cv
Basics
| Name | Sinong Wang |
| Label | PhD Candidate |
| theron.wang@uta.edu | |
| Phone | (681) 221-7301 |
| Url | https://theronwang.github.io/ |
| Summary | I am a PhD candidate in Computer Science at the University of Texas at Arlington. My research interests include machine learning, data mining, and natural language processing. I am currently working on the project of unspuervised lexicon discovery. |
Work
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2024.07 - present Web Developer
CSE department, UT Arlington, TX, USA
Developing the web app service for the CSE department at UTA.
- Developed the web app service for the CSE department at UTA.
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2023.08 - 2024.07 Teaching Assistant
CSE department, UT Arlington, TX, USA
Designed and graded assignments and exams for the undergraduate courses.
- CSE 5302 Programming Language Concepts
- CSE 4369 Natural Language Processing
- CSE 6332 Cloud Computing
Volunteer
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2014.04 - 2015.07 Zurich, Switzerland
Lead Organizer
People's Climate March
Lead organizer for the New York City branch of the People's Climate March, the largest climate march in history.
- Awarded 'Climate Hero' award by Greenpeace for my efforts organizing the march.
- Men of the year 2014 by Time magazine
Education
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2023.08 - present Arlington, TX, USA
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2021.08 - 2023.08 Arlington, TX, USA
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2020.09 - 2023.06 Shenyang, China
Master
Northestern University, Shenyang, China
Software Engineering
- Software Engineering
- Data Structure
Awards
- 2020.10.01
- 2025.04.11
- 2025.08.01
Certificates
| Convolutional Neural Networks | ||
| DeepLearning.AI | 2021-09-10 |
| Structuring Machine Learning Projects | ||
| DeepLearning.AI | 2021-06-20 |
| Improving Deep Neural Networks | ||
| DeepLearning.AI | 2021-05-30 |
| Neural Networks and Deep Learning | ||
| DeepLearning.AI | 2020-11-22 |
Publications
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2026.10.14 Audio-Visual Dog Identification and Tracking in Real-World Videos
Arxiv
A multimodal dog-fingerprinting framework that combines visual identification, multi-object tracking, and vocal fingerprinting to attribute barks to individual dogs in real-world videos, with a benchmark of 46 videos and 213 annotated bark events.
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2026.10.06 A Preview of Computational Animal Linguistics
ACM Computing Surveys
A survey of computational animal linguistics: the study of non-human animal vocal communication as a language system using data-driven methods from NLP and large language modeling.
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2026.05.03 Unsupervised Discovery and Analysis of the Vocal Repertoires and Patterns of Select Corvid Species
ICASSP
Unsupervised discovery and acoustic analysis of the vocal repertoires and call patterns of select corvid species.
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2025.10.27 A Data-driven Approach to the Longitudinal Study of Canine Vocal Pattern Development
ACM MM
The Canine Age Transition Vocalization Dataset of 125 dogs across 6 breeds with verified birthdates, and a longitudinal analysis of how bark types and acoustic units change as dogs mature.
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2025.10.27 EmotionalCanines: A Dataset for Analysis of Arousal and Valence in Dog Vocalization
ACM MM
A framework for collecting reliable arousal and valence labels at scale, producing a dataset of 1,400 Husky and Shiba Inu bark sequences labeled for emotional state.
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2025.10.27 DogSpeak: A Canine Vocalization Classification Dataset
ACM MM
A large-scale in-the-wild dataset of 77,202 bark sequences (33 hours) from 156 dogs of 5 breeds with dog ID, sex, and breed labels, with benchmarks for sex, breed, and individual recognition.
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2025.07.24 Toward Automatic Discovery of a Canine Phonetic Alphabet
ACL
Outstanding Paper Award. An iterative algorithm inspired by human phonetic discovery, based on minimal pairs, that produces a complete alphabet of canine phoneme-like units and recurring acoustic units tied to dogs' environments and activities.
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2024.11.01 Phonetic and Lexical Discovery of Canine Vocalization
EMNLP
A data-driven approach using self-supervised HuBERT to classify canine phones and adaptive grammar induction to identify a preliminary vocabulary, some of whose words show causal relations with dog activities.
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2024.02.25 Phonetic and Lexical Discovery of a Canine Language using HuBERT
Arxiv
A self-supervised HuBERT approach to classify phoneme labels in dog vocalizations and identify a rudimentary vocabulary, with a web-based labeling system that highlights phoneme n-grams in uploaded dog audio.
Skills
| Computer Science | |
| Statistics and Probability | |
| Natrual Language Processing | |
| Machine Learning | |
| Web Development | |
| Python, Pytorch, Flask, SQL, HTML, CSS, JavaScript |
| Cooking | |
| Chinese Cuisine | |
| Baking | |
| Desserts |
Languages
| English | |
| Fluent |
| Mandarin | |
| Naive Speaker |
Interests
| Drama | |
| Stage Performance |
| Video Games | |
| Hades | |
| Slay the Spire | |
| The Legend of Zelda | |
| Civilization VI | |
| The Elder Scrolls V: Skyrim |
References
| Professor Chun Chang | |
| Sinong is a child with a sincere heart, well-mannered and cultured. It is precisely his sincerity that allows him to immerse himself in his roles, steadily progressing toward his goal without fear of adversity. |
| Professor Wei Zhang | |
| Failure is often the main theme in scientific research, and the ability to endure continuous setbacks is one of the necessary conditions for success. During the three years of working with Sinong, his passion for science, the constant flow of ideas, and his down-to-earth spirit have convinced me that he will become an excellent scientist. |
Projects
- 2023.01 - 2023.04
A canine language lexicon discovery analysis system
Developed a system that can automatically discover the lexicon of a canine language.
- Natural Language Processing
- Web development