# Bio (short)

Conrad Borchers is a PhD student at the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University, School of Computer Science, where he is advised by Vincent Aleven and Ken Koedinger. His research studies the effectiveness of educational technologies and learning pathways through data science methods. He holds an MSc in Social Data Science from the University of Oxford, UK, and a BSc in Psychology from the University of Tuebingen, Germany.

# Bio (long)

Conrad Borchers is a PhD student at the Human-Computer Interaction Institute (HCII) at Carnegie Mellon University’s School of Computer Science, advised by Vincent Aleven and Ken Koedinger. His research focuses on the intersection of educational technologies and data science, examining the effectiveness of intelligent tutoring systems, AI-based tools, and learning pathways. His work emphasizes the role of data-driven methods in enhancing learning outcomes, equity, and the design of scalable interventions. Borchers is particularly interested in how AI can support self-regulated learning in middle and high school students and course selection in undergraduates, leveraging machine learning, data mining, and natural language processing to inform the design of educational tools, strategies, and academic advising.

His research has been published in journals and conferences such as Educational Technology Research and Development, PloS One, The Internet and Higher Education, and the proceedings of the ACM Learning@Scale and Learning Analytics and Knowledge Conferences. His work has received multiple accolades, including three best paper awards.

Borchers holds an MSc in Social Data Science from the University of Oxford, where his thesis on labor market analysis using Stack Overflow data earned the OII Thesis Prize for Best MSc Dissertation, and a BSc in Psychology from the University of Tübingen, Germany. He has also worked as a research intern at the University of California, Berkeley, where he studied data-driven course workload estimations using LMS records and higher education enrollment data under Zachary A. Pardos.