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A Work In Progress
I am a cognitive scientist at the University of Maryland, specializing in the cognition underlying learning. My work is at the center of language processing, cognitive modeling, Theory of Mind, and the bridge between human and machine learning to develop equitable and impactful systems at scale. Experienced at leading professional teams and experimental projects.
Scientific & Philosophical Interests
Education
PhD in Human Development (Educational Psychology)
Currently pursuing doctoral research focusing on the intersection of machine learning, data science, and educational psychology. Examining how advanced computational methods can enhance learning outcomes and educational assessment.
B.A. in Economics and International Finance (Dual Degree)
Graduated with Honors, completing dual degrees in Economics and International Finance. Coursework included econometrics, statistical analysis, international trade theory, and monetary policy.
Work Experience
Co-Founder & Lead Systems Architect
- Co-founded AI writing platform with 10,000+ active users, developing academically aligned feedback systems that enhance student writing outcomes through personalized guidance.
- Architected model behavior through systematic evaluation and fine-tuning of transformer-based models, ensuring consistent ethical judgment and aligning outputs with educational values across diverse writing scenarios.
- Developed sophisticated prompt chaining systems that produce contextually appropriate feedback, using carefully engineered prompts and custom synthetic data pipelines to identify and remediate edge cases in model behavior.
- Led full LLM integration lifecycle: dataset curation, model fine-tuning with LLaMA and Mosaic models; performance benchmarking, and cloud deployment.
Founder & Director - Machine Learning Group
- Founded and lead cross-institutional research group with 10 Research Assistants from multiple universities, establishing collaborative workflows for distributed AI research projects.
- Direct two major projects: CLEAVER (multi-level text partitioning framework) and EDITORY (student-AI writing platform), advancing NLP applications in educational contexts.
- Oversee technical design, data pipelines, evaluation frameworks, and fine-tuning strategies across both projects.
- Coordinate interdisciplinary research integrating NLP, educational psychology, and AI alignment principles to create more effective and ethically sound learning technologies.
Graduate Researcher - Disciplined Reading and Literacy Research Lab
- Lead research on human cognition and learning with direct implications for AI modeling and evaluation, bridging psychological theory with computational implementation.
- Conduct empirical study on relational reasoning development in children (ages 3–7), including comprehensive task design, behavioral assessments, and cognitive modeling of reasoning patterns.
- Analyze student-AI interactions across thousands of writing sessions to identify engagement profiles and intervention opportunities using mixed-methods research approaches.
- Collaborate on developing intelligent tutoring systems and cognitively aligned AI tools that provide adaptive support based on established learning science principles.
• "Evaluating Use Patterns of an AI Writing Assistant", AERA, 2025 - Analyzed 8,700+ AI interactions from 1,500+ students
• "Relational Reasoning: What Is It and Why Does It Matter?", Penn State Berks, 2024 - Invited lecture on cognitive foundations
Logistics and Sales Specialist
- Managed end-to-end logistics operations for enterprise clients across ocean, air, and trucking networks, coordinating complex international shipments and customs clearance processes.
- Analyzed comprehensive shipping data to optimize routes, reduce transportation costs, and minimize transit times for client supply chains, improving operational efficiency.
- Developed and maintained strategic client relationships, providing expert guidance on logistics optimization, freight consolidation, and international shipping regulations.
- Generated new business through consultative sales approach, demonstrating platform advantages for supply chain visibility and using data-driven insights to solve client logistics challenges.
Projects
Mental Inferencing Machine
A computational framework combining hierarchical GNNs and LLMs for dynamic cognitive modeling and enhanced model interpretability.
The Mental Inferencing Machine is an innovative computational framework that combines hierarchical graph neural networks with large language models to create dynamic and interpretable models of human cognition. This project represents a significant advancement in cognitive modeling, AI interpretability, and understanding model reasoning patterns.
Presentations
Evaluating Use Patterns of an AI-Enabled Writing Assistant
Presentation in the session "The Influence of Digital Tools on Literacy, Learning Engagement, and Student Development." Identified four distinct engagement profiles from analyzing 1,581 students and 8,720 AI interactions in academic writing.
Relational Reasoning: What Is It and Why Does It Matter for Learning and Development?
Presented on the four forms of relational reasoning (analogy, anomaly, antinomy, antithesis) and their importance for critical thinking, learning, and cognitive development across educational contexts.
From Local to Global: Contextualizing Challenges to Students' Performance on Multiple-Document Tasks
Examined the challenges students face with multiple-document tasks in academic settings, discussing instructional context, task iterations, and implications for cross-national assessments in the age of AI.
Grants and Awards
Presidential Fellow
Flagship Fellowship awarded to doctoral students from unique educational, cultural, and theoretical backgrounds with early contributions.
Jean Mullan Graduate Fellowship Award
Graduate fellowship for innovative research and academic achievement.
Golden 1 National Scholarship Program
National award for academic achievement and community leadership.
Honors in Economics
Distinction awarded to top students in UC Davis's Economics program.
Media & Press
Courses & Skills
AI & Machine Learning
Data Science & Synthetic Data
Technologies & Tools
Research & Educational AI
Key Courses
Learning How to Learn
Learning Theory, Metacognition TA Grad Course
Neuroscience of Learning
Cognitive Neuroscience, Neural Development TA Grad Course
Cognitive Neuroscience
EEG, MEG, fMRI, Neuroimaging TA Grad Course
Mental Representations
Computation, Modularity, Cognitive Science Grad Course
Multilevel Modeling
Hierarchical, Longitudinal, Statistics Grad Course
Achievement Motivation
Expectancy-Value, Self-Efficacy Grad Course
Human Dev & Neuroscience
Neural, Biology, Development Grad Course
Cognitive Development
Theory, Learning, Child Development Grad Course