Junior Full Stack Developer
Junior Full Stack Developer at SilverLine System Integrators Pvt. Ltd. Spearheaded the development of 5+ full-stack applications using Django and Flask for the fintech startup.
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Web Developer
Web Developer at The University of Texas at Arlington, responsible for managing departmental web applications. Improved website-wide search query performance by over 90% using a caching mechanism.
publications
DogSpeak: A Canine Vocalization Classification Dataset
Published in ACM MM 25 (Datasets Track), 2025
This paper introduces DogSpeak, a dataset for canine vocalization classification.
Recommended citation: Hridayesh Lekhak, Theron S. Wang, Tuan M. Dang, and Kenny Q. Zhu. 2025. DogSpeak: A Canine Vocalization Classification Dataset. In Proc. ACM MM 25 (Datasets Track).
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Emotional Canines: A Dataset for Analysis of Arousal and Valence in Dog Vocalization
Published in ACM MM 25 (Datasets Track), 2025
This paper presents a dataset for analyzing arousal and valence in dog vocalization.
Recommended citation: Tuan M. Dang, Theron S. Wang, Hridayesh Lekhak, and Kenny Q. Zhu. 2025. Emotional Canines: A Dataset for Analysis of Arousal and Valence in Dog Vocalization. In Proc. ACM MM 25 (Datasets Track).
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Toward Automatic Discovery of a Canine Phonetic Alphabet
Published in Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025
Dogs communicate intelligently but little is known about the phonetic properties of their vocalization communication. For the first time, this paper presents an iterative algorithm inspired by human phonetic discovery, which is based on minimal pairs that determine phonemes by distinguishing different words in human language, and is able to produce a complete alphabet of distinct canine phoneme-like units.
Recommended citation: Wang, T. S., Li, X., Lekhak, H., Dang, T. M., Wu, M., & Zhu, K. Q. (2025, July). Toward Automatic Discovery of a Canine Phonetic Alphabet. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (pp. 9207-9219).
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A Data-driven Approach to the Longitudinal Study of Canine Vocal Pattern Development
Published in Proceedings of the 33rd ACM International Conference on Multimedia, 2025
This paper presents a data-driven approach to the longitudinal study of canine vocal pattern development.
Recommended citation: Lekhak, Hridayesh and Wang, Theron S. and Dang, Tuan M. and Zhu, Kenny Q. (2025). A Data-driven Approach to the Longitudinal Study of Canine Vocal Pattern Development. In Proceedings of the 33rd ACM International Conference on Multimedia (MM \"25).
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