Antenna Design for the Internet of Things
The goal of this course project is to empower students with antenna design skills to meet the increasing demand for custom wireless internet of things (IoT) devices. The students will decide upon a given IoT application. The students will then use a conceptual CAD model for the IoT device and utilize numerical computer aided design tools (Ansys HFSS & Keysight ADS) to design a suitable antenna solution.
Supervisor: Prof. G. Shaker (Adjunct)
Email: gshaker@uwaterloo.ca
Antenna Measurements
The goal of this course project is to familiarize students with antenna concepts that affect the performance of wireless devices. The students will learn how to perform basic antenna measurements in an anechoic chamber. The students will then need to propose a setup that characterizes/demonstrates the properties of an antenna system and provide detailed material to explain these properties. These properties include (but are not limited to) impedance, efficiency, frequency of operation, bandwidth, gain, polarization, beam width, RCS, noise immunity, and data throughput.
Supervisor: Prof. G. Shaker (Adjunct)
Email: gshaker@uwaterloo.ca
Application of neural network or deep learning algorithms in pattern recognition
This project aims to build deep machine learning models (e.g. recurrent neural networks, transformer models, etc.) to perform experimental data analysis where tasks of classification and pattern recognition are performed.
Required knowledge & skills: Python, machine learning algorithms.
Supervisor: Prof. Na Young Kim
Email: nayoung.kim@uwaterloo.ca
Location: Remote/RAC-2101
Application of quantum and classical machine learning algorithms in real-life data analysis
This project aims to build quantum and classical deep machine learning models (e.g., recurrent neural networks, transformer models, etc.) to assess real-life big data, where tasks such as classification, anomaly detection, and pattern recognition are performed.
Required skills: Python, machine learning algorithms.
Supervisor: Prof. Na Young Kim
Email: nayoung.kim@uwaterloo.ca
Phone: 519-888-4567 x30481
Location: Remote/RAC-2101
Building a Radar System
The goal of this course project is to help students understand basic radar concepts. The course spans topics of applied electromagnetics, antennas, RF design, analog circuits, digital signal processing, machine learning, and artificial intelligence. Students will decide upon a radar application (whether for autonomous drones/robots/vehicles or in the general theme of sensing for healthcare). Students will then get to work towards building a simulation model of their own radar system.
Supervisor: Prof. G. Shaker (Adjunct)
Email: gshaker@uwaterloo.ca
Data Denoising and Preprocessing for Scientific Applications
This project aims to apply and adapt existing denoising algorithms to scientific datasets, such as medical or chemistry data. The goal is to improve data quality and prepare it for subsequent analysis in larger research pipelines. Students will start by using existing Python code for denoising (e.g., for 1D signals or 2D images) and are encouraged to explore alternative preprocessing methods to achieve higher-quality results. This project provides hands-on experience in data handling, preprocessing, and experimental validation within real scientific workflows.
Required knowledge & skills: Basic Python programming; script automation; familiarity with data processing or machine learning libraries; interest in scientific or medical data analysis.
Supervisor: Prof. Na Young Kim
Email: nayoung.kim@uwaterloo.ca
Phone: 519-888-4567 x30481
Location: Remote/RAC-2101
Development of high performance nanomaterial-based energy harvesting devices for self-powered applications
The objective of this project is to develop high performance energy harvesting devices based on novel nanomaterials, which can convert mechanical energy to electrical energy, for self-powered electronic and sensing applications. Working with a group of experienced postdoctoral fellow and graduate students, the student will be trained on nanomaterial synthesis, nanomaterial characterization, device microfabrication and characterization, data analysis and technical writing.
Required knowledge & skills: hands-on capability
Supervisor: Prof. Dayan Ban
Email: dban@uwaterloo.ca
Numerical Simulations of nanoelectronic devices
This project aims to perform numerical simulations of nanoelectronic devices based on nanomaterials, which will explain experimental device performance.
Required knowledge & skills: Semiconductor device physics
Supervisor: Prof. Na Young Kim
Email: nayoung.kim@uwaterloo.ca
Location: Remote/RAC-2101
Numerical Simulations of nanoelectronic devices
This project aims to perform numerical simulations of nanoelectronic devices based on nanomaterials, which will explain experimental device performance.
Required knowledge & skills: Semiconductor device physics
Supervisor: Prof. Na Young Kim
Email: nayoung.kim@uwaterloo.ca
Location: Remote/RAC-2101