IoT Automated Irrigation System (In progres)
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Summary
Designed an IoT automated irrigation system integrating various sensors and applying machine learning models for predictive scheduling.
Applied Mathematics student specializing in Cryptography, Coding Theory, and Security, with a solid foundation in field theory and Galois fields. My expertise bridges algorithm design, embedded systems, and full-stack development—from algebraic modeling to ESP32 firmware and web interfaces. Currently deepening my knowledge in applied algebra and error-correcting codes, with a strong interest in secure system design and post-quantum cryptography. Passionate about research and eager to contribute to advanced academic environments focused on mathematical rigor and real-world impact.
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Bachelor of Science
Applied Mathematics (Cryptography, Coding & Security)
Courses
Object-Oriented Programming (18/20)
Mathematical Foundations of Reinforcement Learning
Stochastic Processes
Field Theory and Galois Fields
Artificial Intelligence (17/20)
Stochastic Processes (13.98/20)
Algorithms and Data Structures (14.25/20)
...etc
Baccalaureate
Scientific Baccalaureate
Grade: 17.62/20
Native
Fluent
Proficient
Native
ESP32, RFID/NFC, Camera Modules, Sensor Integration, PCB design (KiCad).
Reinforcement Learning (Q-learning, MDPs), Regression, SVM, Kernel Methods, Neural Networks, Principle Component Analysis, Correspondence Analysis, BIRCH.
Python (OOP), Java, C, MATLAB, SageMath.
I2C, UART, SPI, ESP-NOW, LoRa, HTTP, WiFi, Serial Communication.
Git, Algorithm Implementation, System Optimization, OOP Design, ESP-IDF, JCDK, Arduino-IDE, ...etc.
Field Theory, Galois Theory, Group Theory, Linear Algebra, Combinatorics, Calculus, Topology, Numerical Analysis, Coding Theory, ...etc.
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Summary
Designed an IoT automated irrigation system integrating various sensors and applying machine learning models for predictive scheduling.