About Me

Hey I'm Oasys.

I love to create software and applicable projects to ease the world and make our society a better place. I love to work on projects with my friends and colleagues, and learn more everyday to improve what I can do.

As a Computer Science and Engineering undergraduate student at University of California, Santa Cruz, I am excited and eager to learn and experiment in AI, Machine Learning, and Data Science.

I boost my expertise in these areas working on several independent projects and going through internships and mentorships throughout my years in University.


University of California, Santa Cruz

Bachelor of Science in Computer Science
Honors/Societies: The National Society of Collegiate Scholars, Dean's List

Neural Networks and Deep Learning



Research Officer September 2018 - Present

Data Science Slugs
Computer Hope

Data Science Slugs (DSS) is an organization that was founded at University of California, Santa Cruz in the Fall of 2018 to gather diverse, like-minded people and those who are forward thinking people. Members of DSS realize the significance and impact Data Science has brought to our current generation and what kinds of benefits it will bring to the future development of human beings. This is the spirit of DSS, a forward-thinking and optimistic group of individuals gathered together to learn and bring on the next generation of Data Science technologies.


As a Research Officer of DSS, my primary responsibility is to find real-world opportunity for members and partnering with businesses for work opportunities. Networking and creating wonderful connections exposes members to important Data Science recruiters and personales, giving them a huge leap in this highly demanding field.

Furthermore, it's vitally important that members get something out of this organization and to prepare members for Data Science careers, and learning already established and up-to-date Data Science techniques is one of our primary goals in this organization. With coordinance with other organization officers, I design and develop technical workshops to cover various skill levels. Additionally, lecturing students on fundamental and advanced topics of Data Science, which includes statistics and machine learning, is another necessary input our organization offers to its members. We aren't just an organization for future optimists, we are an organization whose goals are to spread the awesome possibilities of Data Science through interactive learning.

I also manage and mentor several teams of students to plan and orchestrate machine learning projects, which brings me to the next topic of competitive programming.

Competitive Programming

As an organization filled with very diverse backgrounds but similar goals, it is important to train members on Data Science techniques used in everyday work. Setting up competitions of different level teams enables all members to participate in their respective categories effectively and fairly.

Visit our website to learn in detail what we do! http://datascienceslug.org

Software Engineer, Machine Learning Intern June 2019 - August 2019

PlanA.Earth GmbH
Computer Hope

Plan A’s mission is to empower companies to address the issues of climate change seamlessly by building tools that help them reduce their footprint. Plan A champions individuals, companies and communities who have taken a stance against the destruction of our planet. During my tenure at this organization, I had the opportunity to work on the amazing software as well as using Machine Learning techniques to work with Plan A's expansive custom datasets.

Software Engineering & Development

My software engineering and development role during my time at this company dealt with heading the company's software application, the Climate Change Explorer Toolkit, which was a tool that simplifies the computational and mathematical complexity of data analytics of the company's datasets through the intuitive use of visualization and user interaction. This ultimately allows company holders to make wise and efficient business decisions.

Technically speaking, I focused on full-stack development of the applcation in Python which the front-end uses PyQt, a cross-platform GUI toolkit based off Qt. The backend was also developed using Python. The backend functionality that I developed primarily dealt with REST services for cloud computing protocols to handle the company's huge frequently updated databases as well as data processing and distributions within the application. In other words, I designed and developed the architecture and implementation of the user-interface as well as the backend system, hooking up all API endpoints of the software, and my whole process was driven using Agile techniques. I also implemented, tested, and benchmarked key software improvements and performance optimizations, generating architecture, design, code and test documentation.

Another major backend functionality I dealt with was the implementation of all machine learning and statistical analysis used for intuitive analysis.

Machine Learning

My second role dealt with administering the machine learning aspect of the company's data driven and analytical approaches. Alongside that, I was also working with Data Scientists, planning and researching new ways to represent our current datasets, developing automation scripts to preprocess and clean big data. However, due to custom datasets being too distinct and unable to work with many machine learning and analytical algorithms, extensive research had to be made to design and implement additional functionalities to the algorithm itself.

All in all, the whole process worked seeminglessly and efficiently having a Data Scientist by my side, working together to troubleshoot the complexity of these situations. At this role, I learned that the ability to convey my implementations and rigorous statistical machine learning concepts and considerations to non-experts enables wider possibilities to develop long-lasting, effective empowerment in any situation.

Artificial Intelligence (AI) Developer Intern September 2017- June 2018

Applied Artificial Intelligence Initiative

The Applied Artificial Intelligence Initiative (AAII) brings together students (undergraduate and postgraduate), researchers (any flavor), faculty (any discipline), and members of Industry (primarily Silicon Valley) to lead the AI Revolution.

AAII's Mission is compromised of three goals

1) Promote interdisciplinary research at UCSC using machine learning and AI techniques.
2) Attract and train a diverse population of students (undergraduate and graduate) in AI.
3) Forge partnerships with Industry to enhance all of these activities.

For my first year in University, I had the wonderful opportunity to be exposed to the world of artificial intelligence when I was introduced to AAII. I went through an extensive training/mentorship, getting practical advice from graduate students on all sectors of AI. This expanded my interest and fascination with AI and the different benefits each sector can provide to the world, it motivated me to study more about this amazing subject.


During my tenure here at AAII, I went through an extensive training to learn about current techniques of machine/deep learning, computer vision, natural language processing, and robotics hardware. Throughout my processes, I primarily researched and experimented with many, different and diverse machine learning algorithms and techniques for automated anonymization, information extraction from unstructured documents, item categorization, product recognition and matching, attribute extraction, model interpretability, and survey weighting to name a few. During this time, I was able to develop a text mining pipeline in Python to analyze large unstructured datasets with Latent Dirichlet Allocation (LDA), sentiment analysis, and text classification. Along with these implementations, I also conducted and reported results from prototype projects that focus on the development of algorithms, methods, and tools as well as new scientific domains or applications areas in order to keep track of my progression.

Artificial Intelligence Development

I was also exposed to the wonders of Neural Networks and how different techniques of this topic allow for such advancement in our human history. For a good portion of my tenure, I conceptualized and built a facial expression and sentimental analysis tool to predict false statements. Some of my other implementations include a Region-based Convolutional Neural Network for theft detection using Raspberry Pi and Opencv and Convolutional Neural Network, Logistic Regression, KNN, and SVM to classify facial expressions using OpenCV


On the off chance that you might want to connect with me, be it for investigating innovation, business, or to simply say hello, don't hesitate to send me an email at oasysokubo@gmail.com

I have a LinkedIn page. Visit Oasys Okubo - LinkedIn for finding out more about my experiences, skills and projects.

Thank you for stopping by.

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