Lili Zhang
Lili Zhang is an Assistant Professor in the School of Computing at Dublin City University (DCU), specialized in data analytics and computational modelling of human and machine decision-making. She is now leading the research of building a open-access 3-D gamification platform for Ecological Momentary Neurocognitive Assessment. She is also interested in using methodologies from cognitive psychology and game theory to understand Large Language Models (LLMs) behaviour, aiming to craft strategies to manage and steer LLM-based systems in ways that are beneficial and safe for humanity.
Lili completed here PhD in January 2023, focusing on developing smartphone-based ecological momentary assessment for enhancing phenotyping of human decision-making in clinical settings. She received her MSc in Instrumental Science and Technology from Harbin Institute of Technology in China.
Peer Reviewed Journal
Year | Publication | |
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2024 | (2024) 'A dimensional difference-based population size adjustment framework for differential evolution'. Information Sciences, . https://doi.org/10.1016/j.ins.2024.120110 | |
2024 | (2024) 'CIR-DE: A chaotic individual regeneration mechanism for solving the stagnation problem in differential evolution'. Swarm and Evolutionary Computation, . https://doi.org/10.1016/j.swevo.2024.101718 | |
2024 | (2024) 'Biased Bi-Population Evolutionary Algorithm for Energy-Efficient Fuzzy Flexible Job Shop Scheduling with Deteriorating Jobs'. Complex System Modeling and Simulation, . | |
2023 | (2023) 'Adaptive data collection for intraindividual studies affected by adherence'. Biometrical Journal, . https://doi.org/10.1002/bimj.202200203 | |
2022 | Zhang, Lili; Vashisht, Himanshu; Nethra, Alekhya; Slattery, Brian; Ward, Tomas (2022) 'Differences in Learning and Persistency Characterizing Behavior in Chronic Pain for the Iowa Gambling Task: Web-Based Laboratory-in-the-Field Study'. Journal of Medical Internet Research, 24 (4). [DOI] | |
2022 | Li, C.; Deng, L.; Qiao, L.; Zhang, L. (2022) 'An efficient differential evolution algorithm based on orthogonal learning and elites local search mechanisms for numerical optimization'. Knowledge-Based Systems, 235 . [Link] [DOI] | |
2022 | Zhang, L; Monacelli, G; Vashisht, H; Schlee, W; Langguth, B; Ward, T (2022) 'The Effects of Tinnitus in Probabilistic Learning Tasks: Protocol for an Ecological Momentary Assessment Study'. Jmir Research Protocols, 11 (11). [DOI] | |
2021 | McCarthy, M; Zhang, L; Monacelli, G; Ward, T (2021) 'Using Methods From Computational Decision-making to Predict Nonadherence to Fitness Goals: Protocol for an Observational Study'. Jmir Research Protocols, 10 (11). [DOI] |
Pre-print
Year | Publication | |
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2022 | Lili Zhang; Greta Monacelli; Himanshu Vashisht; Winfried Schlee; Berthold Langguth; Tomas Ward (2022) Tinnitus Assessment via performance in probabilistic learning tasks in the context of ecological momentary assessment (Preprint). PREPRINT [Link] [DOI] | |
2021 | lili Zhang; Himanshu Vashisht; Andrey Totev; Nam Trinh; Tomas Ward (2021) Distributed machine learning methods for the support of Many-Labs collaborations in computational modelling of decision making: A comparative study (Preprint). PREPRINT [Link] [DOI] | |
2020 | Lili Zhang; Himanshu Vashisht; Alekhya Nethra; Brian Slattery; Tomas Ward (2020) Differences in Learning and Persistency Characterizing Behavior in Chronic Pain for the Iowa Gambling Task: Web-Based Laboratory-in-the-Field Study (Preprint). PREPRINT [Link] [DOI] |
Research Interests
Computational Modelling; Ecological Momentary Assessment; Human decision-making; Machine Behaviour; Large language Models; Intelligent Computing