> B.SC. SOFTWARE ENGINEERING :: INTELLIGENT_SYSTEMS

THE FULL-SPECTRUM ENGINEER.

My craft isn't limited to a single layer. I engineer the complete data journey—from optimizing bare-metal firmware at the silicon edge, through robust protocols, up to the neural networks that interpret the world. I don't just stack technologies; I unify them into coherent, intelligent systems.

user@kionit: ~/sys_intro.sh

// KERNEL_EXECUTION_TRACE :: PID_ROOT

> PID: 2025> MEM: LANGUAGE_MODULE

[ STATUS: INSTALLING ]

GERMAN LANGUAGE ACQUISITION

// 2025 – Present// LANGUAGE_MODULE

Integrating German vocabulary and syntax protocols to expand operational capabilities within the DACH region. Objective is to achieve professional working proficiency for local team integrations.

> PID: 2024> MEM: KIONIT-LABS

[ STATUS: COMPILING ]

EMBEDDED SYSTEMS & HOME LAB DEVELOPMENT

// 2024 – Present// HARDWARE_CORE

Establishing a comprehensive hardware laboratory for Edge AI, telemetry, and security auditing. Utilizing ESP32-S3 for machine learning inference (TinyML) and sensor fusion. Conducting Sub-GHz RF vulnerability assessments (CC1101, LoRa SX1278) and protocol reverse engineering via logic analyzers.

> PID: 2025> MEM: UNIVERSITY_OF_EUROPE

[ STATUS: RUNNING ]

B.SC. SOFTWARE ENGINEERING

// 2025 – Present// ACADEMIC_NODE

Focusing on software architecture, digital logic design, and core engineering principles. Currently establishing foundational knowledge in programming and building an AI ecosystem for software development.

// SYSTEM_CAPABILITIES :: PROFICIENCY_MAP

⌜⌝⌞⌟

// MODULE_01 :: EMBEDDED_CORE

ADDR: 0x80

> Microcontrollers & Edge AI (ESP32, S3, ARM)0xF2

> C / C++ Firmware Design0xE5

> LoRa / MQTT0xD8

> FPGA / Verilog0xCC

> RTOS & System Schedulers0xBF

// MODULE_02 :: BACKEND_OPS

ADDR: 0x81

> Python / AI Ecosystems0xE5

> SQL & NoSQL Databases0xCC

> Linux, Docker & SysAdmin0xCC

> Go & Rust (Systems Programming)0xA5

// MODULE_03 :: USER_INTERFACE

ADDR: 0x82

> Next.js / React0xE5

> TypeScript0xE0

> Tailwind CSS / UI Design 0xD8

> WebSockets & API Integration0x7F

// SYSTEM_ARCHITECTURE :: DATA_FLOW_DIAGRAM

Real-time data pipeline from edge sensors to cloud intelligence

Edge Sensor

C++ESP-IDFI2C

Acquiring telemetry from I2C bus at 100Hz polling rate.

sensor_read.cpp

void loop() {
  Serial.printf("RSSI:%d V:%0.2f",
    -64, 3.31);
}

Mesh Gateway

PythonMQTTLoRa

Aggregating LoRaWAN packets and bridging to MQTT broker.

mqtt_bridge.py

def on_msg(c, msg):
  id = 1047
  q_len = 3
  broker.forward(payload)

Inference API

Node.jsTensorFlow

Processing tensors for real-time anomaly detection.

ingest.ts

app.post('/ingest', async (req, res) =>
  res.json({
    ms: 42,
    conf: 0.94
  })
);

Live Dashboard

ReactWebSocket

Rendering real-time data stream at 60fps.

dashboard.tsx

useEffect(() => {
  socket.on('stream', d => {
    setState(d); // 60fps
  }); // ws:3
}, []);

Edge Sensor

C++ESP-IDFI2C

Acquiring telemetry from I2C bus at 100Hz polling rate.

sensor_read.cpp

void loop() {
  Serial.printf("RSSI:%d V:%0.2f",
    -64, 3.31);
}

Mesh Gateway

PythonMQTTLoRa

Aggregating LoRaWAN packets and bridging to MQTT broker.

mqtt_bridge.py

def on_msg(c, msg):
  id = 1047
  q_len = 3
  broker.forward(payload)

Inference API

Node.jsTensorFlow

Processing tensors for real-time anomaly detection.

ingest.ts

app.post('/ingest', async (req, res) =>
  res.json({
    ms: 42,
    conf: 0.94
  })
);

Live Dashboard

ReactWebSocket

Rendering real-time data stream at 60fps.

dashboard.tsx

useEffect(() => {
  socket.on('stream', d => {
    setState(d); // 60fps
  }); // ws:3
}, []);

// INSTALLED_MODULES :: SYSTEM_DIAGNOSTIC_LOG

[ 0x47RL ]::Certified Red Team Operations Management (CRTOM)::Red Team Leaders

[2026-02-13]>

[ 0x83BA ]::Network Fundamentals Training (CCNA ITN)::Bilisim Academy

[2026-02-09]>

[ 0x42ML ]::Machine Learning::Miuul

[2023-10-29]

>> ALL_SYSTEMS_NOMINAL // 3_MODULES_DETECTED

View All Projects