Big Data Technology Capstone Project

Jianfeng Cai serves as Professor in the Department of Mathematics at The Hong Kong University of Science and Technology, where he has established himself as a leading expert in mathematical foundations of imaging and data sciences. After completing his Bachelor's degree from Fudan University and PhD from the Chinese University of Hong Kong in 2007, he worked at several prestigious institutions including the National University of Singapore, UCLA, and University of Iowa before joining HKUST in 2015. His research focuses on theoretical and algorithmic foundations of problems related to information, data, and signals, with particular emphasis on efficient representation, sensing, and analysis of high-dimensional data. His groundbreaking work has garnered over 6,500 citations for a single paper on matrix completion algorithms, while his research has found applications in medical imaging, compressed sensing, signal processing, and machine learning. Named a highly cited researcher in mathematics by Clarivate Analytics in 2017 and 2018, his contributions include pioneering work in image restoration, matrix completion, and blind motion deblurring. Beyond his research, he actively supervises numerous PhD students while maintaining collaborations across multiple disciplines and institutions. His current office is located in Room 3438 at HKUST, where he continues to advance the field of mathematical imaging and data sciences through innovative research and mentorship.

Ke Yi serves as Professor in the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology, where he also directs the MSc Program in Big Data Technology. After completing his BS from Tsinghua University in 2001 and PhD from Duke University in 2006, he has established himself as a leading expert in database theory, parallel computing, and data stream algorithms. His research excellence is evidenced by multiple prestigious awards, including two SIGMOD Best Paper Awards (2022, 2016), a PODS Test-of-time Award (2022), a SIGMOD Best Demonstration Award (2015), and a Google Faculty Research Award (2010). As an ACM Distinguished Member, he has made significant contributions to database systems and algorithms, particularly in areas of data security, privacy, and distributed computing. His teaching excellence has been recognized with multiple Best Teaching Awards for his course on Big Data Computing. Beyond his academic work, Yi maintains active research collaborations with industry partners including Alibaba, Huawei, Microsoft, and Google, while serving as associate editor for prestigious journals and regularly chairing major conferences in the field. His research spans theoretical computer science and practical database systems, with particular emphasis on designing algorithms that offer both theoretical guarantees and practical effectiveness.

Raymond Chi-Wing Wong serves as Professor and Associate Head (Education) in the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology, where he has established himself as a leading expert in databases, data mining, and data science. After completing his BSc, MPhil, and PhD degrees from the Chinese University of Hong Kong in 2002, 2004, and 2008 respectively, he has made significant contributions to both research and education. His teaching excellence has been recognized through numerous awards, including the prestigious Michael G. Gale Medal for Distinguished Teaching in 2020, multiple Honorary Mentions in the HKUST Common Core Teaching Excellence Award, and the School of Engineering Teaching Excellence Award. His teaching philosophy, which he calls "being an alchemist," encompasses nine principles: Active interaction, Listening, Care, High-quality teaching, Eagerness to take challenges, Motivating students, Inspiring students, Sharing, and Technology. Beyond his teaching achievements, he has published over 123 conference papers and 48 journal articles in prestigious venues, with research contributions spanning privacy-preserving data publishing, spatial databases, and graph algorithms. His work has garnered significant attention in the academic community, with several of his papers receiving best paper awards at major conferences including SIGMOD and VLDB. As Program Director of the Undergraduate Research Opportunities Program, he continues to inspire and mentor the next generation of computer scientists while maintaining active research collaborations with leading institutions worldwide.

Cecia Ki Chan serves as a Lecturer in the Department of Computer Science and Engineering at The Hong Kong University of Science and Technology, where she has been teaching since 2012 after completing her PhD in Systems Engineering and Engineering Management from the Chinese University of Hong Kong. Her research expertise spans information extraction, text mining, machine learning, and knowledge systems, with significant contributions to document classification, coreference resolution, entity extraction, and domain adaptation. As an instructor in multiple programs, she teaches courses ranging from introductory programming to advanced topics like Data Mining and Big Data Analytics, while supervising numerous award-winning final year projects including the Mobile App for Health and Well Being and TRAP: A VR and Mobile Cross-platform Networking Game. Her teaching portfolio includes core computer science courses such as Programming with C++, Object-Oriented Programming and Data Structures, and Exploring Artificial Intelligence, demonstrating her commitment to both undergraduate and postgraduate education. Beyond her academic responsibilities, she actively engages in developing practical applications, particularly in areas of virtual reality systems and health technology, showcasing the real-world impact of her expertise in computer science and engineering.