I'm a Deep Learning Enthusiast
I am a Computer Science student at Case Western Reserve University. I love Machine Learning/ Deep Learning and the math behind it. I love spending my free time doing personal and group projects with my friends. I like to work in a team. I learn faster and much more when working in a team. As Napolean Hill said: "It is literally true that you can succeed best and quickest by helping others to succeed."
Name:
Minh Khoi Le
School Year
Junior
Major
Computer Science
School
Case Western Reserve University
Contact
khoileminh309@gmail.com
“There is Nothing More Practical Than A Good Theory”
- Kurt Lewin
Nuna Inc.
June 2021 - Current
Backend Engineer Intern
At Nuna, I built the explainability system for Nuna's Meaningful Match project serving 1 million Personal Care Providers(PCP) under different insurance. I also got to contribute to building the UI for the app as well.
JaTango Inc.
September 2020 - May 2021
Software Engineer Intern
At JaTango, I worked with Senior Software Engineer designing and live-stream and shopping cart system for Jatango’s new web application using ReactJS and NodeJS backend.
Center for Computational Imaging and Personalized Diagnostics (CCIPD)
September 2018 - Current
Undergraduate Research Assistant
At CCIPD, I worked with Dr. Anant Madabhushi and Dr. Cheng Lu on projects that utilize the predictive power of Deep Learning to solve problems in cancers and digital pathology. The work I did here will be described in the Projects section.
Case Western Reserve University
August 2017 - Current
BS - Computer Science (Specialization: Artificial Inteligent)
At Case Western Reserve University, most of the coursework is Java-based programming. During my time in here, I studied OOP, data structure, algorithm, artificial intelligent, etc. Here I also get to study the math behind all of them to further improve my analytic skill
Le Hong Phong High School for the Gifted
August 2014 - May 2017
High school(Speciality: Math)
At my high school, I studied with a schedule focus heavily on Mathematics. In my second year of high school, I realised I love to code and create things so I started to practice coding and participate in my school team for competitive programming.
Online Courses
August 2014 - Current
Online Courses (Sites: Coursera, Udemy, Udacity)
I learned Machine Learning from Andrew Ng's course on Coursera in my second year of high school. Since then, I took some other courses such as Statistics/Data Science on Udacity and Web development from Udemy in my spare time.
“An investment in knowledge always pays the best interest.”
- Benjamin Franklin
Python
Machine Learning
Java
Backend Engineer
Javascript
Data Analytics
C#
Computer Vision
HTML
Research
CSS
Frontend Development
MySQL
Database Engineering
“Without data, you're just another person with an opinion.”
- W. Edwards Deming
Haralick Texture feature of an image are some of the most important hand-crafted feature in Histology Image Analysis. However, the process of generating them tooks very long time and often bottleneck the research process in computational efficiency.
I with the help of Dr.Cheng Lu created a Deep Learning based method that utilize the power of Convolutional Neural Network(CNN) to mimic the process of calculation Haralick features. On CPU, our method is much faster compare to the traditional method. With Convolutional Neural Network, we also can paralelize the process which boost the run time even more when using GPU
I am finalizing the paper so I am not allowed to provide the method and result here yet.
Recurrence in cancer is the term when a person who is cured from cancer have cancer again in 10 years. Knowing if a patient will have cancer again will provide doctor more information to give correct treatment for cancer patients. However predicting recurrence in cancer now is still a complicated task for doctor to do which have a low accuracy.
I am working with Dr. Cheng Lu on developing a Deep Learning method for predicting recurrence in Oropharyngeal cancer using Whole Slide Image (WSI) and Tissue Microarrays (TMA).
Stock prices is a very interesting time series data to analyze because of its randomese but in a very organize way. Stock price not only behave based on the company performance but also based on the strategies of many Wall Street tradebot out there.
Me and 2 of my friend are working on a machine learning model to predict the stock price in the future. Currenly, we had a good enough result with the error rate of 0.5%. We are working on develope a web scrapper to get news data from online sources and use that data to improve our machine learning model.
After optimizing our model, we will create a bot to make financial investment out of it.
A website that I am developing to help people to match with each other based on their data to play various online games. This website also provides a platform to organize tournaments for amateur esport player.
This website will help spread the accessibility of esports to more players. Currently, I aim to provide it to my homecountry, Vietnam first.