James Weichert

Hi! My name is James. I'm a second-year Computer Science M.S. student at Virginia Tech in the Machine Learning Lab. My research focuses on AI ethics and policy, including AI regulation and AI ethics education. I graduated from UC Berkeley in May 2023 with majors in computer science and data science and a minor in public policy. I'm interested in the intersection of public policy, governance, data, and technology and am passionate about promoting a democratic, human-centered, and responsible approach to AI. In my spare time, I like to travel, read, and cook.

During my time at UC Berkeley and Virginia Tech, I've developed a love for computer and data science teaching. This spring marks my tenth semester teaching, including two semesters as a lead TA for Data 8: Foundations of Data Science (UC Berkeley's introductory data science class with over 2,000 students in Fall 2022), four semesters as a graduate TA at Virginia Tech, and two summer semesters as the course instructor for Data 6: Introduction to Computational Thinking with Data.

My teaching experience spans both undergraduate and graduate courses covering a wide range of topics in computing and data science, including Python and Java programming, data manipulation and visualization, statistics, linear algebra, classical machine learning, and ethics. I am particularly passionate about teaching courses on introductory programming, data science and machine learning, and CS ethics or social implications of computing.

Virginia Tech

• CS 4664 Machine Learning Capstone

  Graduate TA (Spring 2025)

• CS 5805 Machine Learning I *

  Graduate TA (Fall 2024)

• CS 5806 Machine Learning II *

  Graduate TA (Spring 2024)

• CS 1114 Introduction to Software Design

  Graduate TA (Fall 2023)

* Graduate course

University of California, Berkeley

• Data 6 Introduction to Computational Thinking with Data

  Instructor (Summer 2022 & 2023)

• Data 8 Foundations of Data Science

  Lead TA (2022 - 2023), Undergraduate TA (Spring 2022), Tutor (Fall 2021)

My research at Virginia Tech explores the dual role of CS students as consumers of and learners about AI technologies. I am interested both in what government policies might shape the development and use of AI, and in how we teach students about AI and its impacts on society. A particular strand of inquiry explores student attitudes and competencies related to AI ethics and policy, culminating in the creation of a two-lecture "AI Policy Module" that I piloted with a graduate-level introductory machine learning class. The module is intended to go beyond the 'surface-level' treatment of AI ethics, focusing instead on how tools, policies, and governance structures can be leveraged to promote the responsible development and use of AI.

Publications

• J. Weichert and H. Eldardiry (2025). "Educating a Responsible AI Workforce: Piloting a Curricular Module on AI Policy in a Graduate Machine Learning Course," American Society for Engineering Education (ASEE) Annual Conference 2025. Recently accepted.
• J. Weichert, D. Kim, Q. Zhu, and H. Eldardiry (2024). "‘Do I Have to Take This Class?’: A Review of Ethics Requirements in Computer Science Curricula," ACM Technical Symposium on Computer Science Education (SIGCSE) 2025.
• J. Weichert, Q. Zhu, D. Kim, and H. Eldardiry (2024). "Perceptions of AI Ethics Policies Among Scientists and Engineers in Policy-Related Roles: An Exploratory Investigation," Digital Society. Recently accepted.
• J. Weichert and H. Eldardiry (2024). "Computer Science Student Attitudes Towards AI Ethics and Policy: A Preliminary Investigation," IEEE International Symposium on Technology and Society (ISTAS) 2024.
• J. Kim, M. Klopfer, J.R. Grohs, H. Eldardiry, J. Weichert, L.A. Cox II, D. Pike (2025). "Examining Faculty and Student Perceptions of Generative AI in University Courses," Innovative Higher Education.
• J. Weichert and C. Dimobi (2024). "DUPE: Detection Undermining via Prompt Engineering for Deepfake Text," Arxiv.

Email: james [dot] p [dot] weichert [at] gmail