Khalil Anderson
Northwestern University CS PhD Grad Artificial Intelligence
About me
Born in Bronxville, New York, and raised in Ellicott City, Maryland, I am a Computer Science PhD from Northwestern University with interests in Machine Learning. More specifically, with interests in Reinforcement Learning, NLP, and how Machine Learning can help augment, not replace, humans in various areas. My previous research focused on providing multimodal analytics to support the development of people’s collaboration skills. I combined models such as traditional NLP, computer vision, LLMs, RAGs, and other Machine Learning methods, and I also conducted surveys and A/B testing to best align the design with users’ needs. Throughout this work, I collaborated with and managed researchers at various levels to support the scope of my research. I hope to continue working to support the development of AI to better support people and to focus on developing AI that meets people’s needs.
Publications:
[1] K. Anderson, Designing a Multimodal Collaboration Analytics Tool to Support Students’ Collaboration Literacy Development, PhD thesis, Northwestern University, 2026.
[2] D. Xie, Anderson, Khalil, T. Eze, C. Lin, B. Shin, and M. Worsley, Clara: An AI-augmented analytics dashboard for collaboration literacy, in International Conference on AI in Education, 2026.
[3] Khalil Anderson. 2022. Real-time Feedback for Developing Conversation Literacy. In Proceedings of the 2022 International Conference on Multimodal Interaction (ICMI ‘22). Association for Computing Machinery, New York, NY, USA, 701–704. https://doi.org/10.1145/3536221.3557031
[4] M. Worsley, K. Anderson, N. Melo, and J. Jang, “Designing Analytics for Collaboration Literacy and Student Empowerment,” JLA, vol. 8, no. 1, pp. 30–48, Apr. 2021, doi: 10.18608/jla.2021.7242.
[5] K. J. Anderson, T. Dubiel, K. Tanaka, M. Worsley, C. Poultney, and S. Brenneman, “Chemistry Pods: A Multimodal Real Time and Retrospective Tool for the Classroom,” in 2019 International Conference on Multimodal Interaction, New York, NY, USA, Oct. 2019, pp. 506–507. doi: 10.1145/3340555.3358662.
[6] K. Anderson and G. Vanhoy, “VALIDATION OF A CRV MODEL USING TVWS MEASUREMENTS,” p. 5, 2017.