algorithms and Data Structures
• Graph Theory
• +۴ مورد دیگر

Frank Kammer is a researcher at the Technical University of Central Hesse , actively engaged in teaching and research projects. He co-leads the RegioTainment platform with Biebertal municipality and contributes to the SEA Project , an open C++ library for space-efficient algorithms. Teaching : Database Systems (CS1020), Software Engineering (CS1023), Efficient Algorithms (CS2353), Artificial Intelligence (CS2364/WK1613), etc. Research : Focuses on space-efficient graph algorithms, temporal graph exploration, and algorithm engineering. His work addresses computational challenges in huge datasets and memory-constrained devices , with applications in planar graph encoding, vertex separators, and student feedback systems. Advising : Supervised theses on topics including data-driven analytics platforms, low-code integration, cloud orchestration, and AI-optimized marketing campaigns. Collaboration : Works with students like Max Stephan, Timon Pellekoorne, and Johannes Meintrup on algorithm implementation and educational tools. Projects like RegioTainment emphasize digital community networking to preserve rural culture while embracing modernity.

Bjoern Andresمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Graph Algorithms
• +۳ مورد دیگر

Prof. Dr. Bjoern Andres holds the position of Professor of Machine Learning for Computer Vision at Technische Universität Dresden . He is a Principal Investigator at the Center for Scalable Data Analytics and Artificial Intelligence and an Academic Fellow at the School of Embedded Composite Artificial Intelligence. His work bridges theoretical computer science, applied mathematics, and biomedical imaging through innovative graph algorithms. Education : PhD in Physics (Heidelberg University), Diploma in Physics (Heidelberg), Pre-Diploma in Physics and Computer Science (Technical University Dortmund) Research Interests : His research focuses on graph-based methods for computer vision and biomedical image analysis, including: Lifted multicut and correlation clustering algorithms Integer programming for anatomical network reconstruction 3D segmentation of neural tissue Optimal tracking of cellular lineages Partial ordering and quantum-inspired optimization Scientific Contributions : His recent publications emphasize: Advancing multicut polytope analysis (2023-2025) Quantum alternating operator ansatz for correlation clustering (2025) 4-approximation algorithms for Min Max correlation clustering Medical imaging applications for organoid segmentation Biomedical applications in vascular network reconstruction Development of scalable graph decomposition methods Awards & Recognitions : IEEE CVPR Outstanding Reviewer (2022) NIPS Best Reviewer (2017) MICCAI Best Paper (2015) DAGM Best Paper Runner-Up (2008) Heidelberg International Exchange Scholarship (2005) Studienstiftung Scholarship (2000-2007) Software Development : Maintains andres::graph , a C++ library for graph algorithms and multi-dimensional arrays, featuring: Efficient graph data structures with constant-time access Implementations of Prim's algorithm and max-flow methods Applications in medical imaging and computer vision

Anusch Tarazمشاهده پروفایل

استاد

• Discrete Mathematics
• Graph Theory
• Combinatorics
• +۵ مورد دیگر

Anusch Taraz is a Professor at the Institute of Mathematics , Hamburg University of Technology. His research focuses on Discrete Mathematics , particularly in Graph Theory , Hypergraphs , and Combinatorics . He holds the Chair of Discrete Mathematics and has contributed extensively to topics like Ramsey Theory , Random Graphs , and Algorithmic Complexity . Education : International Baccalaureate (United World College of the Atlantic, UK), MSc in Mathematics (University of Bonn), PhD in Theoretical Computer Science (Humboldt-University of Berlin, supervisor: Hans Jürgen Prömel) His research explores Size-Ramsey Numbers , Graph Embeddings , and Resilience in random graphs. Recent publications emphasize Random Graphs , Hypergraph Theory , and Extremal Graph Problems . No specific scientific awards are highlighted in the provided texts. Email: taraz@tuhh.de .