
Ashley Gao
5.0
(6)
Build AI Models for Data Analytics with an R1 Professor
Studied at University of Virginia, Charlottesville
Works at William & Mary
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Ashley's Coaching Offerings
Custom hourly
Get help with AI Automation, AI Fundamentals, and .
Ashley also coaches for AI & ML Engineering and Science & Research. View all.
Ashley’s AI for Data & Analytics Qualifications
Experience level: Manager
Welcome to my profile! As an Assistant Professor at William & Mary, I lead the Galatea Lab, where we focus on developing intelligent machines that understand and model human emotions. With a PhD in Computer Science from the University of Virginia, my expertise spans large language models, affective computing, sentiment analysis, and generative AI in emotion modeling. I have authored papers accepted by top-tier AI and machine learning conferences and have served on NIH and NSF grant review panels. Whether you're looking to enhance your skills in AI for data and analytics or need guidance on leveraging AI technologies, I'm here to help you achieve your goals. Let's connect and explore how I can support your journey!
Ashley can help with:
AI Automation
AI Fundamentals
AI Model Evaluation
Dashboard Creation
Data Cleaning & Prep
Data Pipeline Automation
Data Strategy
Data Visualization
Freelancing
Natural Language Querying
Predictive Analytics
Reporting & Insights
Ashley also coaches for AI & ML Engineering and Science & Research. View all.
About Ashley
Ashley Gao is a computer scientist, AI researcher, and engineer specializing in audio-language models, affective computing, and real-world machine learning systems. She is currently an Assistant Professor of Computer Science at an R1 university, where she leads research at the intersection of human-centered AI and scalable system deployment. She has advised PhD, Master's, undergrads, and high school students. Dr. Gao’s work focuses on enabling machines to understand human emotion, behavior, and interaction through speech and language. She has developed end-to-end AI systems deployed in real-world environments, including intelligent monitoring and recommendation platforms designed to support healthcare applications such as dementia caregiving. Her approach combines cutting-edge modeling (e.g., deep learning, domain adaptation, and multimodal AI) with practical considerations like robustness, scalability, and usability. She has published extensively in top-tier venues such as ACL, EMNLP, and ICASSP, with contributions spanning emotion-aware speech modeling, audio large language models, and domain generalization. Her research has received multiple recognitions, including Best Paper awards, and she actively contributes to the field as a reviewer for leading conferences such as NeurIPS, ICML, and ICLR, as well as a panelist for organizations including the National Science Foundation (NSF) and National Institutes of Health (NIH). Beyond research, Dr. Gao works closely with interdisciplinary teams to translate advanced AI techniques into practical, high-impact solutions. She brings a strong ability to bridge technical depth with real-world needs, helping organizations design, deploy, and scale AI systems that deliver measurable outcomes.
Why do I coach?
I coach and consult because I enjoy turning advanced AI ideas into systems that actually work in the real world. Much of my background has been in developing machine learning models, but I’ve found that the bigger challenge and opportunity is helping organizations figure out what to build, how to build it, and how to make it reliable at scale. Consulting allows me to bridge that gap between research and impact, working closely with teams to translate complex technologies like audio-language models and emotion AI into practical, deployable solutions that create measurable value.
Work Experience
Assistant Professor
William & Mary
August 2023 - Present
I am an Assistant Professor in the Department of Computer Science. I lead the Galatea Lab, where we develop intelligent machines striving to understand and model human emotions. I have authored papers that are accepted by 1st tier AI/Machine Learning (ICML), Natural Language Processing (ACL, EMNLP), and signal processing (ICASSP, Interspeech) venues in recent years. I teach a PhD/MS level class on affective computing and an undergraduate level class on the fundamentals of AI/ML at the university. I have served on NIH, NSF grant review panels and the editorial board of Elsevier Smart Health. Area of expertise: Large Language Models (LLMs), affectively computing, sentiment analysis, generative AI in emotion modeling, prompt engineering, and broadly deep learning and machine learning.

PhD Student Researcher
University of Virginia
May 2019 - May 2023
I received my PhD candidacy and diploma from the University of Virginia under the tutelage of Dr. John A Stankovic. During my time at UVa, I studied system engineering and cyber physical systems and was part of the Link Lab.
Education

University of Virginia, Charlottesville
Doctor of Philosophy - PhD, Computer Science
2019 - 2023

UC San Diego
B.A., Literatures of the World
2012 - 2017

UC San Diego
Bachelor of Science - BS, Computer Science
6 Reviews
Overall Rating
5.0
Ashley has helped Leland clients get into Carnegie Mellon University