Distinct teaching and mentorship tracks across AI, entrepreneurship, and applied engineering.
teaching / mentorship / applied ai
Teaching
My teaching activity combines technical workshops, AI-focused teamwork, and research mentoring with a strong emphasis on project-based learning, practical implementation, and collaboration.
The work here covers:
- university and course instruction
- developer team-building projects and collaborative programs
- specialized workshops, seminars, and research mentorship
Practical instruction centered on implementation, experimentation, and team-based problem solving.
Teaching aligned with industrial AI, computer vision, research methods, and startup thinking.
university and course instruction
Course instruction has centered on helping students connect theory to implementation, especially in AI topics that benefit from live demos, code walkthroughs, and practical project work.
RISE Startup Commercialization-Based Entrepreneurship Bootcamp
Program focused on startup item development, business model refinement, expert mentoring, and business plan writing.
Deep Learning and AI Fundamentals
Covered neural networks, CNNs, RNNs, Transformers, optimization, and deployment-oriented thinking.
Computer Vision and Image Processing
Focused on OpenCV, object detection, segmentation, and industrial and medical imaging workflows.
Machine Learning for Industrial Applications
Introduced supervised and unsupervised learning methods with attention to predictive maintenance and process monitoring.
Python for Data Science and AI
Included Python, Pandas, Scikit-Learn, TensorFlow, and PyTorch for project-based AI learning.
developer team-building projects
These programs emphasized collaborative AI development, where participants learned by building systems together and translating technical concepts into real project outcomes.
Program Information
Collaborative developer team-building and AI project participation under the ICT Innovation Square program.
5th Cohort - Active Ingredient Prediction AI
Developed an AI model for predicting active ingredients based on SMILES chemical codes.
4th Cohort - Emergency Situation Detection
Worked on a video-based AI system for object detection and emergency recognition.
3rd Cohort - UAM Battery Diagnosis
Contributed to an AI model for diagnosing urban air mobility battery performance.
specialized workshops and seminars
Workshops and seminars have complemented formal teaching by exposing learners and collaborators to current technology trends, energy systems, and industry-facing innovation spaces.
Access to the Latest Technologies and Trends - BIXPO / GPVC 2021
Attended events connected to SWEET 2021, the Global Photovoltaic Conference, the International Green Car Exhibition, and the Climate Environment Industry Exhibition.
mentorship and research supervision
Mentorship has focused on guiding students through research direction, experimentation, technical writing, and presentation readiness across interdisciplinary AI topics.
Graduate and Undergraduate Research Supervision
Supported projects in industrial AI, medical imaging, intelligent automation systems, and research presentation development.
future teaching and research directions
Looking ahead, the teaching direction continues to move toward applied systems that connect AI theory with automation, robotics, and real deployment settings.
AI-Driven Industrial Automation
Future work is oriented toward smart factories, robotics, automated inspection systems, and practical AI deployment in industrial settings.