جستجوی استاد راهنمای دانشگاهی

Fang Kong is an Assistant Professor in the Department of Statistics and Data Science at the Southern University of Science and Technology (SUSTech). He earned his PhD in Computer Science from Shanghai Jiao Tong University under the supervision of Prof. Shuai Li and received his Bachelor's degree in Software Engineering from Shandong University. Education: PhD in Computer Science, Shanghai Jiao Tong University (2020-2024) Bachelor's Degree in Software Engineering, Shandong University (2016-2020) Dr. Kong is broadly interested in developing theoretically guaranteed algorithms for sequential decision-making problems, with particular focus on multi-armed bandits and reinforcement learning, as well as their applications in online experimentation and recommendation systems. His research spans theoretical foundations of bandit algorithms, matching markets, influence maximization, and online learning under various feedback structures. He has made significant contributions to the understanding of best-of-both-worlds algorithms that perform well in both stochastic and adversarial environments. His publication record shows a strong trajectory of high-impact work in top-tier conferences including NeurIPS, ICML, ICLR, AAAI, WWW, and AAMAS. His research demonstrates expertise in theoretical machine learning with a focus on bandit algorithms, particularly in matching markets and sequential decision-making problems. His work often bridges theoretical guarantees with practical applications in recommendation systems and online experimentation. Scientific Awards: CCF Doctoral Dissertation Award in Agent and Multi-Agent Systems (2025) Baidu Scholarship (2024) National Scholarship for PhD students (2023, 2022) AAMAS Student Scholarship (2023) Microsoft Research Asia Excellence Award (2022) Dr. Kong actively mentors students at various levels, including PhD and Master's students at SUSTech, visiting students from other institutions, and undergraduate researchers. He serves as a reviewer for top machine learning conferences (ICLR, NeurIPS, ICML, WWW) and journals (IEEE PAMI, TMLR). His teaching includes graduate Machine Learning and undergraduate Artificial Intelligence courses at SUSTech.

• Online Learning
• Reinforcement Learning
• Machine Learning
• +۴ مورد دیگر

Florian Bossmann is an Associate Professor at the College of Mathematics, Harbin Institute of Technology (HIT), specializing in Applied Signal Processing with a focus on algorithms and applications. His research encompasses inverse problems, greedy algorithms, sparsity, and compressed sensing, with applications in seismic exploration, ptychography, and video processing. He holds a PhD in Mathematics from the University of Göttingen (2013) and a Diplom in Mathematics from the University of Duisburg-Essen (2009). Current projects include NSFC-funded seismic data interpolation and a start-up grant for applied signal processing research. He teaches courses like 'Signal and Image Processing' and 'Calculus for Civil Engineering'. Supervising Master/PhD students in signal processing, he emphasizes collaboration and innovation. His lab, the ASP Group, explores cutting-edge methods in multidimensional data reconstruction and algorithm design. Prominent publications focus on impedance inversion, neural network applications in geoscience, and object reconstruction techniques. He has led collaborative research initiatives with institutions like the Fraunhofer Institute and the Helmholtz Center for Environmental Health.

• Applied Signal Processing
• Inverse Problems
• Greedy Algorithms
• +۵ مورد دیگر

Liyi Gu is an Assistant Professor in the Department of Information System and Management Engineering at the School of Business, Southern University of Science and Technology (SUSTech). His research bridges operations management and computational methodologies. Education: M.Phil. in Computer Science and Engineering from Hong Kong University of Science and Technology (HKUST) in 2014; Ph.D. in Operations Management and Management Science from University of Maryland in 2019. Gu’s research focuses on operations management , empirical analysis , and stochastic optimization , with an emphasis on simulation and socially responsible operations. His work applies quantitative models to real-world problems, such as humanitarian logistics and competitive online gaming dynamics. The article he co-authored in 2014 explores vulnerabilities in TCP traffic within wireless LANs, combining network security and protocol analysis. This aligns with broader themes of cybersecurity and traffic optimization, though no recent publications are yet detailed in the dataset.

• Operations Management
• Empirical Analysis
• Simulation
• +۳ 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.

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