Tiamiyu Afees Olamilekan is a researcher with a strong background in quantum computing and quantum information science (QIS). He holds a B.Sc. in Solid State Physics and an M.Sc. in Theoretical Physics from Obafemi Awolowo University, Ile-Ife, Nigeria. His undergraduate research focused on the design and construction of a cathode ray oscilloscope (CRO), while his M.Sc. research explored the quantization of damped harmonic oscillators using perturbation theory.

Currently, he is working on superconducting multi-qubit systems in cavity quantum electrodynamics (cQED), with research interests spanning quantum computing, quantum cryptography, and quantum communication. Tiamiyu is passionate about advancing the frontiers of quantum technologies and aims to make meaningful contributions to global quantum research efforts.

Holds a Ph.D. in Science and a Master's degree in Engineering from the Autonomous University of Baja California, Ensenada campus; a Master’s degree in Administration from the Autonomous University of Chihuahua; and a Bachelor's degree in Industrial Chemical Engineering from the University of Sonora.

Currently a Candidate of the National System of Researchers (SNI), member of the RIESS Network of TecNM and RAMSES, and a faculty member in the Department of Engineering.

Research areas: optimization, logistics and supply chain, metaheuristics and artificial intelligence; in the field of social sciences: gender equity and equality.

Dr. Prometeo Cortés completed his Master's and Doctoral studies at the Center for Computing Research, IPN, and is currently a professor-researcher at the Instituto Tecnológico de Tijuana, incorporated through the Researchers for Mexico SECIHTI Program, since 2017. Dr. Cortes's lines of research are the development of Intelligent Computing methods and techniques based on Machine Learning, Fuzzy Logic, Neural Networks, Evolutionary Computing and Meta-heuristics, applied to the control and manipulation of Robots under conditions of uncertainty. His scientific-academic production consists of a total of 49 scientific articles, of which 17 articles have been published in journals with a JCR index, 18 book chapters, 9 articles of scientific dissemination and 5 chapters for dissemination in books in publishers with scientific recognition. As a professor, I have taught 40 courses at the higher and graduate level, and he has supervised doctoral and master's degree theses.

I graduated with honors in Biomedical Engineering from the Tecnológico Nacional de México - Instituto Tecnológico de Tijuana (ITT - TecNM) in 2021. In 2022, I pursued a Master 's degree in Digital Systems at the Centro de Investigación y Desarrollo de Tecnología Digital - Instituto Politécnico Nacional (CITEDI - IPN), where I graduated with honors in August 2024. My thesis centered on developing hybrid classical-quantum methods for computer-aided diagnosis of spine fractures in medical images. Currently, I am continuing my research as a PhD student in Digital Systems at CITEDI - IPN, with a focus on machine learning, deep learning, high-performance computing, quantum computing, and quantum machine learning, particularly applied to medical image diagnosis.

Biography not available at the time of publication. Further details will be provided as soon as possible.

Héctor M. Guajardo holds a Master's degree in Computer Science and is currently pursuing a Ph.D. in the same field. His primary research interests focus on fuzzy logic systems and bio-inspired optimization algorithms, with an emphasis on integrating Type-1 and Type-2 fuzzy logic into nature-inspired metaheuristics.

He has authored three research book chapters:
• Dragonfly Algorithm for Benchmark Mathematical Functions Optimization, published in New Horizons for Fuzzy Logic, Neural Networks and Metaheuristics (2024).
• Comparative Study of Dragonfly and Firefly Algorithms with Type-1 and Type-2 Fuzzy Parameter Adaptation, included in the MICAI 2024 Workshops proceedings.
• Optimization of Routes of a Robot Using Bioinspired Algorithms (Springer, 2021)

In addition to his publications, he has actively participated in international conferences, Mexican International Conference on Artificial Intelligence MICAI 2024 and International Seminar on Intelligent Computing (ISCI) 2024 presenting contributions, which reflects his ongoing commitment to the advancement of hybrid intelligent systems.

Juan Humberto Sossa Azuela holds a PhD in Computer Science from the National Polytechnic Institute of Grenoble, France. He is a full-time professor at the National Polytechnic Institute and Director of the Center for Computing Research. He is an Emeritus Member of the National System of Researchers. He is a member of the Mexican Academy of Sciences and a member of the Academy of Engineering. He is also a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE) and the International Society for Neural Networks (INNS). He is a member of the Academy of Computing Machinery (ACM) and a Fellow of the Mexican Society of Artificial Intelligence (SMIA). In 2021, he was awarded the National Computing Prize by the Mexican Academy of Computing (AMEXCOMP). In 2023, he received the Research Award at the
National Polytechnic Institute in the area of basic research. In 2024, he received an Honorary Doctorate from the Technological Institute of Ecatepec. He is the author of five textbooks, 13 patents, 32 copyrights, and over 500 conference and journal papers. He has given over 560 invited talks. His research interests include Artificial Intelligence, Machine Learning, Artificial Neural Networks, Image Analysis, Pattern Recognition, Robotics, and Metaverses.

Jesús Franco is a Chemical Engineer from BUAP and a Master’s student in Digital Systems at CITEDI-IPN. His multidisciplinary background bridges materials science and AI: during his undergraduate studies, he worked on synthesizing silver nanostars, and now his research focuses on AI-driven advances in materials science, including property prediction in metallic glasses and FIB-SEM image processing of tantalum carbide using GANs. He has also explored generative quantum models.

Committed to conservation, he applies his technical skills to ecological challenges, such as graph-based identification of sea turtles. His goal is to push scientific boundaries by integrating AI, quantum computing, and signal processing to solve complex problems in materials innovation, biodiversity preservation, and beyond.

Biography not available at the time of publication. Further details will be provided as soon as possible.

Bachelor’s degree in Physics and Advanced Technology from the Universidad Autónoma del Estado de Hidalgo, currently pursuing a Master’s degree in Computer Science at the Center for Computing Research of the Instituto Politécnico Nacional. His main research focus lies in variational quantum algorithms applied to combinatorial optimization problems.

He has participated as a workshop instructor at the CORE 2024 conference, where he led the workshop “Algorithms on Quantum Computers.” Additionally, he has been part of the organizing committee for the science outreach event Qiskit Fall Fest 2024, and has participated in the quantum computing mentorship program of the Quantum Open Source Foundation.

Antonio Contreras is a biomedical engineer and data scientist specializing in artificial intelligence and quantum computing. With a strong background in machine learning, NLP, and computer vision, Antonio has worked on a wide range of AI solutions, from cloud-based deployments to hybrid quantum machine learning models. He has given workshops and mentored others in emerging technologies, contributing to research papers and developing proofs of concept across industries. Passionate about education and innovation, Antonio has taught at universities and schools in Mexico and has participated in international hackathons in Paris, focusing on AI agents and startup development, sharpening his skills in real-world, high-impact environments.

Dr. Domínguez Guerrero graduated in Electronic Engineering from the Instituto Tecnológico de Durango in 2009. He completed both his Master’s and Sc.D in Digital Systems Sciences at CITEDI, the Center for Research and Development of Digital Technology, part of the National Polytechnic Institute. His academic focus lies in multi-objective optimization using bio-inspired algorithms.

Since 2017, he has been a full-time professor at the Universidad Autónoma de Ciudad Juárez, where he teaches in the Computer Systems Engineering program. He has supervised a wide range of thesis projects on topics such as combinatorial optimization, convolutional neural networks, single-board computer systems, and object recognition in images, among others.

Juan Pablo Acuña holds a master's degree in Applied Statistical Methods. He specializes in using quantum computing and AI for research on HIV dynamics and antiretroviral therapy.

Kenia Picos is a full-time professor at CETYS Universidad at Escuela de Ingeniería Campus Tijuana. She received her PhD degree in 2017 from Instituto Politécnico Nacional at Centro de Investigación y Desarrollo de Tecnología Digital. She concluded a postdoctoral research in 3D pose estimation with artificial intelligence in Madrid Spain in 2018. Her current research interests include computer vision, object recognition, three-dimensional object tracking, pose estimation, and parallel computing with graphics processing units.

Mario Jara graduated with a Bachelor’s degree in Actuarial Science from the Universidad Autónoma de Nuevo León. He holds Master’s degrees in Artificial Intelligence from Universidad Tecmilenio and in Astrophysics from UANL. He is a PhD candidate in Engineering Physics at UANL. His research focuses on developing tools for AI applications in astrophysics, integrating dynamic hypernetworks, quantum–classical hybrid algorithms, and Bayesian optimization techniques for hyperparameter tuning in AI models applied to wavefront aberration correction and large‑scale data analysis. He contributes to the astrophysics community by authoring open‑source packages, leading workshops on computational methods, and forging partnerships between computational scientists and observational facilities. His work facilitates the adoption of AI‑driven approaches across modern astronomy.

I am a bioengineer graduated from the Autonomous University of Baja California, with a background in microbiology and biomedical engineering. I am currently employed as a high school teacher.

Since my undergraduate studies, I have maintained a strong interest in artificial intelligence, and for that reason I have taught myself as much as possible on the topic. After graduating, I decided to pursue a postgraduate degree focused on artificial intelligence and its applications in the medical field. I am enrolled in a master's program in engineering, where the goal is to develop an auxiliary method for early diagnosis of osteoporosis using convolutional neural networks.

I am passionate about the integration of artificial intelligence to assist healthcare professionals in providing more accurate and earlier diagnoses by identifying recognizable patterns in patients before their condition progresses. Early diagnosis is my goal, and I plan to continue working toward it in the future.

Dr. Óscar Castillo is a Professor and Researcher at the Tijuana Institute of Technology, where he leads the Hybrid Intelligent Systems research group. He holds a Doctor in Science degree from the Polish Academy of Sciences and is a Level 3 (Emeritus) member of Mexico’s National Research System. He currently serves as President of the Hispanic American Fuzzy Systems Association (HAFSA), Past President of IFSA, and Chair of the IEEE Computational Intelligence Society Mexican Chapter. His research focuses on Type-2 and Type-3 Fuzzy Logic, Fuzzy Control, and Hybrid Computational Intelligence. Dr. Castillo has authored over 1,200 publications, including 400 journal articles and 20 books, with an h-index of 100 and more than 33,500 citations. He has served as guest and associate editor for several international journals and was named a Highly Cited Researcher by Clarivate in 2017 and 2018. In 2019, he received Mexico’s National Award in Computer Science.

Dr. Patricia Melin is a Professor of Computer Science at the Tijuana Institute of Technology – TecNM since 1998, where she also serves as Director of the Graduate Program and leads the Hybrid Intelligent Systems research group. She holds a Doctor of Science degree from the Polish Academy of Sciences and is a Level III member of the Mexican National Research System (SNII). Dr. Melin has supervised over 100 graduate students and authored more than 1,100 publications, with over 25,000 citations and an h-index of 87 on Google Scholar. Recognized as a Highly Cited Researcher by Clarivate (2017, 2018), she has received awards such as the IFSA 2021, NAFIPS 2022 K. S. Fu Award, and the Lotfi A. Zadeh Memorial Award (2022, 2024). She is founding Chair of the IEEE CIS Mexico Chapter and Editor-in-Chief of Advances in Fuzzy Systems. Her research focuses on neural networks, fuzzy logic, and hybrid intelligent systems.

My name is Paul O Onoja, a quantum software developer passionate about building scalable and efficient quantum computing systems. Currently, I’m interning at QWorld, where I’m developing a framework for distributed quantum computing, focusing on realistic models for resource optimization across multiple quantum processors. My previous work at Qbraid involved improving quantum intermediate representations and integrating classical-quantum workflows. With a background in software engineering and research spanning quantum simulators and circuit optimization, I aim to contribute tools and ideas that make quantum computing more accessible and practical.

Ricardo Rioda Santiago Sanchez earned his degree in Computer Systems Engineering from Tecnológico Nacional de México – Instituto Tecnológico de Tijuana (ITT - TecNM) in 2024. He is pursuing a Master's in Engineering Sciences at the same institution. In 2019, he competed in the National Physics Olympiad (ONF).

In 2024, Ricardo participated in the Womanium Quantum Workshop, the Seminar on Artificial Intelligence and Quantum Computing, and NEO 2024, presenting research on “Multiclass Evaluation of Vision Transformers for Industrial Welding Defect Detection.”

In 2025, he attended the Numerical Methods in Quantum Information Science Summer School at the University of Massachusetts Amherst and SPIE Optics + Photonics in San Diego, California. He currently works in data science at ITJ Labs. His interests include mathematics, physics, quantum computing, and machine learning. Ricardo continues to deepen his expertise in AI and data analysis to solve real-world challenges.

Sandra S. Rosales holds a Master’s degree in Computer Science with honors from the Universidad Autónoma de Querétaro, and a Bachelor’s degree in Computer Science from the Universidad Autónoma Metropolitana, Iztapalapa campus (UAM-I). In 2020, she was awarded first place in master's-level research by the Consejo de Ciencia y Tecnología del Estado de Querétaro (CONCYTEQ). She is currently pursuing a Ph.D. at the Centro de Investigación y Desarrollo de Tecnología Digital of the Instituto Politécnico Nacional (CITEDI-IPN), where she is advancing her academic career.

Her research focuses on the design of algorithms that optimize the use of computational resources in both classical and quantum architectures. She analyzes, implements, and evaluates various algorithmic approaches to address complex problems, refining each solution according to the specific requirements of the system or application. Her primary interest lies in developing quantum algorithms that effectively leverage the capabilities of quantum computing.

I’m a Computer Engineer with over ten years of experience building software, leading teams, and growing through hands-on and collaborative work. I hold a Master’s in Engineering and Innovation from CETYS University. My journey has taught me that the most valuable systems are those that combine technical depth with purpose and usability. I’m currently researching how artificial intelligence, especially language models, can support financial analysis by connecting structured and unstructured data. This work reflects my broader interest in creating tools that make complexity more understandable and useful. I believe in mentorship, thoughtful leadership, and building things that matter. I strive to design systems that bring together human insight and machine precision to support better decisions and deeper understanding.

Seyi Tope Ogunji is an international conference speaker and researcher in emerging technologies, with a background in Electrical/Electronics Engineering. He graduated with honors, earning multiple academic awards, and holds a certification in quantum computing from the U.S.-based Coding School. Currently pursuing a PhD in Quantum Cryptography with AI at IPN’s CITEDI Centre in Mexico, he earned a cum laude master’s in digital systems through a federal scholarship. His research integrates AI and Cybersecurity with publications in Springer and Scopus-indexed journals. Seyi’s professional journey includes roles in automation at Procter & Gamble, where he trained in Germany and Egypt, and people management at Hayat Kimya. He also founded an AI education non-profit and a logistics company, combining corporate and academic experience to drive innovation.

Ulises Orozco-Rosas received the M.S. and Ph.D. degrees in digital systems from the Instituto Politécnico Nacional, Mexico, in 2014 and 2017, respectively. He has held a postdoctoral position. From 2017 to 2018, he was appointed at the Department of Computer Science, Universidad Rey Juan Carlos, Spain. He is currently an Associate Professor with the School of Engineering, CETYS Universidad, and a member of the National System of Researchers (SECIHTI-SNII). His research interests include machine learning, computational intelligence, parallel and heterogeneous computing, autonomous vehicles, and mobile robots. He has published over sixty papers in peer-reviewed journals, books, and conferences.

Norma Argueta is a technology professional with experience in database administration, project coordination, and data analysis. She holds a Bachelor’s degree in Informatics from the Universidad Autónoma de Baja California and a certification in Microsoft SQL Server administration. Currently, she is pursuing a Master’s in Engineering and Innovation at CETYS University.

In her professional work, Vanessa focuses on maintaining data accuracy, optimizing processes, and supporting clients through practical and reliable solutions. She has participated in projects that require both technical skills and clear communication, ensuring that information systems operate efficiently and meet organizational needs.

Her interest in cinematography and music reflects a curiosity for different ways of understanding and interpreting information. Vanessa approaches her work with a methodical perspective, aiming to contribute knowledge and practical experience in collaborative and academic environments.

Yahir Jasiel Soto Sánchez is a Software Test Automation Engineer at Dexcom / ITJ and is currently pursuing a degree in Computer Systems Engineering at the Instituto Tecnológico de Tijuana (ITT). He has participated in competitions such as the Solana-Tec Tijuana Hackathon, where his team won third place with a Web3 project focused on betting using blockchain technology and the Solana (SOL) cryptocurrency.

He is passionate about learning new technologies that enable him to grow professionally as a software engineer.