For five centuries, the textbook has delivered the same content, in the same order, to every learner. Agentic AI is starting to change that. These systems can reason, plan, use tools, remember, and act, and they are beginning to reshape how people learn. This course asks a simple question: what comes after the textbook?

You will debate current research in agentic AI and the learning sciences, and hear from guest speakers working at the frontier of AI and education. The centerpiece is a semester-long team project: interdisciplinary teams will design, build, and evaluate new AI capabilities for OpenStax, the Rice-based nonprofit whose free, openly licensed textbooks reach millions of learners worldwide. The best ideas have a real path to impact at global scale.

If you are curious about the future of learning, then this course is for you!

More information

Congratulations to Rice ECE/AP PhD student Johaun Hatchett, who just received the Best Student Paper award at the 27th International Conference on Artificial Intelligence in Education in Seoul, Korea for his paper:

"Learning Context Matters: Measuring and Diagnosing Personalization Gaps in LLM-Based Instructional Design"

Rice DSP PhD Shashank Sonkar (PhD, 2025) successfully defended his PhD thesis entitled "Pedagogy Meets AI: Challenges and Innovations in LLM-Powered Learning". His next step is an assistant professor position at the University of Central Florida in the Computer Science Department. His research focuses on artificial intelligence and natural language processing for education.

DSP group member Hossein Babaei successfully defended his PhD thesis entitled "Wavelets for Long Range Representation using State Space Models" in June 2025. His thesis develops new low-latency machine learning structures for time series using classical ideas from control theory (state space) and signal processing (wavelet bases and frames).

Hossein's next stop is at the AI startup Ground Truth Analytics.

DSP group member Sina Alemohammad successfully defended his PhD thesis entitled "Generative AI in the Age of Synthetic Data: Challenges and Solutions" in May 2025.

A pioneer in the study of "MADness" and "model collapse" that occur when generative AI systems are trained using self-synthesized data, Sina has also been a leader in developing methods for safely self-improving genAI models. His work has been written up in the New York Times and a host of other media outlets.

Sina's next position is as a postdoc in Atlas Wang's group at UT-Austin.

On 28 April 2025, we celebrated Professor Don Johnson and his remarkable 50 years of excellence at Rice University. His unwavering dedication to education, his innovative research, and his transformative contributions to the ECE community have made a lasting impact.

DoJo50 commemorated and celebrated the past, present, and future of one of the longest-running successful research and education programs at Rice with a variety of speakers, panel sessions, and discussions.

• • Symposium archive at Rice DSP Group
  • General information at Rice ECE Department

 

DSP group member Imtiaz Humayun successfully defended his PhD thesis entitled "Analyzing and Visualizing Emergent Structures in Deep Network Geometry" in April 2025. A leader in the interpreting deep networks in terms of continuous piecewise affine splines, Imtiaz is the founder of the SplineCam project that provides powerful visualization tools for the inner workings of deep networks.

Imtiaz’s next position is as a Research Scientist at Google Research, where he will be working on ways to make foundation models more adherent to human preferences and decision making processes.

DSP group member Paul Mayer successfully defended his PhD thesis entitled "Rethinking Maximum Likelihood Estimation" in April 2025.

Signal processing engineer by day, DJ and producer by night, Paul loves everything music and audio, from the science and mathematics behind it to producing and performing live. In addition to his research on statistical parameter estimation and machine learning, Paul is interested in the intersection of epistemology and artificial intelligence and has written a book that teaches mathematical logic alongside programming to STEM students. You can see samples of his teaching and radio-ready banter on his YouTube channel.

Paul's next position is R&D engineer at BASSBOSS in Austin, Texas, where he will be designing loudspeakers for nightclubs, festivals, and mobile DJs.

On the Geometry of Deep Learning
Randall Balestriero, Ahmed Imtiaz Humayun, Richard G. Baraniuk
Notices of the American Mathematical Society
April 2025

In this paper, we overview one promising avenue of progress at the mathematical foundation of deep learning: the connection between deep networks and function approximation by affine splines (continuous piecewise linear functions in multiple dimensions). In particular, we overview work over the past decade on understanding certain geometrical properties of a deep network’s affine spline mapping, in particular how it tessellates its input space. The affine spline connection and geometrical viewpoint provide a powerful portal through which to view, analyze, and improve the inner workings of deep networks.

Arxiv version

Richard Baraniuk, Rice University's C. Sidney Burrus Professor of Electrical and Computer Engineering and founder and director of OpenStax and SafeInsights, has been named the recipient of the 2025 IEEE Jack S. Kilby Signal Processing Medal.

The medal, presented annually since 1995, is given for outstanding achievements in signal processing. Baraniuk was specifically cited for his "contributions to multiscale and sparse signal processing."  The medal will be presented at the IEEE VIC Summit & Honors Gala in Tokyo in April 2025.

Rice Engineering News story | Rice News story | IEEE News story