Gabriel Blanco
Computer Engineering Student
UNAM Computer Engineering student focused on data analysis, AI, and system development.
Skilled in Python, SQL, and Java, with experience in technical support, teaching, and explaining complex
ideas in a clear and practical way.
Currently based in CDMX.
Experience
- Analyzed a real-world telecommunications recovery challenge for Zain Sudan, focused on restoring USSD recharge services after the loss of key charging, billing, and USSD infrastructure.
- Proposed a phased cloud-based recovery strategy, prioritizing low cost, fast deployment, and high availability, starting with a minimum viable solution while leaving a clear path for future improvements.
- Evaluated technical trade-offs related to cost, latency, deployment speed, availability, and total cost of ownership, justifying which solutions should be implemented or discarded.
- Led workshops and hands-on sessions focused on urban mobility, safe cycling techniques, and the promotion of active transportation.
- Worked with groups of different ages and skill levels, strengthening my communication, instruction, and public engagement skills.
- Designed and taught an intermediate Python course focused on data processing and visualization.
- Guided students through hands-on projects using NumPy and Matplotlib, receiving excellent feedback for clarity and practical examples.
- Provided hardware and software troubleshooting support for university computer labs.
- Assisted students and faculty with technical issues, managed software installations, and helped ensure the smooth daily operation of IT infrastructure.
Projects
Implemented A* and IDA* algorithms with Manhattan Distance and Linear Conflict heuristics to efficiently compute optimal solutions for 8, 15, and 24-tile puzzles, reducing node expansion and memory usage.
Developed a Battleship simulation framework to compare AI strategies, implementing a Hunter AI using checkerboard parity and greedy search that outperforms random models in target detection and elimination.
Developed a complete compiler and stack-based virtual machine for a custom mini-language. Features include lexical/syntactic analysis, semantic validation, intermediate code optimization, and support for recursion and control structures.
A real-time fleet monitoring and arrival-time prediction system for the Metrobús network using GTFS data, geospatial processing, and XGBoost machine learning.
A fully automated, weather-responsive retractable roof system designed in VHDL and deployed on an Intel MAX 10 DE10-Lite FPGA. It processes real-time environmental data to control a DC motor via an H-Bridge.
Skills
Contact
Let's talk
I’m currently looking for an internship where I can apply my skills, keep learning, and grow while finishing the final semesters of my degree. If you think I’d be a good fit for your team, feel free to reach out. My inbox is open!