Dr. Feng Liu is currently a Research Assistant Professor and Doctoral Supervisor at the School of Psychology, Shanghai Jiao Tong University. He undertook an academic visit to Tsinghua University from October to November 2021 and served as a Visiting Scholar at NYU Shanghai from 2023 to 2024. He is currently an IEEE Senior Member and a CCF Senior Member, and serves on the Affective Computing Specialized Committee of the Chinese Information Processing Society of China, the Emotional Intelligence Committee of the Chinese Association for Artificial Intelligence, and the Technical Committee on Affective Computing and Understanding of the China Society of Image and Graphics. His main research interests include dynamic macro/micro-expression recognition, quantitative affective computing, affective brain-computer interfaces, computational psychology and computational psychiatry, and other interdisciplinary areas at the intersection of computer science and psychology. As first author or corresponding author, he has published more than 100 academic papers in well-known journals and conferences including IEEE/CVF CVPR, IEEE Transactions on Affective Computing, IEEE Transactions on Audio, Speech and Language Processing, IEEE Transactions on Computational Social Systems, IEEE Transactions on Biometrics, Behavior, and Identity Science, ACM Multimedia, Pattern Recognition, Intelligent Computing, Neural Networks, Neurocomputing, Journal of Computer Research and Development, and Journalism Research. He currently serves as an Associate Editor or Young Editorial Board Member for international journals including Biomedical Engineering Frontiers, CAAI Artificial Intelligence Research, The Innovation Informatics, Journal of Social Computing, Behavioral Sciences, and Applied Sciences.

Website: https://lekko1988.github.io/

Affective Computing and Brain-Computer Interfaces

Dynamic Macro/Micro-Expression Recognition, Modeling, and Analysis

Computational Psychology and Computational Cognitive Neuroscience

Interdisciplinary Research at the Intersection of Computer Science and Psychology

Ph.D., School of Computer Science and Technology, East China Normal University

2023.08 - 2024.12  |  Visiting Scholar, Arts and Sciences, NYU Shanghai

2017.03 - 2018.06  |  Jiangsu Huaxin Blockchain Industry Research Institute Co., Ltd., Chief Information Officer

Professional Service and Memberships

Editorial Board Member, Cog (2026-present)

Young Editorial Board Member, Journal of Social Computing (2026-present)

Young Editorial Board Member, The Innovation Informatics (2026-present)

Young Editorial Board Member, Behavioral Sciences (2026-present)

Young Editorial Board Member, Biomedical Engineering Frontiers (BMEF) (2025-present)

Young Editorial Board Member, Applied Sciences (2025-present)

Member, Committee on Behavioral and Health Psychology, Chinese Psychological Society (2026-present)

Member, Emotional Intelligence Committee, Chinese Association for Artificial Intelligence (2025-present)

Member, Technical Committee on Affective Computing and Understanding, China Society of Image and Graphics (2025-present)

Member, Affective Computing Specialized Committee, Chinese Information Processing Society of China (CIPS) (2023-present)

Area Editor for Cognitive Intelligence, CAAI Artificial Intelligence Research (CAAI AIR), Chinese Association for Artificial Intelligence (2024-present)

Founding Member, Blockchain Technical Committee, Chinese Association of Automation (CAA) (2020-2024)

Industry Professor, Wuxi University (2020-2025)

IEEE Senior Member (2026-present)

CCF Senior Member (2020-present)

Academic Publications

[1]F. Liu, R. Huang, Q. Zheng, Y. Wang and F. Liu, "PRP: Procedural-to-Real Masked Pre-training for Transferable and Interpretable Audio Representations," IEEE Transactions on Audio, Speech and Language Processing, doi: 10.1109/TASLPRO.2026.3724415. [Leading journal in speech and audio AI, 5-year impact factor: 6.0] (The study addresses the abundance of unlabeled real-world recordings and the shortage of high-quality labels, and provides a speech-data solution for training embodied intelligence systems and affective world models.)

[2]F. Liu, B. Nan, X. Qian, and X. Fu, "Temporal-spatial cross-fusion for dynamic micro expression recognition," Pattern Recognition, 2026, doi: 10.1016/j.patcog.2026.113715. [Leading journal in pattern recognition and artificial intelligence, 5-year impact factor: 8.0] (The study systematically explores the complementarity of temporal and spatial features for dynamic micro-expression recognition from a dimensional fusion perspective, providing an efficient solution for small-sample settings. Details: https://psychology.sjtu.edu.cn/xsdt/552.html)

[3]F. Liu, B. Nan, X. Qian and X. Fu, "Evaluating and Correcting Human Annotation Bias in Dynamic Micro-Expression Recognition," IEEE Transactions on Affective Computing, doi: 10.1109/TAFFC.2026.3671731. [IEEE Transactions, leading journal in affective computing, ranked No. 1 in its WoS field, 5-year impact factor: 11.7] (The study introduces a quality yardstick for micro-expression datasets in affective computing to quantify human annotation bias introduced during dataset construction. Details: https://psychology.sjtu.edu.cn/xsdt/528.html)

[4]Chen Shi, Yiding Shen, Juntong Chen, Feng Liu, Chenhui Li, Changbo Wang* (2026). “Enhancing trust through a human-center evaluation framework from an accessibility perspective: The case of graph anomaly detection,” International Journal of Human-Computer Studies, 211:103781, doi:10.1016/j.ijhcs.2026.103781. [CCF-A, SSCI] (The study proposes accessibility as a user-centered interpretability objective for generative AI, with emphasis on comprehensibility, verifiability, and timely feedback.)

[5]Feng Liu*, Lingna Gu, Chen Shi, Xiaolan Fu*. "Action Unit Enhance Dynamic Facial Expression Recognition." ACM Multimedia 2025, doi:10.1145/3746027.3754877. [CCF-A] (The study extracts shared knowledge in dynamic facial expression recognition from an Action Unit perspective and uses it to improve dynamic facial expression recognition. Details: https://psychology.sjtu.edu.cn/xsdt/486.html)

[6]Feng Liu*, Ziwang Fu, Yunlong Wang. "Reward-Based Gradient Modulation for Multimodal Emotion Recognition With LoRA." IEEE Transactions on Computational Social Systems, 2025, doi:10.1109/TCSS.2025.3566373. [IEEE Transactions] (The study proposes multimodal emotion recognition based on reward-based gradient modulation, combining dynamic gradient control with parameter-efficient fine-tuning to improve balance and efficiency in multimodal training. Details: https://psychology.sjtu.edu.cn/xsdt/400.html)

[7]Siyuan Shen, Feng Liu*, Hanyang Wang and Aimin Zhou*. (2025). "Towards Speaker-Unknown Emotion Recognition in Conversation Via Progressive Contrastive Deep Supervision," IEEE Transactions on Affective Computing, doi: 10.1109/TAFFC.2025.3558222. [IEEE Transactions, leading journal in affective computing, ranked No. 1 in its WoS field, 5-year impact factor: 11.7] (The study proposes a progressive contrastive deep supervision paradigm for emotion recognition in speaker-unknown settings. Details: https://psychology.sjtu.edu.cn/xsdt/348.html)

[8]Jiahao Qin, Feng Liu*, Lu Zong*. "BC-PMJRS: A Brain Computing-inspired Predefined Multimodal Joint Representation Spaces for enhanced cross-modal learning," Neural Networks, Volume 188, 2025, 107449, https://doi.org/10.1016/j.neunet.2025.107449. (The study proposes a brain-inspired approach to enhance cross-modal learning for multimodal emotion recognition.)

[9]Feng Liu*, Hanyang Wang, Siyuan Shen. "Robust Dynamic Facial Expression Recognition." IEEE Transactions on Biometrics, Behavior, and Identity Science, 2025. https://doi.org/10.1109/TBIOM.2025.3546279. [IEEE Transactions] (Building on the DFER task introduced at CVPR 2023, the study further examines learning under noise and proposes a consistency principle and metric to guide model learning and improve DFER recognition accuracy.)

[10]Feng Liu*, Jiaqi Jiang, Yating Lu, Zhanyi Huang, Jiuming Jiang. "The Ethical Security of Large Language Models: A Systematic Review." Frontiers of Engineering Management, 2025. https://doi.org/10.1007/s42524-025-4082-6. (A systematic review examining privacy and ethical issues associated with large language models.)

[11]Feng Liu*, Jingyi Hu, Qijian Zheng. (2025). "OCC-PAD-OCEAN: An Quantitative Perceptible Modeling of Big Five Personality Based on Computational Affection." Proceedings of the 58th Hawaii International Conference on System Sciences, 3218-3227. http://dx.doi.org/10.24251/HICSS.2025.389. [Top-2 conference in Information Systems] (Extending the OCC-PAD-OCEAN line of work, the study expands the sample size, further validates data accuracy, and develops an interpretability framework for AI models from a developmental perspective.)

[12]Feng Liu*, Qijian Zheng. (2025). "An Advanced BERT-Based Commodity Classification on Amazon Online Malls Based on Consumer Cognitive Attributes." Proceedings of the 58th Hawaii International Conference on System Sciences, 4812-4820. http://dx.doi.org/10.24251/HICSS.2025.579. [Top-2 conference in Information Systems] (The study combines deep learning with consumer cognitive attributes to develop product classification technology for Amazon online marketplaces.)

[13]Liu, F.*, Wang, P., Hu, J., Shen, S., Wang, H., Shi, C., Peng, Y., & Zhou, A.* (2025). "A psychologically interpretable artificial intelligence framework for the screening of loneliness, depression, and anxiety." Applied Psychology: Health and Well-Being, 17(1), e12639. https://doi.org/10.1111/aphw.12639. (Building on the psychologically interpretable OCC-PAD quantitative affective computing paradigm, the study develops AI models for loneliness, depressive emotion, and trait anxiety.)

[14]Feng Liu*, Qianqian Ju, Qijian Zheng and Yujia Peng*. "AI in Mental Health: Innovations brought by AI Techniques in Stress Detection and Interventions of Building Resilience." Current Opinion in Behavioral Sciences, Volume 60, 2024, 101452, ISSN 2352-1546, https://doi.org/10.1016/j.cobeha.2024.101452. (A review of AI techniques from the perspective of psychiatric diagnosis, stress detection, and resilience interventions.)

[15]Liu F. "Artificial Intelligence in Emotion Quantification: A Prospective Overview." CAAI Artificial Intelligence Research, 2024, 3: 9150040. https://doi.org/10.26599/AIR.2024.9150040. (A review of emotion quantification from an artificial intelligence perspective.)

[16]Jiaqi Liu, Feng Liu*. "Cognitive Breakthrough or Intuitive Attraction: Persuasive Cues in Health-Risk Experience Videos and Their Effects on Audience Empathy." Journalism Research, 2024, (06): 76-90+121-122. DOI:10.20050/j.cnki.xwdx.2024.06.009. [Leading journal in journalism and communication] (The study applies the OCC-PAD-OCEAN psychologically interpretable personality quantification model to short-video analysis for facially based trait and psychological assessment.)

[17]S. Shen, Y. Gao, F. Liu, H. Wang and A. Zhou*, "Emotion Neural Transducer for Fine-Grained Speech Emotion Recognition," ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Republic of Korea, 2024, pp. 10111-10115. [Leading conference in speech and signal processing]

[18]Shen S, Liu F, Wang H, Wang Y, Zhou A. "Temporal Shift Module with Pretrained Representations for Speech Emotion Recognition." Intelligent Computing. 2024;3:Article 0073. https://doi.org/10.34133/icomputing.0073. (Co-first authors). [Science Partner Journal] (The study proposes a temporal-shift middleware architecture built on pretrained representations for speech emotion recognition.)

[19]F. Liu*, Yihao Zhou, Jingyi Hu. "An attention-based approach for assessing the effectiveness of emotion-evoking in immersive environment." Heliyon, Volume 10, Issue 3, 2024, e25017, https://doi.org/10.1016/j.heliyon.2024.e25017. [Cell Press journal] (The study combines a Go/No-Go paradigm with virtual reality to examine the effects of emotion induction on attention.)

[20]F. Liu et al., "OPO-FCM: A Computational Affection Based OCC-PAD-OCEAN Federation Cognitive Modeling Approach," IEEE Transactions on Computational Social Systems, vol. 10, no. 4, pp. 1813-1825, Aug. 2023, https://doi.org/10.1109/TCSS.2022.3199119. [IEEE Transactions] (The study introduces a psychologically interpretable OCC-PAD quantitative affective computing paradigm and builds an AI modeling framework using the Big Five OCEAN personality model.)

[21]S. Shen, F. Liu and A. Zhou, "Mingling or Misalignment? Temporal Shift for Speech Emotion Recognition with Pre-Trained Representations," ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Rhodes Island, Greece, 2023, pp. 1-5, doi: 10.1109/ICASSP49357.2023.10095193. [Leading conference in speech and signal processing]

[22]Feng Liu, Zhihan Li, Kun Jia, Panwei Xiang, Aimin Zhou, Jiayin Qi, Zhibin Li. "Bitcoin Address Clustering Based on Change Address Improvement." IEEE Transactions on Computational Social Systems, 2024, 11(6):8094-8105. doi:10.1109/TCSS.2023.3239031. [IEEE Transactions]

[23]Hanyang Wang, Bo Li*, Shuang Wu, Siyuan Shen, Feng Liu*, Shouhong Ding, Aimin Zhou*. "Rethinking the Learning Paradigm for Dynamic Facial Expression Recognition." IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2023), 2023, 17958-17968. https://doi.org/10.1109/CVPR52729.2023.01722. [Leading conference in computer vision] (The study re-examines existing temporal facial expression recognition at IEEE/CVF CVPR and introduces the Dynamic Facial Expression Recognition (DFER) task and its computational paradigm.)

Additional publications are available at the following links

https://faculty.sjtu.edu.cn/fengliu/zh_CN/url/745461/list/index.htm

https://www.researchgate.net/profile/Feng-Liu-152

Research Grants, Achievements, and Honors

Research Grants and Projects in the Past Five Years

[1] Facial Dynamic-Specific Representations and Core Variable Modeling of Depressive Emotion, State Key Laboratory of Cognitive Science and Mental Health, 2026-2028, Principal Investigator.

[2] In-Vehicle Distributed Therapeutic Dialogue System Based on the emotion2vec Psychological Expert Model, Tencent Kaiyang Laboratory, Grant No. 26H010101747, 2026-2027, Principal Investigator.

[3] Precise Recognition and Assessment of Depressive Emotion, Startup Fund for Young Faculty at SJTU, Grant No. 25X010506040, 2025-2027, Principal Investigator.

[4] Dynamic Facial Expression Recognition Enhanced by Facial Muscle Movements, William Mong Man Wai International Exchange Fund, Shanghai Jiao Tong University, Grant No. EE7102008, 2025, Principal Investigator.

[5] Dynamic Social Processing Mechanisms and Prediction of Social Anxiety Based on Eye Tracking, 2023 Open Research Project of the Beijing Key Laboratory of Behavior and Mental Health, 2023-2024, ranked 1st (1/6), Principal Investigator.

[6] International Experience in Building Green Technology Innovation Ecosystems under Carbon Neutrality and Implications for Shanghai, Shanghai Science and Technology Program, 2021-2022, ranked 2nd (2/2), Co-Principal Investigator.

[7] Theories, Assessment System, and Prototype System for Enhancing Emotional Cognition in the General Population, Grant No. 22511105901, Shanghai Science and Technology Program, 2022.09.01-2024.08.31, Participant (6/49).

[8] Deep Learning-Based Quantitative Methods and Systems for Federated Cognitive Modeling, 2021 Director's Fund Project of the Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, 2021.06.01-2023.06.01, Participant (2/9).

[9] Public Opinion Response and Governance in Major Public Health Emergencies, Grant No. 72042004, Special Project on "Response, Governance and Impacts of Public Health Emergencies including the COVID-19 Pandemic" under the National Natural Science Foundation of China, 2020-2021, Participant (5/10).

[10] Technologies and Methods for Governing Cross-Border Data Flows, China-CEEC Higher Education Joint Education Project, Grant No. 202033, 2020.10-2022.09, Participant (4/10).

Supervised undergraduate research projects at Shanghai Jiao Tong University, including the 13th Chun-Tsung Program with student Pengchao Feng (2025-01-05), the 14th Chun-Tsung Program with student Yuanfang Wang (2026-06-10), the 49th Participation in Research Program (PRP) project (T541PRP49003), and the 50th PRP project (T541PRP50002).

Granted Invention Patents

[1] Feng Liu et al. A Micro-Expression Classification Method Based on a Self-Attention Residual Convolutional Neural Network [Invention Patent], CN202110635297.9, 2023.09.19.

[2] Feng Liu et al. An Emotion-Based OCC-PAD-OCEAN Federated Cognitive Modeling Method [Invention Patent], CN202110523544.6, 2021.05.13.

[3] Feng Liu et al. A Facial Expression Classification Method Based on a Genetic Algorithm [Invention Patent], CN112668551B, 2023.09.22.

[4] Feng Liu et al. An Endogenous Data Security Interaction Method for a Dual-Middle-Platform, Dual-Chain Architecture [Invention Patent], ZL 2020 1 1013609.4, 2023.06.27.

[5] Feng Liu et al. An Erasable Processing Method for Blockchain-Based Public Opinion Evidence Preservation Information [Invention Patent], ZL 2020 1 1039245.7, 2023.06.27.

[6] Feng Liu et al. A Cross-Level Heterogeneous Authorization Method for Organizing Blockchain-Based Public Opinion Evidence Preservation Information [Invention Patent], ZL 2020 1 1039673.X, 2023.06.27.

[7] Feng Liu et al. A Device for Blockchain-Based Decomposition and Composition of NFTs [Invention Patent], ZL 2021 1 1270592.5, 2023.06.27.

Honors and Awards

[1] Selected for the 4th "Wenzhi Elite" Young Backbone Talent Training Program of Shanghai Jiao Tong University, 2026.

[2] Feng Liu et al. (1/6), "Understanding the Mind from the Face: Methods for Modeling and Analyzing Dynamic Macro- and Micro-Expressions," Shanghai Open Source Information Technology Association, Grand Prize, Shanghai Open Source Innovation Excellence Award, 2025.

[3] Ran Wu, Jiahao Qin, Jieyu Chen, Feng Liu, "Applicability of the Integrated Motivational-Volitional Model of Suicidal Behaviour among Chinese University Students," Shanghai Association of University Psychological Counseling, First Prize for Conference Paper, 2025 Annual Academic Conference of the Shanghai Association of University Psychological Counseling, 2025.

[4] Feng Liu et al. (1/4), "A General-Purpose Secure Multiparty Computation Protocol for Blockchain-Based Data Privacy Protection," Institute of Scientific and Technical Information of China, F5000 Top Articles from Outstanding S&T Journals of China, 2022.

Student Recruitment and Training (Including Joint Training)

Student Training

The laboratory has jointly trained more than ten doctoral and master's students, with students serving as first or co-first authors on more than ten papers. Team members have received multiple awards at or above the municipal level in innovation and entrepreneurship competitions. More than ten undergraduate students have also been trained, and the laboratory has repeatedly supervised successful undergraduate applications to the Chun-Tsung Program. The laboratory is currently recruiting new members, with a focus on academic development for second- and third-year undergraduate students in Shanghai. Priority is given to students intending to apply for graduate study at the School of Psychology, Shanghai Jiao Tong University. Joint training of master's and doctoral students is also available with the consent of their primary supervisors. Places remain available for students planning to begin master's or doctoral study in 2028. Applicants with backgrounds in psychology, computer science, or biological sciences are preferred. Interested students are invited to contact the laboratory by email with a CV.

Representative CiL Laboratory Alumni (Including Jointly Trained Students)

Class of 2026, Bingyu Nan. Jointly trained master's student, School of Artificial Intelligence and Computer Science, Jiangnan University. Representative publications: IEEE T-AFFC 2026 and Pattern Recognition 2026. Destination: PhD study at Central South University.

Class of 2025, Lingna Gu. Undergraduate in Computer Science and Technology, East China Normal University. Representative publication: ACM Multimedia 2025. Destination: master's study at the University of New South Wales.

Class of 2025, Qijian Zheng. Undergraduate in Computer Science and Technology, East China Normal University. Representative publications: Intelligent Computing 2025, HICSS 2025, COBS 2024, and JSSR 2023. Destination: direct-entry PhD study at Fudan University.

Class of 2025, Jiahao Qin. Jointly trained PhD student, University of Liverpool. Representative publication: Neural Networks 2025. Destination: overseas postdoctoral research.

Class of 2024, Hanyang Wang. Academic master's student in Computer Science and Technology, East China Normal University. Representative publication: IEEE/CVF CVPR 2023. Destination: Midea (Shanghai).

Class of 2024, Siyuan Shen. Academic master's student in Computer Science and Technology, East China Normal University. Representative publications: IEEE T-AFFC 2026 (highly cited), IEEE ICASSP 2023/2024, and Intelligent Computing. Destination: Baidu (Shanghai).

Class of 2023, Ziwang Fu. Jointly trained master's student, School of Computer Science, Beijing University of Posts and Telecommunications. Representative publications: IEEE T-CSS 2025 and FCS 2024. Destination: Midea (Shanghai).

Representative former CiL undergraduate students include Yunlong Wang of Tsinghua University (PhD study at the Chinese Academy of Sciences), Yaxuan Liu of East China Normal University (graduate study at Peking University), Jiahao Zhang of East China Normal University (PhD study at Pennsylvania State University), Ying Lei of East China Normal University (master's study at Simon Fraser University), and Yihao Zhou of East China Normal University (master's study at Pennsylvania State University).

Representative overseas student Research Assistants (RAs) at CiL include Yihan Wang, a master's student at Durham University; Weihao Hua, an undergraduate student at Rutgers University; Yuhan Wang, an undergraduate student at the University of California, Los Angeles (UCLA); and others.