جست‌وجوی استاد و پژوهشگر

Benjamin Doerrمشاهده پروفایل

استاد

• Algorithms
• Randomized Algorithms
• Artificial Intelligence
• +۷ مورد دیگر

Benjamin Doerr is a full Professor of Computer Science at École Polytechnique in France, affiliated with the Laboratoire d'Informatique (LIX). He conducts research in algorithms and artificial intelligence, with a specific focus on randomized algorithms and heuristic search. His work spans theoretical computer science, evolutionary computation, and mathematical analysis of optimization algorithms. Professor Doerr's research interests center on randomized search heuristics, including evolutionary algorithms, ant colony optimizers, and estimation-of-distribution algorithms. His work extends to foundational areas such as group theory (from his diploma work), discrepancy theory and combinatorial games (from his PhD), and algorithmic mathematics (from his habilitation). He has made significant contributions to understanding the runtime behavior of evolutionary algorithms and establishing theoretical guarantees for their performance across various optimization problems. His recent publications reveal a strong focus on multi-objective evolutionary algorithms, particularly analyzing and improving the performance of popular frameworks like NSGA-II, NSGA-III, and SMS-EMOA. His research demonstrates a consistent pattern of providing rigorous theoretical foundations for heuristic search methods, moving beyond empirical observations to establish provable performance guarantees. This theoretical approach has become increasingly influential in bridging the gap between theoretical computer science and practical optimization techniques. Professor Doerr has received several prestigious awards including two Otto-Hahn medals, the Dr. Eduard Martin prize, and the Digiteo-Digicosme prize. His students have also earned significant recognition, with multiple dissertation awards and nominations. He has supervised numerous PhD students to completion, including Tobias Friedrich (now director of HPI and professor at University of Potsdam), Carola Winzen (now permanent researcher at CNRS), and Marvin Künnemann (now professor in Kaiserslautern). He regularly supervises M1/M2 research projects, with many leading to international conference publications at venues like AAAI, IJCAI, and GECCO. Professor Doerr serves on the editorial boards of several leading journals including Artificial Intelligence, Evolutionary Computation, and IEEE Transactions on Evolutionary Computation. At École Polytechnique, Professor Doerr is a member of the executive board of the doctoral school of IP Paris, where he oversees computer science doctoral students across multiple institutions. He previously served as the habilitation reference person for the IDIA department and has been instrumental in shaping the academic processes for doctoral candidates and HDR (Habilitation à Diriger des Recherches) candidates.

Tianyi Chenمشاهده پروفایل

دانشیار

• Bilevel optimization
• Multi-objective optimization
• Machine learning
• +۷ مورد دیگر

Tianyi Chen is an Associate Professor in the Department of Electrical and Computer Engineering at Cornell Tech, Cornell University, starting from Summer 2025. Previously, he was an Associate Professor (tenured) in the Department of Electrical, Computer, and Systems Engineering at Rensselaer Polytechnic Institute (RPI), where he began as an Assistant Professor in 2019. His research bridges theoretical foundations in optimization, signal processing, and machine learning with practical applications in AI, wireless systems, and emerging computing paradigms. Education: Ph.D. in Electrical and Computer Engineering, University of Minnesota (Advisor: Prof. Georgios B. Giannakis) B.Sc. in Communication Science and Engineering, Fudan University (Highest Honors, 2014) Research Interests: Tianyi Chen’s work spans bilevel optimization , multi-objective learning , and federated learning , with recent focus on AI safety , large language models , and analog in-memory computing . His group develops principled algorithms that enable efficient, secure, and scalable learning systems, integrating theory with real-world deployment in next-generation wireless networks and AI platforms. Scientific Awards: IEEE Signal Processing Society Best PhD Dissertation Award (2020) NSF CAREER Award (2021) Amazon Research Award – AWS AI (2022) IEEE Signal Processing Society Young Author Best Paper Award (2024) Best Student Paper Awards at NeurIPS 2020 Workshop and ICASSP 2021 Advising & Grants: Dr. Chen has mentored numerous PhD and Master’s students, many of whom have secured faculty or industry research positions. His research is supported by NSF, Amazon, Cisco, IBM, and NVIDIA. He is currently recruiting postdocs and students with backgrounds in optimization, advanced computing, and wireless networks for Fall 2025/2026 at Cornell Tech. Labs & Teams: His research group operates at the intersection of optimization theory, machine learning, and system design, with active collaborations across Cornell Tech, RPI, MIT-IBM Watson Lab, and industry partners like Amazon, Cisco, and IBM AI Horizons Network.

Gary B Lamontمشاهده پروفایل

استاد

• Evolutionary Algorithms
• Multi-Objective Optimization
• Computational Intelligence
• +۷ مورد دیگر

Dr. Gary B. Lamont is a Professor in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT), part of Air University. His work bridges computational intelligence, evolutionary algorithms, and defense systems engineering, with extensive applications in aerospace, cybersecurity, and autonomous systems. Ph.D., University of Minnesota Institute of Technology, 1970 Master of Science in Electrical Engineering, University of Minnesota Institute of Technology, 1967 Bachelor of Physics, University of Minnesota Institute of Technology, 1961 Dr. Lamont’s research centers on multi-objective evolutionary algorithms (MOEAs) , with applications in UAV swarm mission planning, network intrusion detection, image processing, and protein structure prediction. He has pioneered the use of evolutionary computation in military and defense contexts, including radar waveform design, satellite constellation planning, and autonomous agent behavior generation. His work often integrates swarm intelligence, artificial immune systems, and distributed optimization techniques. The recent publications highlight a strong trend toward military and defense applications of computational intelligence, particularly in electronic warfare, space surveillance, and cyber defense. His work frequently employs multi-objective optimization to balance competing constraints in real-world systems such as radar, UAV swarms, and network security architectures. Image processing and signal transformation using evolved algorithms also remain active areas, especially for defense imaging and compression. IEEE Fritz Russ Bio-Engineering Award, 2008 IEEE Senior Life Member, 2004 Eta Kappa Nu AFIT Teacher of the Year, 2002 WPAFB Professional Employee of the Year, 1981 Best Presentation Award, Institute of Navigation, 2008 BEST PAPER AWARD, Gameon North America '09 Best Paper Award Nominee, IEEE SSCI 2007 Dr. Lamont has advised numerous graduate students, including Jeremy Stringer, Mark Kleeman, and Dustin Nowak, many of whom have co-authored significant publications with him. His research has been supported by the U.S. Air Force and other defense agencies, enabling high-impact work in autonomous systems, network security, and optimization under uncertainty. He has led projects involving multi-agent systems, self-organized swarms, and parallel evolutionary algorithms, often in collaboration with institutions like Wright-Patterson Air Force Base. His research group at AFIT operates at the intersection of computational intelligence and defense engineering, focusing on self-organized UAV swarms , evolutionary intrusion detection systems , and adaptive signal processing . The team utilizes high-performance computing environments and simulation platforms like Swarmfare to test swarm behavior and mission planning algorithms. The lab emphasizes software engineering discipline in AI systems, as seen in tools like jREMISA, and integrates biological metaphors such as immune systems and genetic algorithms into robust cyber defense frameworks.

Krzysztof Walkowiakمشاهده پروفایل

استاد

• Computer Network Optimization
• Machine Learning in Networks
• Artificial Intelligence
• +۱۳ مورد دیگر

Krzysztof Walkowiak is a Professor at the Faculty of Computer Science and Telecommunications, Wrocław University of Science and Technology (PWr), where he also serves as the Dean of the Doctoral School. He leads the Computer Networks Team (ZSK) and is actively involved in multiple research projects, including Dark-Box Optimization and evolutionary methods for multi-criteria network design. A Senior Member of IEEE and IEEE ComSoc, he contributes to academic governance as a member of the Polish Academy of Sciences’ Committee on Electronics and Telecommunications. PhD in Computer Science (2000, with distinction) Habilitation in Computer Science (2008) Professor of Technical Sciences (2017) Dean of the Doctoral School, PWr (since 2020) Senior Member, IEEE and IEEE Communications Society Member, Committee on Electronics and Telecommunications, Polish Academy of Sciences His research spans computer network optimization, machine learning in networks, evolutionary algorithms, survivable optical networks, and intelligent computational techniques . He has pioneered the integration of AI methods in teleinformatics and leads initiatives in intent-based and cognitive networking. His work emphasizes multi-layer, application-aware network design and distributed processing systems. The 15 most recent publications reflect a strong trend in optimization under uncertainty, AI-driven networking, and metaheuristic algorithm development . There is a clear focus on survivability, scalability, and automation in modern network architectures, with increasing attention to edge intelligence via TinyML and cognitive systems. His recent work also addresses internationalization and pedagogical innovation in doctoral education. Fabio Neri Best Paper Award 2014 (Elsevier Journal of Optical Switching and Networking) Best Paper Award, DRCN2009 (Washington, USA) Best Paper Award, RNDM2015 (Munich, Germany) Medal of the National Education Commission (2011) Scientific Scholarship, Wrocław University of Science and Technology (2017) Star of Internationalization 2024 – Teaching Star Professor Walkowiak has supervised 10 completed PhD theses and currently mentors 5 doctoral students. He has led or managed 13 research projects funded by NCN (including 4 OPUS grants), EU, NAWA, and national agencies. His grant leadership includes the NAWA InterDocSchool project (2021–2023) and the Unite! Doctoral School curriculum development. He has reviewed over 300 journal submissions and served as session chair at 22 international conferences. He leads several research teams: Computer Networks Team (ZSK), Machine Learning Team, Advanced Data Analysis Methods Team, Metaheuristics Team, and Teaching Team . He has developed innovative educational programs such as the Research Skills course and Recent Research Trends , promoting international collaboration and doctoral training. He championed the transition to English-language instruction in the Doctoral School and promotes internationalization as a 'team sport' across institutional levels.

• Artificial Intelligence
• Machine Learning
• Human-Computer Interaction
• +۱۶ مورد دیگر

Professor Damien Coyle is the Director of the Bath Institute for the Augmented Human at the University of Bath, where he leads cutting-edge research in artificial intelligence, machine learning, and human-computer interaction. His work is centered on brain-computer interfaces (BCI), neurotechnology, and cognitive computing, with applications in healthcare, rehabilitation, and intelligent systems. His research interests include Brain-Computer Interfaces , Spiking Neural Networks , Deep Learning , Emotion Recognition , Virtual and Extended Reality , and Neurofeedback Systems . He applies advanced AI techniques to decode neural signals, enabling real-time interaction between the brain and external devices. His interdisciplinary approach integrates neuroscience, computer science, and engineering. His recent publications from 2023–2024 reveal a strong focus on anomaly detection in industrial systems , EEG-fMRI data fusion for inner speech decoding , multi-level IT incident prediction using AI , and enhancing neurofeedback with immersive VR . These works demonstrate a trend toward multimodal data integration, real-time BCI applications, and AI-driven decision support in both clinical and technological domains. He has supervised numerous students and collaborators, many of whom are co-authors on his publications. His research is frequently published in top-tier IEEE and Springer conferences. He actively contributes to the advancement of neuroadaptive technologies and is involved in high-performance computing for BCI calibration. His leadership in organizing major conferences further underscores his influence in the field.

• Computational Intelligence
• Evolutionary Multi-objective Optimization
• Evolutionary Machine Learning
• +۵ مورد دیگر

Professor Hisao Ishibuchi is Chair Professor of Computer Science and Engineering at Southern University of Science and Technology (SUSTech) in Shenzhen, China, a role he has held since April 2017. Previously, he spent nearly three decades at Osaka Prefecture University, progressing from Research Associate (1987-1993) to Assistant Professor (1993), Associate Professor (1994-1999), and full Professor (1999-2017). He is an IEEE Fellow , served as Vice-President of the IEEE Computational Intelligence Society (2010-2013) , and is currently President of the Japan Society for Evolutionary Computation (2016-2018) . He is Editor-in-Chief of IEEE Computational Intelligence Magazine (2014-2019) and the Journal of the Japan EC Society (2014-2018). Education: Ph.D. in Engineering, Osaka Prefecture University, 1992 M.S. in Engineering, Kyoto University, 1987 B.S. in Engineering, Kyoto University, 1985 Research Focus: Professor Ishibuchi is internationally recognised as a pioneer of computational intelligence , with seminal contributions to evolutionary multi-objective optimisation , evolutionary machine learning , fuzzy systems , neural networks , and hybrid intelligent systems . He introduced the first multi-objective memetic algorithm and early methods for multi-objective fuzzy rule-based classifier design that balance accuracy and interpretability. Publications & Impact: With over 100 journal papers in top-tier venues such as IEEE Transactions on Evolutionary Computation and nearly 500 conference papers, his work has attracted more than 24 000 Google-Scholar citations and an h-index of 68. His recent articles concentrate on many-objective optimisation, fuzzy machine learning, and transfer learning techniques. Honours & Awards: IEEE Computational Intelligence Society Fuzzy Systems Pioneer Award 2019 IEEE Fellow 2014 JSPS Prize 2007 (Japan’s most prestigious mid-career award) Multiple Best Paper Awards from GECCO, FUZZ-IEEE, SCIS & ISIS, WAC, ACIIDS, HIS-NCEI, and others Teaching & Mentoring: At SUSTech he teaches Advanced Algorithms and Advanced Optimization Algorithms , covering greedy algorithms, hyper-heuristics, memetic algorithms, multi-objective optimisation, and performance assessment. His research group actively recruits post-doctoral fellows and research assistants in evolutionary computation, fuzzy systems, and neural networks. Labs & Teams: He leads the Computational Intelligence Research Group at SUSTech, maintaining active collaboration networks across Asia, Europe, and North America, and supervising several post-doctoral researchers and graduate students working on next-generation intelligent systems.

Soo Mi Choiمشاهده پروفایل

استاد

• Computer Graphics
• Virtual Reality
• Augmented Reality
• +۷ مورد دیگر

Dr. Soo Mi Choi is a distinguished Professor in the Department of Computer Science and Engineering at Sejong University's College of Engineering. She serves as Director of the Mobile Virtual Reality Research Center (ITRC), a Korean government-designated research facility, and leads the eXtended Reality Research Center. Her academic journey began at Ewha Womans University where she earned her B.S. (1993), M.S. (1995), and Ph.D. (2001). She has held prestigious positions including Visiting Researcher at Fraunhofer Institute for Computer Graphics Research in Germany (1998) and Visiting Professor at ETH Zurich in Switzerland (2008-2009). Ph.D., Ewha Womans University (2001) M.S., Ewha Womans University (1995) B.S., Ewha Womans University (1993) Professor Choi's research spans computer graphics, virtual reality, augmented reality, mixed reality, and their applications in healthcare, urban planning, and education. She has pioneered work in mobile VR content representation, sketch-based interfaces for facial features, virtual freeform architecture with stereo 3D rendering, and medical image analysis. Her recent focus integrates AI with XR technologies, particularly for education in the metaverse, environmental monitoring, and medical applications. Her work demonstrates exceptional interdisciplinary reach, connecting computer science with earth sciences, neuroscience, and education. Analysis of her recent publications reveals a strong trend toward applying extended reality technologies to environmental monitoring and disaster management, with numerous papers on flood susceptibility mapping, land subsidence, and pollution modeling using advanced AI techniques. She has also produced influential work on metaverse education frameworks and VR-assisted learning systems, reflecting her commitment to applying cutting-edge technology to educational challenges. Her research shows increasing integration of generative AI with virtual reality systems. Cum Laude Poster Award (SPIE2001) Korean HCI Society 2011 Excellent Paper Award KCC 2015 Best Paper Award KCC 2013 Best Paper Award KCC 2014 Excellent Presentation Paper Award Professor Choi actively mentors students, with numerous publications showing her as corresponding author guiding first-author students through significant research contributions. She leads international collaborations with institutions including ETH Zurich, Disney Research Studios, Samsung Seoul Hospital, and Seoul National University Hospital. Her Mobile Virtual Reality Research Center (ITRC) serves as a hub for government-funded research projects applying VR technologies to real-world problems. She has supervised numerous undergraduate and graduate students, many of whom have received awards for their collaborative work. As Director of the Mobile Virtual Reality Research Center and the eXtended Reality Research Center at Sejong University, Professor Choi leads a dynamic research team working on cutting-edge XR applications. Her labs collaborate internationally with Swiss institutions through Korea-Switzerland research projects and maintain strong ties with medical institutions for healthcare applications of VR technology. The centers focus on developing intelligent content creation tools for augmented and virtual reality, with applications spanning education, disaster management, and medical visualization.

Frits C.R. Spieksmaمشاهده پروفایل

استاد

• Combinatorial Optimization
• Operations Research
• Scheduling
• +۷ مورد دیگر

Prof. Frits C.R. Spieksma is a full professor in the Department of Mathematics and Computer Science at Eindhoven University of Technology (TU/e) , where he leads research within the Combinatorial Optimization Group. He has held academic positions at Maastricht University, KU Leuven, and the University of British Columbia, and has been at TU/e since 2018. Education: M.Sc. in Econometrics, University of Groningen (1987) Ph.D. in Operations Research, Maastricht University (1992) Research Focus: His work lies at the intersection of combinatorial optimization and real-world applications . Key themes include: Scheduling and clustering problems, especially in sports tournaments Organ allocation optimization for Eurotransplant Assignment and transportation problems Approximation algorithms and graph-theoretic optimization Scientific Service & Leadership: Founder and ex-Chair, EURO Working Group OR in Sports Member, Steering Committees of MAPSP and MathSports International President, EURO (Association of European Operational Research Societies) Former Vice-President, IFORS Former President, Belgian Society of Operations Research (ORBEL) Editorial Boards: Associate Editor, 4OR (2015–present) Associate Editor, Journal of Quantitative Analysis in Sports (2014–present) Associate Editor, Operations Research Letters (2008–2024) Former Associate Editor, INFORMS Transactions on Education , OMEGA , Computers & Operations Research , IIE Transactions , Naval Research Logistics PhD Supervision & Mentoring: He has supervised more than 25 PhD theses at KU Leuven and TU/e, many of whom now hold academic positions worldwide. Conference & Workshop Organisation: Recent leadership roles include General Chair of IPCO 2022 (Eindhoven), organiser of Benders Day 2024 , and co-organiser of the Dagstuhl Seminar on Fairness in Scheduling and Resource Allocation (March 2025).

Carlos A. Coello Coelloمشاهده پروفایل

استاد مهمان

• Evolutionary Computation
• Multi-objective Optimization
• Genetic Algorithms
• +۵ مورد دیگر

Dr. Carlos A. Coello Coello is a distinguished professor (CINVESTAV 3F Researcher) at the Center for Research and Advanced Studies of the National Polytechnic Institute (CINVESTAV-IPN) in Mexico City. He also serves as a Distinguished Visiting Professor in Computer Science and Computational Intelligence at Tecnológico de Monterrey's School of Engineering and Science, and as a visiting professor at the Basque Center for Applied Mathematics (BCAM) in Spain. Elected to El Colegio Nacional in 2023, he is the first computer scientist to join this prestigious Mexican institution, which groups the country's most important scientists, artists, and intellectuals. Dr. Coello's research focuses on evolutionary computation, particularly multi-objective optimization algorithms. His work spans genetic algorithms, evolutionary strategies, and bio-inspired optimization techniques with applications in engineering. He has made pioneering contributions to evolutionary multi-objective optimization, including developing the first genetic microalgorithm for multi-objective optimization, which has been applied in real-world contexts such as aerospace design. His research bridges computer science, applied mathematics, and operations research. Dr. Coello has published extensively since the 1990s, with recent publications focusing on advanced evolutionary algorithms, surrogate modeling for expensive optimization, and dynamic multi-objective optimization. His work shows a clear progression from foundational evolutionary computation techniques to sophisticated multi-objective and many-objective optimization approaches with practical engineering applications. MCDM Edgeworth-Pareto Prize (2024) Crónica Prize in Science and Technology (2023) SIGEVO Outstanding Contribution Award (2023) IEEE Computational Intelligence Society Evolutionary Computation Pioneer Award (2021) 2013 IEEE Kiyo Tomiyasu Award 2012 National Medal of Science and Arts IEEE Fellow (since 2011) Dr. Coello has successfully secured significant research funding through Mexico's CONACyT, with projects ranging from foundational algorithm development to advanced multi-objective optimization techniques. He has supervised PhD students, including Dr. Luis Vicente Santana-Quintero who received the Arturo Rosenblueth PhD Thesis Award. As Associate Editor for prestigious journals including IEEE Transactions on Evolutionary Computation, Dr. Coello plays an active role in shaping the field. His work has earned him international recognition, including being ranked 289th worldwide and 1st in Mexico among the 1000 most outstanding computer scientists in the 2022 Guide2Research Ranking.

• Multiobjective Optimization
• Evolutionary Algorithms
• Combinatorial Optimization
• +۳ مورد دیگر

Professor Andrzej Jaszkiewicz is a faculty member at the Faculty of Computer Science and Telecommunications, Poznań University of Technology, where he works in the Institute of Informatics. He holds the position of full professor with extensive experience in multiobjective optimization and evolutionary algorithms, as evidenced by his habilitation completed in 2001 and continuous research output through 2025. Professor Jaszkiewicz's research focuses on theoretical and practical aspects of multiobjective optimization, particularly addressing the challenges of many-objective problems. His work spans quality indicator development (hypervolume, R2), efficient data structures (ND-Trees), evolutionary algorithm design, and applications to combinatorial optimization problems. His publications demonstrate consistent theoretical rigor combined with practical implementation considerations. Recent publications (2022-2025) reveal continued productivity with multiple articles in top journals like IEEE Transactions on Evolutionary Computation and Physics of Fluids. These works explore theoretical properties of quality indicators, efficient calculation methods, and novel applications of optimization techniques to complex problems including fluid dynamics. Professor Jaszkiewicz has supervised doctoral research including Tarek Alkhaeir's 2021 dissertation on software quality metrics and Marek Kubiak's 2009 work on memetic algorithms. He has also reviewed numerous doctoral dissertations in related fields, demonstrating his standing in the academic community and commitment to graduate education. His scholarly output includes journal articles, conference papers, book chapters, and two books. The 2005 edited volume 'Advanced OR and AI methods in transportation' reflects his interest in practical applications of optimization techniques. His research demonstrates sustained scholarly activity from the 1990s to the present, with particular emphasis on advancing the state-of-the-art in multiobjective optimization theory and practice.

Wei Chenمشاهده پروفایل

استاد

• Software Engineering
• Intelligent Software Engineering
• Network Distributed Computing
• +۶ مورد دیگر

Wei Chen is a Research Fellow at the Institute of Software, Chinese Academy of Sciences, where he serves as a PhD and Master's supervisor. He leads the Software Engineering Technology R&D Center and maintains affiliations with the University of Chinese Academy of Sciences and its Nanjing College. Dr. Chen has established himself as a leading figure in intelligent software engineering research within China's academic community. His primary research focuses on four interconnected areas: intelligent code maintenance and quality assurance (particularly Python ecosystem compatibility based on domain knowledge), reliability assurance of complex IoT systems in human-machine-object convergence scenarios, cloud-native system development with emphasis on Function-as-a-Service optimization, and quality assurance of deep learning frameworks in resource-constrained environments. Dr. Chen's work consistently bridges theoretical advances with practical applications, maintaining strong industry collaborations with major Chinese technology companies. Analysis of Dr. Chen's recent publications reveals a strategic integration of AI techniques with traditional software engineering challenges. His research shows increasing emphasis on leveraging large language models for IoT component synthesis, sophisticated dependency management solutions for Python ecosystems, and innovative approaches to testing autonomous systems. The work demonstrates both theoretical depth and practical utility, with many publications leading to implemented tools and systems. Second Prize of Science and Technology Progress Award of China Institute of Electronics (2022) First Prize of Science and Technology Progress Award of China Institute of Electronics (2021) ACM SIGSOFT Distinguished Paper Award (2023) Special Prize of the 4th China Software Open Source Innovation Competition (2021) First Prize in the 4th China Software Open Source Innovation Competition (2021) OW2 Programming Contest First Prize (2016) Dr. Chen has mentored over ten graduate students who have achieved notable success in academic competitions and industry placements. His laboratory (TCSE, http://tcse.cn/) currently manages multiple significant research projects including 'Complex IoT System Reliability Assurance Key Technology Research' (2025-2028), 'Intelligent Development, Testing, and Maintenance of Cloud-native Software Ecosystems' (2024-2027), and 'Traffic Infrastructure Digital Industrial Software Architecture and Core Technology Standard System' (2021-2024). The lab maintains active collaborations with Huawei, Alibaba, Tencent, and other leading technology enterprises.