Richard G. Baraniuk

Richard G. Baraniuk, PhD

Full Affiliate Member, Research Institute
Houston Methodist


Biography

Dr. Baraniuk grew up in Winnipeg, Canada and received his B.Sc. degree in 1987 from the University of Manitoba. During his undergraduate studies he was a research engineer with Omron Tateisi Electronics in Kyoto, Japan (1986) and a Research Assistant with the National Research Council of Canada (1987). He received his M.Sc. degree in 1988 from the University of Wisconsin-Madison, and a Ph.D. degree in 1992 from the University of Illinois at Urbana-Champaign. While at the University of Illinois, he held a joint appointment with the CERL Sound Group and the Coordinated Science Laboratory.

After spending 1992-1993 at Ecole Normale Supérieure in Lyon, France, he joined Rice University in Houston, Texas, where he is currently the Victor E. Cameron Professor of Engineering and a sporadic DJ for KTRU. He spent sabbaticals at Ecole Nationale Supérieure de Télécommunications in Paris in 2001 and Ecole Fédérale Polytechnique de Lausanne in Switzerland in 2002. Dr. holds eight U.S. patents and has published more than 120 manuscripts. He Joined TMHRI in 2010.

Dr. Baraniuk received a NATO postdoctoral fellowship from NSERC in 1992, the National Young Investigator award from the National Science Foundation in 1994, a Young Investigator Award from the Office of Naval Research in 1995, the Rosenbaum Fellowship from the Isaac Newton Institute of Cambridge University in 1998, the C. Holmes MacDonald National Outstanding Teaching Award from Eta Kappa Nu in 1999, the Charles Duncan Junior Faculty Achievement Award from Rice in 2000, the University of Illinois ECE Young Alumni Achievement Award in 2000, the George R. Brown Award for Superior Teaching at Rice in 2001, 2003, and 2006, the Hershel M. Rich Invention Award from Rice in 2007, the Wavelet Pioneer Award from SPIE in 2008, the Internet Pioneer Award from the Berkman Center for Internet and Society at Harvard Law School in 2008, and the World Technology Award for Education in 2009.

He was selected as one of Edutopia Magazine's Daring Dozen educators in 2007. Connexions received the Tech Museum Laureate Award from the Tech Museum of Innovation in 2006. His work with Kevin Kelly on the Rice single-pixel compressive camera was selected by MIT Technology Review Magazine as a TR10 Top 10 Emerging Technology in 2007. He was co-author on a paper with Matthew Crouse and Robert Nowak that won the IEEE Signal Processing Society Junior Paper Award in 2001 and another with Vinay Ribeiro and Rolf Riedi that won the Passive and Active Measurement (PAM) Workshop Best Student Paper Award in 2003. He received the IEEE Signal Processing Society Magazine Column Award in 2009. He was elected Fellow of the IEEE in 2001 and Fellow of the AAAS in 2009.

Description of Research

Dr. Baraniuk's research interests lie in the areas of signal and image processing and include compressive sensing (compressed sensing), sensor networks, and pattern recognition and learning. In a bygone era he has worked in multiscale natural image modeling using hidden Markov models and time-frequency analysis.

In 1999, Dr. Baraniuk launched Connexions, a non-profit publishing project that aims to bring textbooks and learning materials into the Internet Age. Connexions makes high-quality educational content available to anyone, anywhere, anytime for free on the web and at very low cost in print by inviting authors, educators, and learners worldwide to "create, rip, mix, and burn" textbooks, courses, and learning materials from its global open-access repository. Each month, Connexions' free educational materials are used by over 2 million people from nearly 200 countries.

Areas Of Expertise

Signal and imaging processing Compressive sensing Sensor networks Pattern recognition Learning
Education & Training

PhD, University of Illinois at Urbana-Champaign
MSc, University of Wisconsin-Madison
Publications

Code Soliloquies for Accurate Calculations in Large Language Models
Sonkar, S, Chen, X, Le, M, Liu, N, Basu Mallick, D & Baraniuk, R 2024, . in LAK 2024 Conference Proceedings - 14th International Conference on Learning Analytics and Knowledge. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 828-835, 14th International Conference on Learning Analytics and Knowledge, LAK 2024, Kyoto, Japan, 3/18/24. https://doi.org/10.1145/3636555.3636889

Foveated thermal computational imaging prototype using all-silicon meta-optics
Saragadam, V, Han, Z, Boominathan, V, Huang, L, Tan, S, Fröch, JE, Böhringer, KF, Baraniuk, RG, Majumdar, A & Veeraraghavan, A 2024, , Optica, vol. 11, no. 1, pp. 18-25. https://doi.org/10.1364/OPTICA.502857

SELF-CONSUMING GENERATIVE MODELS GO MAD
Alemohammad, S, Casco-Rodriguez, J, Luzi, L, Humayun, AI, Babaei, H, LeJeune, D, Siahkoohi, A & Baraniuk, RG 2024, , Paper presented at 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Austria, 5/7/24 - 5/11/24.

Marking: Visual Grading with Highlighting Errors and Annotating Missing Bits
Sonkar, S, Liu, N, Mallick, DB & Baraniuk, RG 2024, . in AM Olney, I-A Chounta, Z Liu, OC Santos & II Bittencourt (eds), Artificial Intelligence in Education - 25th International Conference, AIED 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14829 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 309-323, 25th International Conference on Artificial Intelligence in Education, AIED 2024, Recife, Brazil, 7/8/24. https://doi.org/10.1007/978-3-031-64302-6_22

IMPLICIT NEURAL REPRESENTATIONS AND THE ALGEBRA OF COMPLEX WAVELETS
Roddenberry, TM, Saragadam, V, de Hoop, MV & Baraniuk, RG 2024, , Paper presented at 12th International Conference on Learning Representations, ICLR 2024, Hybrid, Vienna, Austria, 5/7/24 - 5/11/24.

Automated Long Answer Grading with RiceChem Dataset
Sonkar, S, Ni, K, Tran Lu, L, Kincaid, K, Hutchinson, JS & Baraniuk, RG 2024, . in AM Olney, I-A Chounta, Z Liu, OC Santos & II Bittencourt (eds), Artificial Intelligence in Education - 25th International Conference, AIED 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14829 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 163-176, 25th International Conference on Artificial Intelligence in Education, AIED 2024, Recife, Brazil, 7/8/24. https://doi.org/10.1007/978-3-031-64302-6_12

Expanded Multiplexing on Sensor-Constrained Microfluidic Partitioning Systems
Kota, PK, Vu, HA, LeJeune, D, Han, M, Syed, S, Baraniuk, RG & Drezek, RA 2023, , Analytical Chemistry, vol. 95, no. 48, pp. 17458-17466. https://doi.org/10.1021/acs.analchem.3c01176

Fourth Annual Workshop on A/B Testing and Platform-Enabled Learning Research
Ritter, S, Heffernan, N, Williams, JJ, Lomas, D, Bicknell, K, Roschelle, J, Motz, B, McNamara, D, Baraniuk, R, Basu Mallick, D, Kizilcec, R, Baker, R, Fancsali, S & Murphy, A 2023, . in L@S 2023 - Proceedings of the 10th ACM Conference on Learning @ Scale. L@S 2023 - Proceedings of the 10th ACM Conference on Learning @ Scale, Association for Computing Machinery, Inc, pp. 254-256, 10th ACM Conference on Learning @ Scale, L@S 2023, Copenhagen, Denmark, 7/20/23. https://doi.org/10.1145/3573051.3593397

Unlocking Financial Success: Empowering Higher Ed Students and Developing Financial Literacy Interventions at Scale
Bradford, BC, Basu Mallick, D & Baraniuk, RG 2023, . in L@S 2023 - Proceedings of the 10th ACM Conference on Learning @ Scale. L@S 2023 - Proceedings of the 10th ACM Conference on Learning @ Scale, Association for Computing Machinery, Inc, pp. 363-367, 10th ACM Conference on Learning @ Scale, L@S 2023, Copenhagen, Denmark, 7/20/23. https://doi.org/10.1145/3573051.3596188

Secure Education and Learning Research at Scale with OpenStax Kinetic
Basu Mallick, D, Bradford, BC & Baraniuk, R 2023, . in L@S 2023 - Proceedings of the 10th ACM Conference on Learning @ Scale. L@S 2023 - Proceedings of the 10th ACM Conference on Learning @ Scale, Association for Computing Machinery, Inc, pp. 360-362, 10th ACM Conference on Learning @ Scale, L@S 2023, Copenhagen, Denmark, 7/20/23. https://doi.org/10.1145/3573051.3596187

Evaluating generative networks using Gaussian mixtures of image features
Luzi, L, Marrero, CO, Wynar, N, Baraniuk, RG & Henry, MJ 2023, . in Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023. Proceedings - 2023 IEEE Winter Conference on Applications of Computer Vision, WACV 2023, Institute of Electrical and Electronics Engineers Inc. pp. 279-288, 23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023, Waikoloa, United States, 1/3/23. https://doi.org/10.1109/WACV56688.2023.00036

Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust
Babaei, H, Alemohammad, S & Baraniuk, RG 2024, , IEEE Transactions on Neural Networks and Learning Systems, vol. 35, no. 4, pp. 5014-5026. https://doi.org/10.1109/TNNLS.2023.3266429

A Blessing of Dimensionality in Membership Inference through Regularization
Tan, J, LeJeune, D, Mason, B, Javadi, H & Baraniuk, RG 2023, , Proceedings of Machine Learning Research, vol. 206, pp. 10968-10993.

Towards the Future of AI-Augmented Human Tutoring in Math Learning
Aleven, V, Baraniuk, R, Brunskill, E, Crossley, S, Demszky, D, Fancsali, S, Gupta, S, Koedinger, K, Piech, C, Ritter, S, Thomas, DR, Woodhead, S & Xing, W 2023, . in N Wang, G Rebolledo-Mendez, V Dimitrova, N Matsuda & OC Santos (eds), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky - 24th International Conference, AIED 2023, Proceedings. Communications in Computer and Information Science, vol. 1831 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 26-31, 24th International Conference on Artificial Intelligence in Education , AIED 2023, Tokyo, Japan, 7/3/23. https://doi.org/10.1007/978-3-031-36336-8_3

SplineCam: Exact Visualization and Characterization of Deep Network Geometry and Decision Boundaries
Humayun, AI, Balestriero, R, Balakrishnan, G & Baraniuk, R 2023, . in Proceedings - 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 2023-June, Institute of Electrical and Electronics Engineers Inc. pp. 3789-3798, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2023, Vancouver, Canada, 6/18/23. https://doi.org/10.1109/CVPR52729.2023.00369

Deduction under Perturbed Evidence: Probing Student Simulation (Knowledge Tracing) Capabilities of Large Language Models
Sonkar, S & Baraniuk, RG 2023, , CEUR Workshop Proceedings, vol. 3487, pp. 26-33.

A Case Study Using Large Language Models to Generate Metadata for Math Questions
Bainbridge, K, Walkington, C, Ibrahim, A, Zhong, I, Mallick, DB, Washington, J & Baraniuk, R 2023, , CEUR Workshop Proceedings, vol. 3487, pp. 34-42.

MultiQG-TI: Towards Question Generation from Multi-modal Sources
Wang, Z & Baraniuk, RG 2023, . in E Kochmar, J Burstein, A Horbach, A Horbach, A Horbach, R Laarmann-Quante, N Madnani, A Tack, V Yaneva, Z Yuan, T Zesch & T Zesch (eds), BEA 2023 - 18th Workshop on Innovative Use of NLP for Building Educational Applications, Proceedings of the Workshop. Proceedings of the Annual Meeting of the Association for Computational Linguistics, Association for Computational Linguistics (ACL), pp. 682-691, 18th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2023, Toronto, Canada, 7/13/23.

Summary of “Towards the Future of AI-augmented Human Tutoring in Math Learning”
Thomas, DR, Aleven, V, Baraniuk, R, Brunskill, E, Crossley, S, Demszky, D, Fancsali, S, Gupta, S, Ritter, S, Woodhead, S, Xing, W & Koedinger, K 2023, , CEUR Workshop Proceedings, vol. 3491.

Unsupervised Learning of Sampling Distributions for Particle Filters
Gama, F, Zilberstein, N, Sevilla, M, Baraniuk, RG & Segarra, S 2023, , IEEE Transactions on Signal Processing, vol. 71, pp. 3852-3866. https://doi.org/10.1109/TSP.2023.3324221

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