

I firmly believe in the emancipatory power of social work education. It equips students with the knowledge and tools to critically examine social structures and power dynamics, understand the root causes of inequality and injustice, and work towards creating a more equitable and just society. Social work education goes beyond simply imparting knowledge; it fosters a sense of social responsibility and empowers students to become agents of change.
I am also passionate about democratizing knowledge, particularly in the areas of research methods, quantitative analysis, and computational social science. I believe that these tools and skills are essential for effectively serving diverse populations and addressing complex social issues. This is one of the driving forces behind my research blog, where I share resources, tutorials, and insights to make these methods more accessible to students, practitioners, and community members.
Further, I strive to incorporate a QuantCrit perspective into my teaching, encouraging students to critically examine the ways in which quantitative methods can perpetuate or challenge existing power structures and social inequalities. Finally, I aim to foster a balanced approach to utilizing data science and computational tools in social work and mental health practice by integrating both critical and optimistic views of technology. My goal is to equip students with the knowledge and skills to harness the power of these tools for social good while remaining mindful of their potential limitations and biases.
TEACHING EXPERIENCE
Instructor of Record
- Technology for Social Good: Innovation and Ethics in Social Impact LeadershipCourse site
- Data Visualization Applications (SW672)Python tutorials
- Lab for Generalized Linear Models (PHDSW-GS 3067)Stata tutorials
- Lab for Introductory Statistics (PHDSW-GS 3028)Stata tutorials
- Using Artificial Intelligence to Support Youth Mental Health (MSWELGS 3121)
- 3-day Statistics Camp for Incoming PhD Students
Post-Master Certificate Director / Instructor
- Using Artificial Intelligence to Support Mental HealthI designed this program, and the teaching note on it is accepted at the Journal of Social Work Education.
Method workshops
- Implementing AI-based large language models for social work research: Foundations, local deployment of open-source models, and practical considerations
- Analyzing social media data for social work research: sentiment analysis and topic modeling using natural language processing
Invited and guest lectures
- Computational Social Science Methods for Minority Mental Health Research
- Computational Social Science Methods for Social Work Research
- Community-Engaged Research in Immigrant Mental Health
- Harnessing Data Science in Social Work: A Case for Mental Health Research
- Navigating the Intersection of Data Science and Social Work Research
- Using Artificial Intelligence to Support Youth Mental Health
- Leveraging Large Language Models for Computational Social Science
- Introduction to Reproducibility in Social Science Research
- How to get access to clinical notes on the MIMIC database using SQL
- The Influences of Immigration and Globalization on Wellbeing of Families
- Developing Resumes, CVs, & Websites for Graduate School
- Measurement Issues in Studying Diverse Populations and Evaluating Measurement Invariance and Cultural Validity
- Text as Data for Social Work Research