Control & Embedded Systems (CES)

Vision

Trains our students to be future leaders in

todays fast-changing intelligent world.

Mission

• Lets students be experts in new technologies such as AI, big data, IoT, and blockchain.
• Practices student to have experience in self-control/self-decision devices & systems such as wearable devices, network sensors, autonomous vehicles, smart robots, smart factory, smart farms, and smart grid.
• Trains students to be lifelong self-learners.

Compulsory Elective Courses
Students must pass at least two of these courses.

• 2102500* Linear Algebra for Electrical Engineering (1 Credits)
• 2102501* Random Processes for Electrical Engineering (2 Credits)
• 2102504   Introduction to Mathematical Analysis (3 Credits)
• 2102508* Optimization Concepts and Applications (1 Credits)
• 2102509* Introduction to Optimization Techniques (2 Credits)
• 2102510* Linear Programming (1 Credits)
• 2102511* Optimization Methods for Engineering and Machine Learning(2 Credits)
• 2102518* Neural Networks and Deep Learning (1 Credits)
• 2102519* Reinforcement Learning and Applications (1 Credits)
• 2102521* System Identification (2 Credits)
• 2102523* Estimation Theory (2 Credits)
• 2102535* Nonlinear Control Systems (3 Credits)
• 2102537   Glocal Control System (3 Credits)
• 2102541   IoT Fundamentals (3 Credits)
• 2102542* Digital Circuit Design (2 Credits)
• 2102544   Advanced Embedded Systems (3 Credits)
• 2102545   Digital Integrated Circuits (3 Credits)
• 2102547* Analog Integrated Circuits (2 Credits)
• 2102570* Introduction to Computer Vision (2 Credits)
• 2102575   Statistical Inference and Modeling (3 Credits)
• 2102587* Sensor Technology and Applications (3 Credits)
• 2102635   Control System Theory (3 Credits)
• 2102637   Multivariable Control System (3 Credits)

Examples of Two Elective Compulsory Courses

Smart Things

2102541 IoT Fundamentals
2102544 Advanced Embedded System

Smart Robots

2102541 IoT Fundamentals
2103535 Mechatronics

Smart Control

2102541 IoT Fundamentals
2102635 Control System Theory

IC Design

2102545 Digital IC Design
2102546 Analog IC Design

Smart Thinks

2102541 IoT Fundamentals
2110654 Artificial Intelligence

Factory 4.0

2102544 Advanced Embedded System
2103530 Industrial Robots

Smart Decision

2102635 Control System Theory
2110743 Machine Learning

Systems & Control

2102505 Intro to Optimization
2102635 Control System Theory

IoT & Big Data

Professor in the Cluster	Research Interests
David Banjerdpongchai [DBP]	Industrial Automation, Advanced process control, Convex optimization, Robust control design, Control Application to Flexible Robot Arm, Distillation Column, Boiler, HVAC System; Energy management system, Energy Efficiency, Load and RE Forecast
Watcharapong Khovidhungij [WKG]	Infinite-Dimensional Control System, Nonlinear Control Systems
Thavatchai Tayjasanant [TTN]	Power Quality Analysis, Power Quality Impacts of Distributed Generations and Smart Grid, Power quality data analytics, Smart Road Lighting, Horticultural Lighting, Human Centric Lighting, Intelligent lighting control
Chaodit Aswakul [CAK]	Reinforcement Learning in Road and Telecommunication Network Applications, Vehicular Mobility Classification, Network Traffic Anomaly Detection, Machine Learning in Building Energy Management System Data and Mobile Telecommunication Network Data with Differential Privacy Protection, Network Security by Software-Defined Networking, Traffic Engineering Optimisation in Wireless Mesh Network, Network Function Virtualisation in Container Orchestration Cloud
Wanchalerm Pora [WPR]	Smart Devices, Smart Grid, Renewable Energy, EMS, AI, Weather Forecast, Mosquito Species Image Classification, Dangerous Object Detection in X-ray images
Chaiyachet Saivichit [CSC]	Communication Networking, Intelligent methods for Comm Networking, Graph Theoretical Networking, Telecom Economics, Network Reliability, Survivability and Trustworthiness
Jitkomut Songsiri [JSS]	system modelling, statistical learning, non-smooth optimization, sparse system identification, sparse optimization, solar power forecasting, brain connectivity, Granger causality, causality learning in time series
Suchin Arunsawatwong [SAR]	control systems design, stability analysis, delay systems, nonlinear control systems, fractional PID control, load frequency control, power system stabilizer design, numerical optimization.
Manop Wongsaisuwan [MWS]	Control Systems Theory, Robotics, Computer Application in Control Engineering, Machine Learning
Suree Pumrin [SPR]	Image processing, Computer Vision, Embedded Systems, Microscopy Image, Plant Phenotyping
Boonchuay Supmonchai [BSC]	Low-Power IC Designs and Applications, Biomedical Instrumentations, High-speed Communication Circuits, Performance Analysis of Networks
Napong Panitantum [NPT]	Analog and mixed signal IC design, Low-voltage/low-power amplifiers and data converters, RF communication circuits, IoT system developments and applications.
Suwit Kiravittaya [SKR]	Photonics, Electronics, Solar Cell, Photodetector, LED, Light Emitting Diode, Laser, Molecular Beam Epitaxy, Optical Properties, Semiconductor, Nanostructure, Quantum Technology, Quantum Sensing, Quantum Secure Communication, Quantum Computing