Post-Doctoral Fellow, Baylor University, 2015
PhD, Electrical and Computer Engineering, The University of Texas at El Paso (UTEP), 2011
MS, Electrical Engineering, Chihuahua Institute of Technology (ITCH), 2006
BS, Computer Science, Nogales Institute of Technology (ITN), 2004
 

Journal Publications

Tianqi Ding, Annette von Jouanne, Liang Dong, Xiang Fang, Tingke Fang, Pablo Rivas, and Alex Yokochi, "A Review of AI Applications in Lithium-Ion Batteries: From State-of-Health Estimations to Prognostics", in Energies, vol. 19, no. 2, article 562, 1/2026. [ bib | .pdf ]

Pablo Rivas, Renato Borras-Chavez, Jorge Yero Salazar, Ted Cheeseman, Pipa Low, Ken Southerland, Douglas Krause, and Sarah S Kienle, "Scalable Individual Identification in marine megafauna: Harnessing Pretrained Vision Models for Non-Invasive Ecological Monitoring", in Methods in Ecology and Evolution, 7/2025. [ bib |  .pdf ]

Bikram Khanal and Pablo Rivas, "Data-dependent generalization bounds for parameterized quantum models under noise", in The Journal of Supercomputing, vol. 81, article 611, 3/2025. [ bib | .pdf ]

Bikram Khanal, Pablo Rivas, Arun Sanjel, Korn Sooksatra, Ernesto Quevedo, and Alejandro Rodriguez, " Generalization Error Bound for Quantum Machine Learning in NISQ Era—A Survey ", in Quantum Machine Intelligence, vol. 6, article no. 90, 12/2024. [ bib |  .pdf ]

Korn Sooksatra and Pablo Rivas, " Dynamic-Max-Value ReLU Functions for Adversarially Robust Machine Learning Models ", in Mathematics, vol. 12, no. 22, p. 3551, 11/2024. [ bib |  .pdf ]

Maisha Binte Rashid, Md Shahidur Rahaman, and Pablo Rivas, " Navigating the Multimodal Landscape: A Review on Integration of Text and Image Data in Machine Learning Architectures ", in Machine Learning and Knowledge Extraction, vol. 6, no. 3, pp. 1545-1563, 7/2024. [ bib |  .pdf ]

Pablo Rivas, Javier Orduz, Tonni Das Jui, Casimer DeCusatis, and Bikram Khanal, " Quantum-Enhanced Representation Learning: A Quanvolutional Autoencoder Approach against DDoS Threats ", in Machine Learning and Knowledge Extraction, 5/2024. [ bib |  .pdf ]

Bikram Khanal and Pablo Rivas, " A Modified Depolarization Approach for Efficient Quantum Machine Learning ", in Mathematics, 5/2024. [ bib |  .pdf ]

Tonni Das Jui and Pablo Rivas, " Fairness issues, current approaches, and challenges in machine learning models ", in the International Journal of Machine Learning and Cybernetics, 1/2024. [ bib |  .pdf ]

Ernesto Quevedo, Tomas Cerny, Alejandro Rodriguez, Pablo Rivas, Jorge Yero, Korn Sooksatra, Alibek Zhakubayev, and Davide Taibi, " Legal Natural Language Processing from 2015-2022: A Comprehensive Systematic Mapping Study of Advances and Applications ", in IEEE Access, 11/2023. [ bib |  .pdf ]

Conference Presentations and Publications

Paapa Kwesi Quansah, Pablo Rivas, and Ernest Bonnah, "VERIFY: A Novel Multi-Domain Dataset Grounding LTL in Contextual Natural Language via Provable Intermediate Logic", in Proc. of International Conference on Learning Representations (ICLR 2026), 4/2026. [ bib | .pdf ]

Abanisenioluwa Orojo, Emmanuelli El-Mahmoud, Erika Leal, Pablo Rivas, "ByteFlow: A Byte-Level LLM for Deep Packet Inspection and Network Intelligence", in Proc. of the Workshop on AI for Cyber Threat Intelligence (WAITI) 2025, co-located with the Annual Computer Security Applications Conference (ACSAC25), 12/2025. [ bib | .pdf ]

Pablo Rivas, Jorge Yero Salazar, Javier S. Turek, and Bikram Khanal, "Few-Label SetFit for C2C Online Marketplace Listings: Multi-Label Classification and Entity Extraction for Identifying Potentially Illicit Ads", in Proc. of the LatinX in AI Research Workshop at NeurIPS 2025, 12/2025. [ bib | .pdf ]

Andrew Hamara, Greg Hamerly, Pablo Rivas, and Andrew C. Freeman, "Learning to Plan via Supervised Contrastive Learning and Strategic Interpolation: A Chess Case Study", in Proc. of The Second Workshop on Game AI Algorithms and Multi-Agent Learning (GAAMAL) at IJCAI 2025, 8/2025. [ bib | .pdf ]

Landon Bragg, Nathan Dorsey, Josh Prior, Ben Kim, John Ajit, Nate Willis, and Pablo Rivas, "Robust DDoS-Attack Classification with 3D CNNs Against Adversarial Methods", in Proc. of the 29th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV'25), in The 2025 World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE'25), 7/2025. [ bib |  .pdf ]

Caleb Gates, Patrick Moorhead, Jayden Ferguson, Omar Darwish, Conner Stallman, Pablo Rivas, and Paapa Quansah, "Near Real-Time Dust Aerosol Detection with 3D Convolutional Neural Networks on MODIS Data", in Proc. of the 29th International Conference on Image Processing, Computer Vision, & Pattern Recognition (IPCV'25), in The 2025 World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE'25), 7/2025. [ bib | .pdf ]

Mia Gortney, Garret Parker, Patrick Harris, Austin Huizinga, Alejandro Rodriguez Perez, Ernesto Quevedo Caballero, Kor Sooksatra, Tomas Cerny, Pablo Rivas, Bikram Khanal, Maisha Binte Rashid, and Jie Ren, "Visualizing Human Trafficking and Criminal Networks: A Systematic Mapping Study", in Proc. of the 24th International Conference on Information & Knowledge Engineering (IKE'25), in The 2025 World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE'25), July 21–24, 2025, Las Vegas, NV, USA. [ bib | .pdf ]

Abanisenioluwa Orojo, Bikram Khanal, Emmanuelli El-Mahmoud, Joseph Yu, Maisha Binte Rashid, Paapa Quansah, Sri Manjusha Tella, Tianqi (Kirk) Ding, Xiang Fang, Pablo Rivas, and Maryam Samami, "Baylor Environmental AI Research System (BEARS): An Agentic AI Project to Combat Climate Change", in Proc. of the 27th International Conference on Artificial Intelligence (ICAI'25), in The 2025 World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE'25), July 21–24, 2025, Las Vegas, NV, USA. [ bib | .pdf ]

Pablo Rivas and Donald R. Schwartz, "Designing Multi-Objective CNN Architectures for SQL Query Modeling with Evolution Strategies", in Proc. of the 27th International Conference on Artificial Intelligence (ICAI'25), in The 2025 World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE'25), July 21–24, 2025, Las Vegas, NV, USA. [ bib | .pdf ]

Pablo Rivas and Donald R. Schwartz, "Explainable AI for SQL Grading: A Practical Approach with Multi-task CNNs", in Artificial Intelligence and Applications, CSCE 2024, Communications in Computer and Information Science, vol. 2252, Springer. 5/2025. [ bib | .pdf ]

Kyle Hoang and Pablo Rivas, "Semantic Representation of Musical Identity: AI-Driven Cover Image Generation from Lyrics", in Proc. of AIR-RES 2025: The 2025 International Conference on the AI Revolution: Research, Ethics, and Society, April 14–16, 2025, Las Vegas, USA. [ bib | .pdf ]

Tianqi (Kirk) Ding, Dawei Xiang, Pablo Rivas, and Liang Dong, "Neural Pruning for 3D Scene Reconstruction: Efficient NeRF Acceleration", in Proc. of AIR-RES 2025: The 2025 International Conference on the AI Revolution: Research, Ethics, and Society, April 14–16, 2025, Las Vegas, USA. [ bib | .pdf ]

Xiang Fang and Pablo Rivas, "Comparative Study of Single-Stage vs. Two-Stage Detectors for ASL Gesture Recognition", in Proc. of AIR-RES 2025: The 2025 International Conference on the AI Revolution: Research, Ethics, and Society, April 14–16, 2025, Las Vegas, USA. [ bib | .pdf ]

Adriana García Aguirre, Pablo Rivas, and Liang Sun, "Cybersecurity Policy Clustering with LLM-Based Embeddings and Dimensionality Reduction", in Proc. of AIR-RES 2025: The 2025 International Conference on the AI Revolution: Research, Ethics, and Society, April 14–16, 2025, Las Vegas, USA. [ bib | .pdf ]

Michael Okonkwo and Pablo Rivas, "Assessing the Efficacy of DinoV2-Based Embeddings in Clustering Visual Data from C2C Marketplaces", in Proc. of AIR-RES 2025: The 2025 International Conference on the AI Revolution: Research, Ethics, and Society, April 14–16, 2025, Las Vegas, USA. [ bib | .pdf ]

Warren Huang and Pablo Rivas, "The New Regulatory Paradigm: IEEE Std 7003 and Its Impact on Bias Management in Autonomous Intelligent Systems", in Proc. of AIR-RES 2025: The 2025 International Conference on the AI Revolution: Research, Ethics, and Society, April 14–16, 2025, Las Vegas, USA. [ bib | .pdf ]

Cameron Armijo and Pablo Rivas, "Exploring Visual Embedding Spaces Induced by Vision Transformers for Online Auto Parts Marketplaces", in Proc. of AAAI 2025 Workshop on AI for Social Impact – Bridging Innovations in Finance, Social Media, and Crime Prevention at The 39th Annual AAAI Conference on Artificial Intelligence, 2/2025. [ bib | .pdf ]

Maisha Binte Rashid and Pablo Rivas, "A Framework for Evaluating Vision-Language Model Safety: Building Trust in AI for Public Sector Applications", in Proc. of AAAI 2025 Workshop on AI for Public Missions at The 39th Annual AAAI Conference on Artificial Intelligence, 2/2025. [ bib | .pdf ]

Tonni Das Jui and Pablo Rivas, " Analyzing Insurance Cost Estimation: A Supervised Regression Approach ", in 11th Annual Conference on Computational Science and Computational Intelligence (CSCI'24), 12/2024. [ bib |  .pdf ]

Patrick Harris, Mia Gortney, Amr S. Abdelfattah, Tomas Cerny, and Pablo Rivas, " Designing a System-Centered View to Microservices Using Service Dependency Graphs: Elaborating on 2D and 3D Visualization ", in 2024 4th International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), 11/2024, pp. 01-07, IEEE. [ bib |  .pdf ]

Books

Ziheng Sun, Nicoleta Cristea, and Pablo Rivas , " Artificial Intelligence in Earth Science: Best Practices and Fundamental Challenges." Publisher: Elsevier. 2023. [ buy ]

Pablo Rivas , " Deep Learning for Beginners: A beginner's guide to getting up and running with deep learning from scratch using Python." Publisher: Packt, 416 pages. 2020. [ bib |  buy ]

Grants

My research has been supported by more than $3.23M in external funding across federal, foundation, and industry sources. As PI, I lead the NSF IUCRC Phase I Center for Responsible AI and Governance (CRAIG) (NSF CISE–CNS Award 2515265, $510,814, 2025–2030), the Central Texas Cyber Program (DoEd Cyber Program Award P116Z230151, $1,500,000, 2023–2026), Schmidt Sciences Award G-23-66054 ($33,614, 2024–2026), NSF SaTC (Award 2210091, $314,284, 2022–2024), and the NSF IUCRC Planning Grant for the Center for Standards and Ethics in AI (CSEAI: https://cseai.center; NSF CISE–CNS Award 2136961, $19,996, 2022–2023), along with Google TinyML support (2020–2022). I have also contributed as a non-PI to major funded efforts, including an NSF MPS–CHE award (1905043, $80,499, 2021) and a KEEN/Kern Foundation program ($734,000, 2021).

“An Introduction to AI: Gifts and Gotchas of Machine Intelligence” — AI and the Church, George W. Truett Theological Seminary (Waco, TX), May 2025
“The Dual Faces of AI: Fostering Innovation while Fighting Misuse” — Belmont University Research Symposium (Keynote Speaker) (Nashville, TN), April 2024
“AI Orthopraxy: Walking the Talk of Trustworthy AI” — Enterprise Computing Community (Keynote Speaker) (Poughkeepsie, NY), June 2023
“Trustworthy AI with Adversarial Robustness” — LatinX in AI Workshop at NeurIPS (Keynote Speaker) (New Orleans, LA), November 2022
“Fairness and Adversarial Robustness in Deep Learning Models” — Baylor University, CSI 5010 Graduate Seminar (Waco, TX), September 2021
“Hacking Machine Learning Models with Generative Adversarial Attacks: Seeking Provable Robustness” — Baylor University, CSI 5010 Graduate Seminar (Waco, TX), November 2020
“Hands-on Unsupervised Deep Learning for Beginners” — Technical Workshop, Tapia Conference (Texas), September 2020
“Introduction to Quantum Machine Learning” — UNAM FES Acatlán (Mexico), September 2019
“Writing Advisor Project” — IBM Thomas J. Watson Research Center (Yorktown Heights, NY), September 2018
“Unsupervised Deep Learning with Stacked Autoencoders on Chameleon” — Argonne National Laboratory (Chicago, IL), September 2017
“The Multilayer Perceptron: An Introduction to Machine Learning” — Computer Society, Marist College (New York), November 2016
“Support Vector Machines in Computer Vision” — Computer Society, Marist College (New York), November 2015
 

Outstanding Scholarship Award - ECS Faculty and Staff Awards - Baylor University. 2024

Outstanding Contribution to NLP Award - ICAI 2024 - Detecting Hallucinations in Large Language Model Generation: A Token Probability Approach. 2024

1st Place Best Paper Award (Poster) - LXAI @ ICML 2023 - Gabor Filters as Initializers for Convolutional Neural Networks: A Study on Inductive Bias and Performance on Image Classification. 2023

2nd Place Best Paper Award - LXAI @ NAACL 2022 - Study of Question Answering on Legal Software Document using BERT based Models. 2022

Honorific Mention for Social Impact - LXAI @ NAACL 2022 - Distributed Text Representations Using Transformers for Noisy Written Language. 2022

1st Place Best Paper Award - LXAI @ ICML 2022 - Bottleneck-based Encoder-decoder Architecture (BEAR) for Learning Unbiased Consumer-to-Consumer Image Representations. 2022

Inducted to the Upsilon Pi Epsilon (UPE), the international honor society for the computing and information disciplines, 5/2021.

Inducted to the International Honor Society Eta Kappa Nu (HKN), for those individuals in excellent academic standing and outstanding professional achievement, 4/2011.

Recipient of the Research Excellence Award by Texas Tech University. 2009

NASA Graduate Research Program, Selected for a 10-week internship through the UMBC an Honors University in Maryland. 2009

Seal mothers care for deceased pups, exhibiting unique mammalian behavior in Antarctic predator species — The University of Rhode Island (November 2025): https://www.uri.edu/news/2025/11/seal-mothers-care-for-deceased-pups-exhibiting-unique-mammalian-behavior-in-antarctic-predator-species/

Possibilities, concerns rise as artificial intelligence breaks into health care — Baylor Lariat (December 2024): https://baylorlariat.com/2023/12/05/possibilities-concerns-rise-as-artificial-intelligence-breaks-into-health-care/

Collaboration for a Higher Purpose – Foundations for Flourishing — Q&A with Baylor’s Human Flourishing Researchers (October 2023): https://research.baylor.edu/foundations-flourishing

Baylor professors use AI to identify online listings that lead to criminal activity — CBS / KWTX News 10 (October 2022): https://tinyurl.com/p9dkzcbs

Meet Baylor’s expert on artificial intelligence and deep learning — Baylor Proud (September 2021): https://t.co/yGogsrsTk0

Pablo Rivas — Baylor Connections podcast, Season 4, Episode 412 (March 2021): https://www.baylor.edu/connections/index.php?id=977243

The Marist Mindset List — Marist Institutional News (June 2020): https://www.marist.edu/-/mindset-list-t-zurhellen

Do Ethics Apply to AI? — Marist Faculty News (September 2019): https://www.marist.edu/-/marist-news-do-ethics-apply-to-ai-

How your phone’s camera could help detect a rare cancer in kids — Upworthy (June 2016): http://www.upworthy.com/how-your-phones-camera-could-help-detect-a-rare-cancer-in-kids