Mr. Kai-Chih Chang has garnered extensive professional experience throughout his academic career. As a Graduate Research Assistant at the UT Austin Center for Identity from April 2017 to May 2025, he utilized Python to process datasets from over 6,000 media news reports of identity theft, built a graphical model using Java and JavaScript to visualize large-scale datasets, and ran simulations with a Bayesian Network model to answer research questions on identity theft. Additionally, he served as a Software Engineer for the Privacy Preserve Contact Tracing App in collaboration with UT Austin and Verizon from June 2020 to December 2021. In this role, he implemented the graphical user interface (GUI) for Android and iOS versions of the app using C# on Xamarin, developed the backend system with AWS and C#, and collaborated with team members using GitHub for version control. His work experience showcases his proficiency in software development, data processing, and collaborative project management.
Research Interests:
Mr. Kai-Chih Chang’s research interests encompass a broad spectrum of topics within the realm of electrical and computer engineering. His primary focus lies in the fields of machine learning and data mining, where he explores advanced algorithms and their applications. Additionally, he has a keen interest in parallel programming and deep learning, investigating their potential to enhance computational efficiency and performance. Mr. Chang is also dedicated to mobile computing and web development, leveraging technologies such as PET, TensorFlow, and Unity to create innovative solutions. His research is further complemented by his expertise in distributed systems and the utilization of platforms like GitHub and Linux, reflecting his commitment to advancing technology and solving complex engineering challenges.
Skills:
Mr. Kai-Chih Chang possesses a robust set of technical skills that span across various programming languages, technologies, and frameworks. His proficiency includes languages such as Python, Scikit-Learn, C♯, HTML/CSS, JavaScript, MySQL, and RStudio. He has honed his expertise in key areas such as machine learning, data mining, parallel programming, deep learning, mobile computing, and web development. Additionally, Mr. Chang is adept with technologies and frameworks including PET, TensorFlow, Unity, GitHub, Linux, Shell Script, Cluster Computer, and Distributed Systems. His diverse skill set enables him to tackle complex engineering problems and develop innovative technological solutions.
Publications: