Lili Zhang

Profile Photo

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.

Book Chapter

Year Publication
2023 Lili Zhang; Ruben Mukherjee; Piyush Wadhai; Willie Muehlhausen; Tomas Ward (2023) 'Computational Phenotyping of Decision-Making over Voice Interfaces' In: [Link] [DOI]

Peer Reviewed Journal

Year Publication
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
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]

Other Publication

Year Publication
2021 Marie McCarthy; Lili Zhang; Greta Monacelli; Tomas Ward (2021) Using Methods From Computational Decision-making to Predict Nonadherence to Fitness Goals: Protocol for an Observational Study (Preprint). [Link] [DOI]
Certain data included herein are derived from the © Web of Science (2024) of Clarivate. All rights reserved.

Employment

Employer Position From / To
Maynooth University Assistant Professor 15/01/2023 - 31/12/2023

Education

Start date Institution Qualification Subject
18/11/2018 Dublin City University PhD Computational Modeling
01/09/2013 Harbin Institute of Technology Bachelor Instrument Science and Technology
01/09/2017 Harbin Institute of Technology Master Instrument Science and Technology

Languages

Language Reading Writing Speaking
Mandarin Chinese Fluent Fluent Fluent
English Fluent Fluent Fluent

Research Interests

Computational Modelling; Ecological Momentary Assessment; Human decision-making; Machine Behaviour; Large language Models; Intelligent Computing

Modules Coordinated

Term Title Subject
2024 CA168
2024 CA259