I'm currently a R&D Engineering Co-Op (intern) at Infinera building things for the Firmware team with some awesome people. I am on track to graduate from University of Cincinnati after completing my B.S. in Computer Science (with Embeded Systems Concentration, and Maths minor) and M.S. with the Class of 2023, from College of Engineering and Applied Sciences :)
As an engineer, I enjoy bridging the gap between innovation and design — combining my technical knowledge with my keen eye for perfection to create valuable tools.
When I'm not working, I'm probably painting, listening to music, travelling around, or crossing off another item on my SCRUM board.
I joined UC in fall '18, as a CS student with a concentration on embedded systems and microfinance as my elective studies.
The amazing thing about UC is the Co-Op program that has helped me achieve the professional experience that is quite rare in the education demography i.e. a second-year student. I joined Infinera, a Silicon Valley telecom company, with the help of UC's Co-Op program and support from my advisors. Joining Infinera launched me forward by quite a bit in achieving my career goals because I did not just learn about embedded systems, but worked and delivered high priority projects related to such!
Having all these said, my journey was not all rainbows and unicorns, I had a super hard time transitioning into college life. The only thing I would change if I could go back to my initial freshman years would be to tell myself to stop buying unlimited meal plan from UC and use that money to buy more Chipotle XD (because food affects my mood quite a bit, no offense to UC's meal-plan).
I am planning on keeping focus narrow on embedded systems studies and keep learning algorithmic trading on my own- I usually trade forex, Megacap and Index equities. (Please refer to my resume for addition info on this)
A Machine Learning Model trained on American sign language Dataset to predict the letters or numbers from a picture of a hand doing a certain sign. With the given Quick Predictor python script, you can use a pretrained model to classify a given picture of a hand sign to predict what letter / number is actually signified.
A CLI ENCRYPTION Application, written in Rust, uses Honey Encryption Method to encrypt message. Digests the required string, text file, object with HASH and can verify a HASH with another string, text file, object. Currently Implementing Honey Encryption Method. Currently woring on the Machine Learning script to generate the Honeys.
A Machine Learning Model trained on American sign language Dataset using tensorflow nightly built, to predict the letters or numbers from a picture of a hand doing a certain sign.
A full stack CLI ENCRYPTION Application made with Rust [Encryptions available are DES and SHA] uses Honey Encryption Method to hash message/files/objects, and verify them. Uses a Deep Learning Model to generate the Honeys, using Natural Language Processing [LSTM].
ThingZone prototype used for user study conducted at School of IT, CECH, University of Cincinnati. This is an android app, in developement state for UC-research.
This program is a somewhat faithful recreation of chess. It allows two people to play a full game against each other. It provides a graphical representation of the board, as well as the ability to check that every move is legal and determine when each king is in check.
A game where player starts in an unknown map. Searches for three bombs, and deactivate them to aquire IDs. And lastly deactivates the main bomb to win the game.
🏆 Won a bet of Chipotle against my friend 🏆
This portfolio / personal website, designed and developed with a conscious effort to showcase my projects that I am currently working on. I did not develop this, I am not very skilled at web-dev, I just reused code. Thanks to Brittany Chiang for open-sourcing this portfolio website source code.