title: “From Clicks to Conversations: Evaluating the Effectiveness of Conversational Agents in Statistical Analysis” collection: publications category: manuscripts permalink: /publication/2025-02-08-Clicks-to-Conversations excerpt: ‘This study evaluates the effectiveness of conversational agents versus traditional point-and-click interfaces for statistical analysis tasks.’ date: 2025-02-08 paperurl: ‘https://www.arxiv.org/abs/2502.08114’ citation: ‘Wen, Q., Kochhar, P., Zeyada, S., Javaheri, T., & Rawassizadeh, R. (2025). “From Clicks to Conversations: Evaluating the Effectiveness of Conversational Agents in Statistical Analysis.” International Journal of Human-Computer Interaction (Accepted).’ —

title: “One Ocean, All Tasks: A Holistic Simulation Environment for Marine Robotics” collection: publications category: manuscripts permalink: /publication/2025-01-15-One-Ocean-Marine-Robotics excerpt: ‘This paper presents a comprehensive simulation environment for marine robotics that supports diverse underwater tasks and scenarios.’ date: 2025-01-15

paperurl: ‘http://academicpages.github.io/files/one-ocean-paper.pdf’

citation: ‘Liu, S., Wen, Q., Chen, X., Hu, X., & Su, N. (2025). “One Ocean, All Tasks: A Holistic Simulation Environment for Marine Robotics.” Submitted to ICRA 2026 (Under Review).’ —

title: “Estimation of Distribution Parameters by Mean Absolute Deviations of a Truncated Distribution Using Quantile Functions” collection: publications category: manuscripts permalink: /publication/2025-01-10-MAD-Distribution-Parameters excerpt: ‘This paper develops novel methods for estimating distribution parameters using mean absolute deviations and quantile functions for truncated distributions.’ date: 2025-01-10

paperurl: ‘http://academicpages.github.io/files/mad-distribution-paper.pdf’

citation: ‘Pinsky, E. & Wen, Q. (2025). “Estimation of Distribution Parameters by Mean Absolute Deviations of a Truncated Distribution Using Quantile Functions.” Statistical Papers (Under Review).’ —

title: “Pruning and Quantization Impact on Graph Neural Networks” collection: publications category: manuscripts permalink: /publication/2025-01-05-Pruning-Quantization-GNN excerpt: ‘This study investigates the effects of pruning and quantization techniques on the performance and efficiency of Graph Neural Networks.’ date: 2025-01-05

paperurl: ‘http://academicpages.github.io/files/pruning-gnn-paper.pdf’

citation: ‘Khedri, K., Wen, Q., & Rawassizadeh, R. (2025). “Pruning and Quantization Impact on Graph Neural Networks.” Manuscript.’ —

title: “Simple Approximations and Interpretation of Pareto Index and Gini Coefficient Using Mean Absolute Deviations and Quantile Functions” collection: publications category: manuscripts permalink: /publication/2025-01-01-Pareto-Gini-MAD-Approximations excerpt: ‘This paper provides simple approximation methods for computing Pareto index and Gini coefficient using mean absolute deviations and quantile functions.’ date: 2025-01-01 paperurl: ‘https://www.mdpi.com/2225-1146/13/3/30’ citation: ‘Pinsky, E. & Wen, Q. (2025). “Simple Approximations and Interpretation of Pareto Index and Gini Coefficient Using Mean Absolute Deviations and Quantile Functions.” Econometrics, 13(3), 30.’ —

title: “Tiny-HAR: Extremely Resource-efficient Human Activity Recognition Model Compression” collection: publications category: manuscripts permalink: /publication/2024-12-15-Tiny-HAR-Model-Compression excerpt: ‘This paper presents novel compression techniques for Human Activity Recognition models, achieving extreme resource efficiency while maintaining accuracy.’ date: 2024-12-15

paperurl: ‘http://academicpages.github.io/files/tiny-har-paper.pdf’

citation: ‘Longhitano, G., Wen, Q., & Rawassizadeh, R. (2025). “Tiny-HAR: Extremely Resource-efficient Human Activity Recognition Model Compression.” Manuscript.’ —

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Recommended citation: Wen, Q., Zeng, X., Zhou, Z., Liu, S., Hosseinzadeh, M., & Rawassizadeh, R. (2025). "GradES: Significantly Faster Training in Transformers with Gradient-Based Early Stopping." Submitted to ICLR 2026.
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