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Hire Dr. Martha Ivon C.

Spain

USD 20 /hr

PhD in AI, senior researcher in Explainable Machine Learning for Healthcare, Proteomics & Industrial Applications.

Profile Summary

I have accumulated more than twenty-five years of professional experience in teaching, research, and technological innovation, primarily in the fields of artificial intelligence, data science, and applied mathematics. My professional path has consistently combined academic research, higher education, and applied AI development within the framework of Industry 4.0 and STEAM education. Since 2019, I have served as an Associate Professor in the Department of Computer Science at the Universitat Politècnica de Catalunya (UPC), teaching undergraduate courses in Foundations of Computing, Object-Oriented Programming, Data Structures and Algorithms, and Human-Computer Interaction and Interface Design. I have also supervised final degree projects related to machine learning, robotics, and data analytics, and actively participated in the continuous improvement of the STEAM teaching program. My teaching combines theoretical foundations with practical applications of computational intelligence and software engineering. Previously, from 2011 to 2017, I completed my Ph.D. in Artificial Intelligence at UPC, where I conducted advanced research on the use of machine learning and manifold learning methods for the computational analysis of G-protein-coupled receptor sequences applied to bioinformatics and pharmacoproteomics. During this stage, I participated in several national and European research projects (KAPPA-AIM, ERA-NET NEURON, and others), publishing in BMC Bioinformatics, Genomics and Computational Biology, and IEEE BHI Conference Proceedings. My doctoral work contributed to data-driven discovery for neuropharmacological targets, applying probabilistic modeling and intelligent data analysis. Parallel to my university career, I have held a permanent teaching position in Mathematics and Technology with the Department of Education of the Government of Catalonia since 2004, where I have led educational innovation projects involving robotics, programming, and 3D printing. As head of the CTM (Mathematics-Technology-Science) area, I have designed and implemented curricular programs that integrate computational thinking and AI in secondary education, including participation in the European Erasmus+ STEAMTeach project. I have been an invited speaker and contributor at several international conferences on educational robotics and AI-based learning methodologies, and have co-authored more than 20 academic and educational publications in these domains (RiE, ICAS, ROSETA, EDULEARN, AIHUB CSIC). Since 2020, I am the CEO and founder of Intelligent Battery Analytics (IBA), a technology startup that applies artificial intelligence, big-data analytics, and machine learning to improve battery health monitoring and predictive maintenance systems for electric mobility and energy storage. Under my leadership, IBA has developed advanced models for the data-driven characterization and optimization of lithium-ion batteries, bridging the gap between academic AI research and industrial applications. My combined background in computational intelligence research, engineering education, and applied AI entrepreneurship demonstrates sustained professional maturity and leadership in technological innovation. I actively promote interdisciplinary collaboration between academia, industry, and education to foster responsible and inclusive AI development. Core Competencies: Artificial Intelligence • Machine Learning • Data Analytics • Computational Modeling • Software Development • STEM/STEAM Education • Research and Innovation Management • Project Supervision • Industry 4.0 Applications • Entrepreneurship

Subject Matter Expertise

• ☆ Data Analysis
• ☆ Machine Learning
• ☆ Python
• ☆ Matlab

Services

• Data & AI

Data & AI Predictive Modeling, Statistical Analysis, Algorithm Design-ML, Data Visualization, Big Data Analytics

Work Experience

Assistant Professor - AI senior researcher

Universitat Politècnica de Catalunya

September 2017 - Present

Academic staff in Discrete Maths and Statistics

ENTI - Universitat de Barcelona

September 2017 - June 2018

Education

PhD en Inteligencia Artificial y Ciencias de la Computación (Computer Science)

Universitat Politècnica de Catalunya

October 2014 - July 2017

Licenciada en Matemáticas

Universidad de la Habana

September 1990 - July 1996

Certifications

• Certification details not provided.

Publications

CONFERENCE PAPER

König, C., Cardenas, M.I., Copado, P.J., Vellido, A.(2026). Fairness-Aware Machine Learning for Biomedical Prediction: Evaluating and Correcting Bias in Gallstone Diagnosis Models . Lecture Notes in Computer Science. 16148 LNBI. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 59-73.

Sánchez-Cárdenas, I.-T., Cárdenas, M.-I.(2026). Predicting Obesity-Related Phenotypes from the Human Gut Microbiome Using Machine Learning . Lecture Notes in Computer Science. 16148 LNBI. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 527-539.

Cardenas, M.I., Copado, P.J., König, C.(2026). Uncovering Cardiac Risk Patterns: Visualization and Interpretation via Probabilistic Topographic Mapping . Lecture Notes in Computer Science. 16148 LNBI. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 29-44.

Molas, L., Cardenas, M.-I.(2024). Revolutionizing Traffic Management: AI-Driven Micro:bit Integration for Real-Time Traffic Control . Lecture Notes in Networks and Systems. 1084 LNNS. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 379-390.

Cardenas, M.-I., Molas, L., Puertas, E.(2023). Artificial Intelligence with Micro:Bit in the Classroom . Lecture Notes in Networks and Systems. 747 LNNS. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 337-350.

Cárdenas, M.I., Vellido, A., Giraldo, J.(2016). Visual exploratory assessment of class C GPCR extracellular domains discrimination capabilities . Advances in Intelligent Systems and Computing. 477. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 31-39.

Cárdenas, M.-I., Vellido, A., Giraldo, J.(2014). Manifold learning visualization of Metabotropic glutamate receptors . Frontiers in Artificial Intelligence and Applications. 269. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 269-272.

Cardenas, M.-I., Vellido, A., Giraldo, J.(2014). Visual interpretation of class C GPCR subtype overlapping from the nonlinear mapping of transformed primary sequences . 2014 IEEE EMBS International Conference on Biomedical and Health Informatics Bhi 2014. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 764-767.

Cárdenas, M.I., Vellido, A., Olier, I., Rovira, X., Giraldo, J.(2012). Complementing Kernel-based visualization of protein sequences with their phylogenetic tree . Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics. 7548 LNBI. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 136-149.

Vellido, A., Cárdenas, M.I., Olier, I., Rovira, X., Giraldo, J.(2011). A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences . Esann 2011 19th European Symposium on Artificial Neural Networks. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 233-238.

Vellido, A., Cárdenas, M.I., Olier, I., Rovira, X., Giraldo, J.(2010). A probabilistic approach to the visual exploration of G Protein-Coupled Receptor sequences . Esann 2011 Proceedings 19th European Symposium on Artificial Neural Networks Computational Intelligence and Machine Learning. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 233-238.

JOURNAL ARTICLE

König, C., Cárdenas, M.I., Giraldo, J., Alquézar, R., Vellido, A.(2015). Label noise in subtype discrimination of class C G protein-coupled receptors: A systematic approach to the analysis of classification errors . BMC Bioinformatics. 16. (1).

BOOK CHAPTER

Cárdenas, M.-I., Olier, I., Vellido, A., Rovira, X., Giraldo, J.(2013). Kernel generative topographic mapping of protein sequences . Bioinformatics Concepts Methodologies Tools and Applications. 2. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 817-830.

Cárdenas, M.-I., Vellido, A., Olier, I., Rovira, X., Giraldo, J.(2012). Kernel generative topographic mapping of protein sequences . Medical Applications of Intelligent Data Analysis Research Advancements. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 195-208.