MinerAlert
MinerAlert
The University of Texas at El Paso (UTEP) and Universidad Autónoma de Ciudad Juárez (UACJ) have long shared a culture, the border and an interconnected economy. Now, researchers from both institutions are building a binational partnership focused on the future of artificial intelligence.
The collaboration, known as the Binational Research Network for Modern AI, was established in May 2026 through a U.S.-Mexico Research Collaboration initiative funded by UTEP. The project brings together faculty and students from both institutions to explore developments in AI while creating new opportunities for research, mentorship and student exchanges across the border.
The partnership stems from an academic connection between Martine Ceberio, Ph.D., professor of computer science and associate dean for people, culture and environment in UTEP's Miguel A. Loya College of Engineering, and José David Díaz Román, Ph.D., of UACJ.
The two researchers first connected when Ceberio hosted a UACJ doctoral student in her research lab, CR2G (Constraint Research and Reading Group), as part of UACJ's required external research internship program. After learning more about Díaz Román's work and reading several publications authored by him and his colleagues, Ceberio recognized significant overlap between their research interests and those of several UTEP faculty members.
“When we are so close geographically, it feels like a missed opportunity not to collaborate,” Ceberio said. “There is an opportunity to create synergy, add value to our research and, most importantly, create new opportunities for our students.”
That initial connection led Ceberio and Díaz Román, who now serve as co-leads of the collaboration, to pursue U.S.-Mexico Research Collaboration funding through UTEP. After receiving the award, the researchers began building a framework to expand research and student opportunities across both institutions.
The grant currently supports one UTEP student and one UACJ student as research assistants. A UACJ student also is expected to spend the spring semester at UTEP as a visiting researcher.
At the center of the partnership is a rapidly emerging area of AI research: Kolmogorov-Arnold Networks, or KANs.
KANs are a specialized type of neural network that differs from traditional deep-learning models by allowing components of the network to learn mathematical functions during training. Researchers believe the approach may lead to AI systems that are more efficient, more interpretable and easier to understand than conventional neural networks.
Researchers from both institutions see the collaboration as an opportunity to expand research experiences for students on both sides of the border. The researchers are investigating KANs from theoretical and applied perspectives, exploring fundamental mathematical questions while also examining practical applications in engineering, computing and science.
That work brings together researchers from both institutions with complementary areas of expertise. UTEP researchers involved in the project include Martine Ceberio, Ph.D.; Vladik Kreinovich, Ph.D.; Christoph Lauter, Ph.D.; and Marcelo Frías, Ph.D. UACJ counterparts’ researchers include José David Díaz Román, Ph.D.; Boris Jesús Mederos Madrazo, Ph.D.; and José Manuel Mejía Muñoz, Ph.D.
Kreinovich also presented research on propagating uncertainty through Kolmogorov-Arnold Networks as part of a broader exchange featuring work by researchers and students from both institutions. Presentations covered KAN optimization and high-performance computing, deep learning and federated learning, brain-computer interfaces, AI in medical diagnosis, intelligent decision-support systems, robotics and symbolic execution.
The research exchange, held as part of UACJ’s 32nd Semana de Ingeniería, also gave researchers and students from both institutions an opportunity to strengthen relationships beyond their individual presentations.
“Basically, we are building a research team,” Ceberio said. “The meeting allowed us to get to know each other better, build trust and better understand what each of our labs is working on. We hope that will lead to a more engaged and meaningful collaboration.”
The institutions plan to establish a cross-border co-mentoring system that will allow faculty members from both universities to advise students jointly. The recent meeting helped identify potential mentor-student matches and common research interests among participants.
Beginning in spring 2027, UTEP and UACJ plan to host an annual binational research meeting, expanding participation beyond the current research groups to bring together additional researchers from both institutions. The goal is to encourage greater collaboration, strengthen connections between research groups and create additional opportunities for students.