Lingnan University has achieved another remarkable milestone in the 2025 edition of the World's Top 2% Scientists list, published by Stanford University. This year, a total of 43 Lingnan scholars were named in the list, representing an increase of about 50 per cent compared with last year's 29. Among them, 19 scholars were ranked among the global top 100 in their respective disciplines, underscoring the international recognition of Lingnan's research excellence and its rising global impact.
The Stanford World's Top 2% Scientists list evaluates the academic performance of scholars worldwide based on the significance of authorship and the number of citations in the Scopus database. Rankings are presented for career-long research impact and citations, as well as those in the single year of 2024, covering nearly all academic disciplines. This ranking has been among the most comprehensive for researchers worldwide and across disciplines since 2015.
43 distinguished Lingnan scholars named Stanford University’s World’s Top 2% Scientists.
Lingnan scholars recognised in this year's list represent diverse fields, including artificial intelligence (AI), data science, and humanities and social sciences.
Prof Xin Yao, Vice-President (Research and Innovation) and Tong Tin Sun Chair Professor of Machine Learning, ranks No. 4 in overall China and No. 1 in Hong Kong SAR in AI and Image Processing for career-long research impact.
President S. Joe Qin, President and Wai Kee Kau Chair Professor of Data Science, once again ranks No. 1 in overall China and Hong Kong SAR in his field of Industrial Engineering and Automation for career-long research impact.
Prof Richard M. Walker, Lee Shau Kee Foundation Chair Professor of Public Administration and Head of the Department of Government and International Affairs and Director of the Lingnan University Institute for Advanced Study (LUIAS), ranks No. 1 in overall China and Hong Kong SAR in Political Science and Public Administration for both career-long and 2024 single-year citation categories.
Prof Raymond Chan Hon-fu, Vice-President (Academics) cum Provost and Lam Man Tsan Chair Professor of Scientific Computing, ranks No. 11 in overall China and No. 1 in Hong Kong SAR in Numerical and Computational Mathematics for career-long research impact.
In addition, Prof Ngai Pun, Chair Professor of Department of Cultural Studies and Director of the Centre for Cultural Research and Development, ranks No. 2 in overall China and Hong Kong SAR in Cultural Studies for both career-long and 2024 single-year citation categories.
Prof Edward Kwabena Ameyaw, Research Assistant Professor of the School of Graduate Studies (GS), ranks No. 6 in overall China and No. 3 in Hong Kong SAR in Public Health for the 2024 single-year citation category.
Prof Siu Oi-ling, Head of Department of Psychology, Lam Woo & Co Ltd Chair Professor of Applied Psychology and Director of the Wofoo Joseph Lee Consulting and Counselling Psychology Research Centre, ranks No. 14 in China and No. 6 in Hong Kong SAR in her field of Business and Management for the career-long category; ranks No. 9 in Hong Kong SAR in the 2024 single-year citation category.
Furthermore, a total of 19 Lingnan scholars were ranked among the global top 100 in their respective disciplines for career-long and/or 2024 single-year citation categories.
President Qin congratulates Lingnan’s distinguished scholars and looks forward to seeing more Lingnan scholars translating their research outcomes into knowledge and technologies that benefit society and address the needs of the digital age.
President Qin congratulated Lingnan's distinguished scholars and remarked, “This ranking is recognised as one of the most influential and prestigious annual benchmarks for individual researchers globally. The number of Lingnan scholars included on the list has steadily increased at a significant rate. This year, several Lingnan scholars have topped the rankings in their respective fields in the China and Hong Kong SAR, which is truly encouraging. I look forward to seeing more of our scholars translating their research outcomes into knowledge and technologies that benefit society and address the needs of the digital age.”
The World's Top 2% Scientists list by Stanford University is based on a composite indicator of standardised citation metrics, which include the number of citations, the h-index (measuring scientific research output), and the significance of authorship.
Does a depressive mood inevitably lead to more pessimistic thinking or over-analysing? A global meta-analysis, the largest of its kind examining the relationship between a depressive mood and reality judgment, co-conducted by the Department of Psychology at Lingnan University has found that the key lies in the nature of the judgment. Overall, individuals in a depressive mood generally make more accurate judgments when handling self-referent tasks or complex issues requiring deep analysis. However, their accuracy is impaired as regards understanding others and interpreting interpersonal relationships. Researchers noted that the findings clarify a decades-long academic debate in psychology regarding whether a depressive mood allows individuals to perceive reality more objectively, and will aid in designing more targeted intervention strategies. The paper was published in Clinical Psychology Review, a top international academic journal in clinical psychology.
A global meta-analysis co-conducted by the Department of Psychology at Lingnan University finds that individuals in a depressive mood can make more accurate judgments in self-referent tasks requiring deep analysis.
The research team, comprising scholars from Lingnan University, the Polish Academy of Sciences in Poland, and The Chinese University of Hong Kong, aggregated psychological and clinical studies published globally between 1971 and November 2025 from three leading international academic databases: Web of Science, PsycINFO, and PubMed. Synthesising empirical data from 32,914 participants, the study examined the relationship between a depressive mood and judgmental accuracy across three distinct groups: non-depressed healthy controls, individuals with a self-reported depressive mood via questionnaires, and clinically diagnosed depressed patients, using known objective outcomes as the baseline for comparison.
The team integrated multiple classic psychological behavioural experiments in the study. The first type of experiment was the "green light test", which assessed judgment of control. Participants sat in front of a computer and chose whether or not to press a button to see if a green lightbulb would light up. In reality, the light was entirely randomised by a computer programme. The results showed that the healthy control group tended to believe they had a significant ability to control the light, exhibiting an optimistic bias. Conversely, individuals in a depressive mood understood that they had absolutely no control over the outcome.
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The second type of experiment was the "deception detection task" to test complex analytical capabilities. Participants watched multiple video clips of real people speaking and had to identify who was telling the truth and who was lying. Spotting deception requires multi-step logical deconstruction, representing a complex issue that demands deep analysis. The results indicated that in these complex tasks, individuals in a depressive mood achieved a higher level of analytical accuracy compared to the healthy control group.
The third type of experiment evaluated "other-referent tasks" testing the participants' ability to observe and decode the behaviours, emotional states, or social interactions of others, such as evaluating the actual emotional states of individuals in audio or video clips. The results revealed that the judgmental accuracy of individuals in a depressive mood lagged significantly behind. The study suggested that depressed individuals are more prone to misinterpret others' behaviour and reactions.
The research team explained that the first and second types of experiments involved self-referent judgments, such as evaluating one's own performance, assessing one's ability to influence outcomes, or facing complex tasks requiring multi-step analysis. Individuals in a depressive mood made slightly more accurate judgments than healthy controls because the non-depressed control group commonly exhibited an "optimistic bias". This bias acts as a healthy psychological defence mechanism that maintains self-esteem through over-optimism, causing people to overestimate the extent to which they can control outcomes.
However, the third type of experiment involved other-referent tasks, such as understanding the behaviour of others and interpreting interpersonal relationships. In these scenarios, participants with severe but not moderate or mild depressive symptoms were more prone to judgmental bias and demonstrated lower accuracy. This shows that the relationship between a depressive mood and judgmental accuracy varies significantly depending on the task and context; hence, a blanket assumption that a "depressive mood allows people to see reality more objectively" is inaccurate, especially for those in severe emotional distress, or with sleep problems, difficulty concentrating, or fatigue – all symptoms of clinical depression.
Prof Hodar Lam, lead and corresponding author of the study and Research Assistant Professor at Lingnan University.
Prof Hodar Lam, lead and corresponding author of the study and Research Assistant Professor of the Department of Psychology and Associate Programme Director of the MSc in Work and Organisational Psychology Programme at Lingnan University, stated that this global big-data study spanning nearly half a century provides a vital reference for Hong Kong citizens who face a fast-paced and stressful lifestyle. He said "From an evolutionary perspective, all emotions, positive and negative, help humans to survive. A depressive mood could trigger more analytical, problem-solving rumination and learnings from the negative emotions. A transient depressive mood in daily life is fundamentally different from clinical depression. Experiencing mild, short-term depressive or negative emotions in daily life does not necessarily mean a decline in cognitive capabilities. In tasks involving self-assessment, deep analysis, or complex judgments, individuals in a depressive mood are actually less susceptible to the ‘optimistic bias’ common to the healthy public, allowing them to make a more objective appraisal of their own situation and capabilities."
Prof Lam went on to explain "Society should avoid stereotyping and categorising all depressive moods as a lack of rational judgment. Equally, we must not misunderstand a depressive mood as an inherent advantage, thereby ignoring its potential risks. Since research shows that a depressive mood impairs accuracy in understanding others and interpreting interpersonal relationships, the judgmental bias of participants with more severe symptoms will increase. Therefore, people must take emotional health seriously. This area could become a key focus for future psychological interventions to design more targeted treatment and support strategies."
Prof Lam emphasised that to help others experiencing persistent emotional distress, first show empathy and validation instead of asking them to “think positively or rationally”, because their perceptions could be right. People with deteriorating depressive symptoms, or who find that their work, interpersonal relationships, or daily lives are being affected, are encouraged to seek professional help as a brave and responsible act of self-care.
The study was co-first authored by Dr June Yeung of the Polish Academy of Sciences and an alumna of Lingnan University. To read the full research paper, please visit: Depression and accuracy of judgment: A meta-analysis – ScienceDirect
