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🎓 Computer Engineering graduate focused on embedded systems, applied AI, and hardware–software integration.
🛠️ Core Technologies
💼 Featured Projects
- Languages: C, C++, Python, VHDL, SQL
- Embedded Platforms: Cortex-M0 (CubeIDE), ESP32 (ESP-IDF), FreeRTOS, Zephyr
- AI & ML: PyTorch, CNNs, Torch C++, embedded inference, signal-based feature extraction
- Build & Tooling: PyBind11, CMake, Docker, Conan, GitHub Actions, Make, GCC/MSVC
- Communication & Control: TCP/UDP, MQTT, serial protocols(I2C, UART,SPI,1-Wire, etc), interrupts (ISR), thread-safety, servers
- Focus Areas: C/C++ systems, embedded, AI systems, safety-critical, dependable design, automation, hardware–software co-design, vector-based retrieval (FAISS), hybrid packaging (C++/Python), DevOps
Due to the need to preserve strategic information until the patent process is fully regularized, the thesis project remains private and access is currently restricted.
Public disclosure will only be granted once all legal and procedural matters are resolved.
Cross-language C++/Python retrieval engine for modular vector processing and hybrid ML workflows.
Features embedding pipelines, FAISS search, PyBind11 bindings, and OpenMP-accelerated document operations, packed in reproducible manylinux wheels and CI-driven builds.
RTL module for PS/2 mouse decoding, written in VHDL and verified with functional testbenches and synthesis reports.
Includes finite state machine design, and full ASIC-oriented flow, with post-synthesis timing validation and Cadence toolchain support.
Loadable Kernel Module (LKM) enabling message queueing between user-space processes via a /dev/mq Character Device interface.
Implements per-process circular buffers, a control block registry, and spinlock-based synchronization for concurrent messaging.
Includes a C user-space client for interaction and was cross-compiled with Buildroot for embedded Linux systems.
This tool performs automated cryptanalysis of messages encrypted with the Vigenère cipher, a classical polyalphabetic substitution technique.
Designed for educational purposes, it showcases the application of frequency analysis and statistical inference to deduce the key and decrypt a ciphertext. Python-based cryptanalysis tool for the classical Vigenère cipher — developed with academic rigor and statistical methods.
“Firmware, networks, memory and learning — it’s all part of the same reliability surface.”
🧩 I approach systems as unified layers — from bits to models.
📐 I aim for technical rigor, clean documentation, and reusable architecture.
🌍 I’m constantly exploring intersections between AI, embedded design, and resilient engineering.