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Seminars and Events
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| October 20, 2025 |
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| September 26, 2025 |
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Title: Quantum Bayes' rule and Petz transpose map from the minimum change principle
Time: 10:30am
Venue: CB308, HKU
Speaker(s): Cliff Liu
Remark(s): Abstracct
Bayes' rule, which is routinely used to update beliefs based on new evidence, can be derived from a principle of minimum change. This principle states that updated beliefs must be consistent with new data, while deviating minimally from the prior belief. Here, we introduce a quantum analog of the minimum change principle and use it to derive a quantum Bayes' rule by minimizing the change between two quantum input-output processes, not just their marginals. This is analogous to the classical case, where Bayes' rule is obtained by minimizing several distances between the joint input-output distributions. When the change maximizes the fidelity, the quantum minimum change principle has a unique solution, and the resulting quantum Bayes' rule recovers the Petz transpose map in many cases.
About the speaker
Ge Bai is an Assistant Professor at The Hong Kong University of Science and Technology (Guangzhou). His research focuses on quantum causal inference, quantum machine learning and quantum communication network theory. Before his current position, he was a postdoctoral fellow at the National University of Singapore. He received his PhD from the University of Hong Kong, where he was awarded the Hong Kong Young Scientist Award.
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| September 19, 2025 |
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Title: Sublinear Algorithms for Graph Optimization
Time: 10:30am
Venue: CB308, HKU
Speaker(s): Cliff Liu
Remark(s): Abstracct
In the era of big data, massive datasets emerge in almost every application domain. Processing data in a traditional way, which takes at least time and space linear in the input size, becomes more-and-more commercially unaffordable. Important topics within sublinear algorithms include parallel computation (sublinear time), streaming algorithms (sublinear space), and communication complexity (sublinear communication), to name a few. In this talk, I will investigate the above topics through the lens of two fundamental problems: graph connectivity and bipartite matching. For graph connectivity, I will start with the simplest possible parallel algorithm with running time O(log n), then introduce the recent breakthroughs of how to break the O(log n) barrier. I will also show how to achieve o(log n) time and linear work, which is optimal. For bipartite matching, I will start with a simple approximate streaming algorithm whose correctness proof is based on combinatorial auctions, then I will introduce our recent work that finds the exact bipartite matching in the semi-streaming model that takes sublinear passes unless the graph is extremely dense.
About the speaker
Cliff Liu is an associate professor at Shanghai Jiaotong University. He was a postdoc in CMU theory group and obtained his PhD from Princeton. His research is around sublinear algorithms, graph algorithms, and data structures. Cliff was a recipient of the Gordon Y.S. Wu Fellowship and NSFC Science Fund Program for Distinguished Young Scholars.
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| September 12, 2025 |
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Title: Algorithmic Optimization of Carbon Footprint in Long-Haul Heavy-Duty E-Truck Transportation
Time: 10:00am
Venue: CB308, HKU
Speaker(s): Minghua Chen
Remark(s): Abstracct
The US transportation sector accounted for 37% of the country's total CO2 emissions in 2023. While representing only 0.4% of on-road vehicles, long-haul heavy-duty trucks contribute a disproportionate 12% of transportation carbon emissions, making their decarbonization a critical leverage point for climate change mitigation. Electrifying long-haul heavy-duty trucks represents a vital step toward decarbonizing the trucking sector, yet realizing their full potential requires minimizing the carbon footprint of timely deliveries. This involves optimizing electric truck travel between distant locations across the national highway system under strict deadline constraints. The resulting task, encompassing strategic path, speed, and charging planning, is combinatorial in nature and proven NP-hard. Consequently, traditional methods, including our recent approximation algorithms, struggle to optimize at scale. To this end, we present a novel stage-expanded graph formulation that reduces modeling complexity while revealing exploitable problem structure. Our approach naturally decomposes the problem into tractable subproblems, enabling efficient coordination between routing and charging decisions while maintaining manageable graph sizes. Leveraging these structural insights, we design an efficient algorithm with theoretical performance guarantees. Simulations using real-world data across the US highway system demonstrate that our method achieves an additional 25% carbon reduction beyond the 36% reduction from electrification alone, yielding a total 61% emissions decrease. Furthermore, our carbon-optimized strategy, applicable across various truck types, can achieve comparable carbon reductions nine years sooner than relying solely on zero-emission truck adoption, providing a powerful tool in addressing climate change.
About the speaker
Minghua is a Presidential Chair Professor in School of Data Science, The Chinese University of Hong Kong, Shenzhen. He received the Eli Jury award from UC Berkeley in 2007 and The Chinese University of Hong Kong Young Researcher Award in 2013. His recent research interests include online optimization and algorithms, machine learning for optimization with hard constraints and its application in power system operations, intelligent transportation, distributed optimization, and delay-critical networking. He is an ACM Distinguished Scientist and an IEEE Fellow.
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| May 21, 2025 |
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Title: Keynote talk by Zack KASS – Former Head of Go-To-Market for OpenAI
Time: 11:00am
Venue: KB223, 2/F, Knowles Building, HKU
Speaker(s): Zack Kass
Remark(s):
Keynote Abstract:
In the age of Artificial Intelligence, everything is changing, from how we work to how we create. How can you take advantage of this change to improve your life and career? As the former Head of Go-To-Market for OpenAI, Zack Kass has been at the forefront of AI's global transformation for over 15 years. In this compelling keynote, Zack counters the conventional dystopian narrative of AI, sharing a positive vision that offers the potential for game-changing innovation, opportunity, and human potential. Audiences will come away understanding how technology will reshape their industries, organizations, workforce, and lives for the better.
About Zack Kass:
Zack Kass is a globally recognized AI advisor and thought leader. With over 16 years of industry experience, he most recently served as Head of Go-To-Market at OpenAI, where he built the company's sales, solutions, and partnerships teams. Zack now advises Fortune 1000 companies and global institutions on long-term AI strategy and transformation. He also serves as Executive-in-Residence at the University of Virginia’s McIntire School of Commerce, where he contributes to curriculum development and discourse on the socioeconomic impact of AI.
Registration: https://shorturl.at/dehPt
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| May 09, 2025 |
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Title: JUPAS Information Session 2025
Time: 09:00am
Venue: Digital Literacy Lab and Student Advisory Services area, 2/F, Chi Wah Learning Commons, Centennial Campus, HKU
Speaker(s):
Remark(s): JUPAS Information Session 2025: Discover the Future of Computing and Data Science
The School of Computing and Data Science is thrilled to invite DSE applicants to the captioned event, which is designed to provide S.6 students with a comprehensive understanding of the exciting opportunities available in the fields of computing, data science, and related disciplines.
Event Highlights
Mini Lectures
Gain insights into key areas shaping the future of technology and data:
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Time
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Field
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09:00-09:30
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Reflection on Statistical Decision Sciences: A Lifelong Journey
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09:45-10:15
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Actuarial Science: Overview of Actuarial Mathematics
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10:30-11:00
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Computing and Data Science: Machine Intelligence Beyond Vision and Language
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11:15-11:45
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Applied Artificial Intelligence
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12:00-12:30
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Financial Technology:
Criminals on the Chain: Navigating the Landscape of Financial Crimes in Blockchain
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Mingling with CDS Professors
Meet and interact with our professors. This is your chance to ask questions, learn about our programmes, and gain valuable advice about your academic and career path.
Alumni Sharing
Hear from our accomplished alumni as they share their experiences, career journeys, and how their education has propelled them to success.
Final Year Project Showcase
Be inspired by innovative projects created by our final-year students, showcasing the practical applications of their knowledge and skills in computing and data science.
Event Details
Date: 9 May, 2025 (Friday)
Time: 09:00 – 12:30
Venue: Digital Literacy Lab and Student Advisory Services area, 2/F, Chi Wah Learning Commons, Centennial Campus, HKU
Who Should Attend?
This event is tailored for JUPAS applicants who are considering pursuing studies in computing, data science, artificial intelligence, actuarial science, statistics, or financial technology.
Why Attend?
- Gain a deeper understanding of the programmes offered by the School of Computing and Data Science.
- Learn about career opportunities and industry trends.
- Connect with professors, alumni, and current students.
- Get inspired by real-world applications of computing and data science.
How to Register
Spaces are limited, so secure your spot today!
Register Now: https://forms.gle/Zs5m8bcx7jBJcfCf6
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| February 13, 2025 |
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| December 05, 2024 |
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| December 02, 2024 |
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| October 03, 2024 |
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