Eugene Wang

Hi, I'm Eugene, an AI researcher, an Android developer, and an autonomous vehicle engineer. My research interest is building efficient decentralized systems and Explainable Artificial Intelligence.

I completed my undergrad in Physics at the University of Waterloo and am doing a master's in Computer Engineering. I am currently in the job market seeking to join a vibrant team! Don't hesitate to check out my résumé and reach me at my email

Activity

2021	Submitted Manuscript "Candle Eggs with a Phone ..." to IEEE GHTC, will present in August 2021.
2020	Presented "Adapting a Container Infrastructure for AV Dev" at IEEE CCWC2021, Las Vegas, NV.
2018	Authored "Developing a process in architecting microservice infrastructure with Docker, Kubernetes, and Istio" for the client.
2017	Won Microsoft Image Cup, Canada Reginal Final for A CNN model to monitor Egg development moniter.

Publications

CCWC

Adapting a Container Infrastructure for Autonomous Vehicle Development

Y Wang, Q. Bao

In IEEE Cloud Computing Workshop and Conference, CCWC 2021

Abstract IEEE Arxiv Code

In the field of Autonomous Vehicle (AV) development, having a robust yet flexible infrastructure enables code to be continuously integrated and deployed, which in turn accelerates the rapid prototyping process. The platform-agnostic and scalable container infrastructure, often exploited by developers in the cloud domain, presents a viable solution addressing this need in AV development. Developers use tools such as Docker to build containers and Kubernetes to setup container networks. This paper presents a container infrastructure strategy for AV development, discusses the scenarios in which this strategy is useful and performs an analysis on container boundary overhead, and its impact on a Mix Critical System (MCS). An experiment was conducted to compare both operation runtime and communication delay of running a Gaussian Seidel Algorithm with I/O in four different environments: native OS, new container, existing container, and nested container. The comparison reveals that running in containers indeed adds a delay to signal response time, but behaves more deterministically and that nested container does not stack up delays but makes the process less deterministic. With these concerns in mind, the developers may be more informed when setting up the container infrastructure, and take full advantage of the new infrastructure while avoiding some common pitfalls.
GHTC

Candle Eggs with a Phone: An Explainable Symmetrical Model for Retail Farmers

Y. Wang, A. Siong

IEEE Global Humanitarian Technology Conference, GHTC 2021

Microsoft Imagine Cup, Canada Finalist 2017

Abstract pre-published manuscript

We present a low-cost solution to candle eggs for mid-to-low-income farmers in developing counties with an android app. This lets farmer use their phone’s embedded camera and flashlight, and A DIYed tube as light cocnentrator to shoot the image of half an egg with the other half being obstructed by the tube. The image is symmetrically filled and then placed through Hough transform, and then feed to a pre-trained model on a seven layer CNN network. The model then uses a feature by feature algorithm to provide the logic behind each detection. Our model, with the image of only half an egg can achieve as much as 82% percent accuracy. We offer our code, model, and raw dataset public.
Project

Developing a process in architecting microservice infrastructure with Docker, Kubernetes, and Istio

Y. Wang, D. Ma

CGI software development Periodical 2018

Abstract arXiv code

As an application usage grows, its owner scales up vertically by replacing old machines with more powerful ones. This methodology is expensive and leads to resource waste. In response to the business needs, internet giants have developed the microservice architecture, which lets developers divide up their application into smaller units that can be hosted on multiple machines, thus enabling horizontal scale up. We propose a triphasic incremental process to transform a traditional application into a microservice application that guarantees stability during the operation. Then we demonstrated such methodology in a prototype microservice application based on an existing monolithic application. First, the developer splits a monolithic application into atomic services and aggregated services. Second, these services are packaged, containerized, and then deployed on Kubernetes. During this stage, Istio is deployed on the Kubernetes cluster to establish pod level communications, delegate traffic flows and filter requests, and enable the autoscaler. Other external add-ons, such as database connections, are defined in service entry. In the last stage, we developed an algorithm guideline to minimize inter-service calls by compiling all needed calls into a list and perform one finalized call. Although it increases memory usage, it avoided the wait time incurred during interservice calls. We then investigated managing configurations using config maps, recommended a pipeline being developed to perform automatic rollover.