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Arslan Kenbayev

@arskenchik

HW/SWE engineering with experience in ML and Edge AI

KAIST EE student with a focus on hardware/software systems with AI integration/optimization for these systems

Open to

Startup collaborationFunding & grantsProject collaborationResearch collaborationJoining competitions & hackathons

Career

Experience: 3 years

Experience

Edge AI Engineer Intern

KAIST IC Lab

Jan 2026 — Present

Optimized compact on-device ML inference and built a synchronized 50 Hz IMU pipeline for Wear OS on Samsung Galaxy Watch 6.

• Optimized on-device ML inference latency and memory on Wear OS by deploying compact TFLite/LiteRT models under strict resource constraints. • Achieved zero-loss signal synchronization by engineering a 50 Hz IMU data pipeline with real-time buffering and normalization techniques. • Accelerated hardware-software integration by debugging tensor shapes, model loading, and multi-modal execution directly on Samsung Galaxy Watch 6.

Embedded Systems Engineer Intern

AXInvent

May 2025 — Mar 2026

Designed sensor schematics and PCB integrations, programmed C-based sensor nodes, and validated an edge-to-cloud IoT setup.

• Accelerated smart agriculture prototyping by designing Altium-based I2C/SPI/UART sensor schematics and integrating analog/digital PCB components with custom power regulation and signal conditioning. • Programmed the complete functional logic of master and slave nodes from scratch in C to initialize, isolate, and continuously stream real-time environmental sensor data. • Validated IoT sensor data integrity through oscilloscope/DMM bring-up, sensor debugging, and edge-to-cloud integration across Arduino Nano, Nvidia Jetson, and Raspberry Pi 4 via gRPC/HTTP/2.

Semiconductor Engineer Intern

KAIST IOEL Lab

May 2025 — Aug 2025

Fabricated CO2-derived OLED thin-film stacks and analyzed I-V sweeps to investigate lower turn-on voltage and higher luminance.

• Optimized organic OLED performance toward lower turn-on voltage and higher luminance by fabricating CO2-derived thin-film stacks and systematically analyzing forward-bias I-V sweep characterization data.

Automation Engineer Intern

AAEngineering

Jul 2024 — Sep 2024

Validated sensor integration and RF/IoT topology and prototyped automated control logic for gold ore segregation.

• Improved gold ore segregation readiness by validating sensor integration in SolidWorks, analyzing multi-node RF/IoT topology, and prototyping automated control logic.

Education

Bachelor of Science, Electrical Engineering

KAIST

2022 — 2027

Selected projects

AI for Robot Intelligence

Integrated a Gemini LLM action planner, fine-tuned YOLOv8-pose vision, and Nav2 A* path planning across Karto SLAM-mapped environments. Implemented physical manipulation using JAX-based optimization for inverse kinematics and an Implicit Q-Learning policy trained on teleoperation datasets.

Pipelined RISC-V CPU

Designed a synthesizable 5-stage RISC-V pipeline CPU with hazard detection and forwarding logic; achieved a 100% testbench pass rate and debugged waveform timing faults across pipeline stages.

Ultra-Low-Power Smartwatch Firmware

Developed embedded architecture and C device drivers with a DMM-verified system current draw of 85 μA. Implemented IMU duty cycling, step counting, OLED sleep, coordinated I2C sensor polling, and synchronized BLE GATT server firmware.

Capstone: Industrial Anomaly Detection

Trained an unsupervised autoencoder on ToyADMOS and MIMII acoustic datasets and used reconstruction-error thresholding for mechanical failure detection under real-world noise.

Skills

PCB DesignFirmware Dev (nRF5 SDK)Sensor IntegrationI2C/SPI/UART/BLEOscilloscope/DMMI-V CharacterizationROS2Nav2SLAMYOLOv8JAXReinforcement LearningInverse KinematicsLLM APIsC/C++PythonSystemVerilog/VerilogMATLABAltiumSolidWorks