I remember being a kid and seeing computers as a sort of sorcery. From school to play, it seemed like the common
denominator with all things "modern" was these mysterious machines. Yet no one I knew, from parents to teachers, could
explain how they worked. So whenever I thought about how clicking a button can change the pixels on a screen, all I
could say to myself was "Might as well be magic...". After years of wondering, I simply couldn't take it anymore. I had
to understand the magic. This brings us to today, where I just graduated with my BS in CS from UO in June of 2023. I'm pleased to say I
am beginning to understand.
My goal is to eventually obtain a job in the field of artificial intelligence, but at this point in my career, I would
be happy with any job that pushes me to keep learning and become a better programmer.
I decided to study CS in college because AI blew my mind. I took relevant math courses and AI/ML courses, and through that picked up skills like PyTorch, multivariable calculus, and linear algebra to better understand AI. My most elaborate personal projects; MountainAI and HungryAI, showcase these skills.
~5 years experience with web design front and backend that ranges from HTML, CSS, JS, to WordPress and PHP, and back to NodeJS, Angular2 and Sveltekit. Experience with MongoDB, Firebase, and GCP for database/deployment.
I have a great curiosity for Computer Architecture and Operating Systems. This paid off and I got a 4.0 GPA in those 2 classes. My experience is primarily with UNIX systems.
I learned how to use the Unity framework to build games. My experience here is broad and ranges from asset management to creating physics models with C#.
Good ol' Python. This was the language I was introduced to programming with, and I have ~6 years of experience with it. I have used a variety of its libraries and frameworks, most recently Selenium and FastAI.
UO's CS curriculum is C heavy, and specifically focuses on teaching C and C++. I also learned C# while making a game in Unity. I seem to have a knack for C because I have a 4.0 GPA in C related classes.
I graduate in June 2023, and following my graduation I will be available to work full time in or near Portland, Oregon. I am also open to remote positions. What I want most from my job is a stable work environment where I will be pushed to continue developing my skills and knowledge as a Computer Scientist.
Call/Text:
505-204-0976
Email:
afrench7@uoregon.edu
Alder French, 2023
Duck Simulator
- using the Unity framework and editor to design and test games
- writing code in C#, including physics formulas for weapons and movement as well as for game logic and design
- managing digital assets, including a small amount of editing 3d models in blender
- working in a team, including merging with Github and communicating to avoid conflicts. Fun times :)
NFTKEY / ETH Encrypt & Decrypt
- research and testing on Ethereum blockchain: confirmed ability to encrypt, send, and decrypt messages via transactions, NFTs, and accounts built in public/private keys
- distributed systems architecture, specifically the Ethereum blockchain
- writing and reading code in Solidity and JavaScript as these languages are used alot in the blockchain ecosystem
- Working with niche JavaScript libraries, specfically eth-crypto and web3js
- Networking, like JSON RPC calls and their related call/response semantics
MountainAI
- The AI image classification pipeline including: data collection (scraping), training AI models, and deployment to Web/Mobile
- Full Stack Development - Made website with Svelte Front end, FireBase (includes authentication) and GCP databases, and REST API with Flask to host AI and make inferences. Deployed on Firebase and GCP
- Python and some of its libraries like FastAI, Selenium, and Pytorch
- Web Scraping: most of my work for this project's AI model went into developing a functional bing image scraper that I have used to collect up to 75,000 photos per session
- Training AI models: learned the basics of FastAI and wrote a rudimentary script to train AI models given labelled training images
HungryAI
- PyTorch including making machine learning model architecture and training
- Dealing with large Github Repos: I copied a few from various research papers and pieced them together for my own uses.
- Jupyter Notebooks: Did machine learning coding and testing within Jupyter notebook, like most AI researchers do.
- General Adversarial Networks and Image classification: these were the types of models I used in the experiment
- Web Scraping: Had to scrape a bunch of images of food with my old Selenium web scraper
