Congratulations to all winners of the Faculty researcher awards

Faculty Outstanding Researcher Award 2022-23

Dr. Hailiang Chen receives INFORMS Information Systems Society (ISS) Sandy Slaughter Early Career Award 2022
Professor Hailiang Chen

Professor Hailing Chen has been awarded the Faculty Outstanding Researcher Award 2022-23. Professor Chen’s research focuses on social media, FinTech, and data analytics. The recognition of his advancement was evidenced by having five articles published in “A” journals over the past five years, including Information Systems Research; Journal of Financial Economics; Journal of Management Information Systems and Management Science. He was also very productive in grant applications. He received four GRF grants with an amount of HK$2.85M. His 2021 ISR paper received the award of Essential Science Indicators’ (ESI) Highly Cited Paper (Top 1% in the field of Social Sciences, General).

Faculty Output Prize 2022


Dr. Jinzhao Du

The aim of the prize was to honour  Faculty’s best research output published in the preceding calendar year. Dr. Jinzhao Du was awarded the Faculty Output Prize 2022 for the publication:

Wilfred Amaldoss, Jinzhao Du, and Woochoel Shin (2021),“Media Platforms’ Content Provision Strategies and Sources of Profits,” Marketing Science, 40 (3), 527-547.

This paper creatively emplies a three-sided game-theoretical model, which incorporates the interaction between a media platform and three groups of strategic players: consumers, advertisers, and content suppliers. It generates new and important insights on a media platform’s content provision strategies and their implications for platforms’ profits and content suppliers’ profits. The paper was published at Marketing Science, the leading journal in the field of marketing and is the first Marketing Science publication that is affiliated with HKU

Faculty KE Award 2023

HKU Summer Workshop on Innovation and Information Management HKU Summer Workshop on Innovation and Information Management
Professor Haipeng Shen, Dr Dan Yang and Dr Zhengli Wang

Prof. Shen, Dr. Yang, and Dr. Wang received the Faculty KE Award 2023 for the KE project “Transforming Industries: Empowering Organizations through Big Data Analytics.”

The teams has consistently participated in KE activities, leading to significant advancements in the application of big data analysis and machine learning across diverse industries. Their involvement has sparked transformative changes in organizational operations within mainland China and the Greater Bay Area, spanning sectors such as healthcare, finance, real estate, banking, dairy, and manufacturing.

Other Events
HKU Business School Releases a Comprehensive Evaluation Report on the Image-Generation Capabilities of AI Models
2025 | News
HKU Business School Releases a Comprehensive Evaluation Report on the Image-Generation Capabilities of AI Models
HKU Business School released a Comprehensive Evaluation Report on the Image Generation Capabilities of Artificial Intelligence Models, providing a systematic assessment of 15 text-to-image models and 7 multimodal large language models (LLMs). The results showed that ByteDance’s Dreamina and Doubao, as well as Baidu’s ERNIE Bot ranked among the top performers in terms of image content quality for new-image generation and image revision. However, despite DeepSeek having attracted global attention, its newly released text-to-image model, Janus-Pro, did not perform as well in new-image generation. HKU Business School researchers also found that while some text-to-image models excelled in content quality, their performance in safety and responsibility was significantly lacking. In general, multimodal LLMs demonstrated better overall performance compared to text-to-image models.
AI Image Generation Evaluation Results Released: ByteDance and Baidu Perform Well, DeepSeek Janus-Pro Falls Short
2025 | Research
AI Image Generation Evaluation Results Released: ByteDance and Baidu Perform Well, DeepSeek Janus-Pro Falls Short
The frontier of AI models has evolved beyond text processing to encompass the ability to understand and generate visual content. These models not only comprehend images but also generate visual content based on textual prompts. This study presents a systematic evaluation of the image generation capabilities of AI models, focusing on two core tasks: generating new images and revising existing images. Using carefully curated multidimensional test sets, we conducted a comprehensive evaluation of 22 AI models with image generation capabilities, including 15 text-to-image models and 7 multimodal large language models. The results show that ByteDance’s Dreamina and Doubao, as well as Baidu’s ERNIE Bot, demonstrate impressive performance in both new image generation and image revision tasks. Overall, multimodal large language models deliver superior performance compared to text-to-image models.