Tuong Q.
Phung
AI & Embedded Systems Engineer
Passionate about creating intelligent systems that bridge the gap between artificial intelligence and embedded hardware. Specializing in machine learning, computer vision, and IoT solutions.
About Me
I'm a passionate engineer specializing in embedded systems and artificial intelligence. With expertise in hardware design, firmware development, and machine learning, I create innovative solutions that bridge the gap between software and hardware. My work focuses on developing intelligent systems for IoT applications, computer vision implementations, and real-time embedded solutions.
Skills & Technologies
C/C++
Programming
Python
Programming
Verilog
Hardware
ROS2
Robotics
Cadence
EDA
FPGA
Hardware
TensorFlow
AI/ML
STM32
Embedded
Education, Training & Courses
Bachelor of Engineering – Mechatronic
Ho Chi Minh University of Technology
- •High Distinction in Advanced Mathematics I–II, Physics I–II, and core engineering.
- •Built an autonomous Arduino-based drone: sensor fusion, control algorithms, basic navigation.
Bachelor of Engineering – Mechatronic (Honours)
University of Technology Sydney (UTS)
- •Focus: embedded systems, digital design, and real-time systems.
- •Hands-on projects with FPGA/HDL, sensors, and modern C++ (concurrency, code quality).
- •Delivered an end-to-end IoT gas-detection system with real-time dashboarding.
Analog IC Design Trainee
Mentor: Dr. Huy Binh (Senior Analog Engineer, Apple, UK)
- •CMOS fundamentals: device physics, biasing, current mirrors
- •Op-amp topologies: folded/telescopic cascode, Miller compensation
- •Noise analysis: thermal/flicker noise, stability & phase margin
- •Layout: matching, parasitic extraction, Monte Carlo simulation
RF Design Trainee
Mentor: PM Doan Hung (Bosch Vietnam)
- •RF fundamentals: transmission lines, Smith chart, S-parameters
- •Matching networks: L-section, Pi/T-networks, broadband techniques
- •PCB design: microstrip/stripline, impedance control, parasitics
- •EMC/EMI: shielding, filtering, VNA calibration, measurement analysis
AIDE (MLOps & Data) – 6-Month Program
AIDE
- •Data Engineering: ETL/ELT pipelines, streaming (Kafka/Spark), data quality
- •MLOps: CI/CD for ML, Docker/Kubernetes, model versioning (MLflow)
- •Experiment tracking: hyperparameter optimization, A/B testing
- •Production: model deployment, monitoring, drift detection, retraining
Neural Signal Processing & Time-Frequency Methods
Specialized Program
- •EEG/ECG processing: STFT/wavelets, artifact removal
- •Spectral feature engineering and time-frequency analysis
- •Real-time signal inference and validation protocols
AIO (ML/DL Training) – 1-Year Program
AIO
- •First principles: gradients/normal equations, Bayes/likelihood, bias-variance
- •Classical ML: linear/logistic regression, SVM, trees/ensembles, regularization
- •DL fundamentals: networks from scratch, activations, normalization, optimizers
- •Advanced: Transformers, GNNs, RL agents, generative models (VAEs, flow-matching)
Advanced Digital Hardware Design (FPGA/SoC & High-Speed PCB)
Professional Track
- •FPGA/SoC: Zynq UltraScale+, Versal ACAP, HLS/C++ synthesis
- •RTL Design: SystemVerilog/UVM, timing closure, formal verification
- •High-Speed Interfaces: DDR4/DDR5, PCIe Gen4/5, Ethernet 100G
- •PCB Design: impedance control, signal integrity, mixed-signal integration
Projects
A comprehensive IoT system for environmental monitoring using embedded sensors, real-time data processing, and cloud integration. Features include temperature, humidity, and air quality monitoring with automated alerts.
Technologies:
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Get In Touch
I'm always interested in new opportunities and exciting projects. Let's work together to create something amazing!
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