EXPERIENCE:- Served as the lead engineer for a small but cutting-edge computer vision project by a Fortune-100 robotics company [Python, NumPy, Numba, Tensorflow]- Created a decentralized application (DApp) for on-chain data storage, achieving over 400 paying users in the first 4 weeks- Experimented with generative art and related blockchain applications, including the minting and sale of over 2000 Tezos NFT editions to over 1000 unique collectors.- Wrote and deployed my own FA2 token (ERC-721 equivalent on Tezos) contract, minting a fungible token and distributing it through an "airdrop" to all collectors of my own NFT artwork- Building smart contracts to facilitate additional modes of interaction with this tokenDETAILS:I have 3 years of experience developing computer vision software for robotics and autonomous vehicles. This was done through "Photon Semantics" (a startup which I co-founded) in partnerships with major tech companies.I'm also eager to work on blockchain technology. In late 2016 I began to study DeFi, and I've been hooked ever since. My main smart contract languages are SmartPy (Tezos) and Solidity (Ethereum) as a majority of my expertise is in the Tezos and Ethereum blockchains. As a user I am further experienced with the popular EVM-based ecosystems, including Polygon, BSC, XDAI, Avalanche, Harmony, Optimism, and Arbitrum. I am level 6 on RabbitHole, and you can view my "on-chain resume" via my ENS name (RyanBranch.ETH).The languages and tools with which I am most experienced are listed below, in rough order.1. Python2. C++3. C# (incl. Unity)4. SmartPy5. JavaScript, React6. Solidity7. HTML/CSS8. C9. Flask10. JekyllI can confidently take on most development tasks in any of these.Please also feel free to reach out with projects outside of this list, as I am a fast learner and eager to maintain expertise.

Photon Semantics is a computer vision startup focused on the improvement of sensor performance in autonomous robotics. It was co-founded by myself and several others in 2017, from the research of Dr. Nicholas Kotov at the University of Michigan College of Engineering.

Specialized in creation and long-term maintenance of computer systems for production monitoring and software control in manufacturing environments.

- Co-founded "Photon Semantics", a computer vision startup out of the University of Michigan- Patented, as a team of 8 inventors, a novel approach to LIDAR sensor operation- Designed and built devices to automate data collection for the training and testing of Machine Learning algorithms- Measured and enhanced commercial sensor performance through custom Arduino electronics, CAD, and 3D printing- Worked for the startup from the day of its formation through the first $1,000,000 of commercial investmentEntrepreneurial Achievements:- Recipient of a 2017 Joint Toyota Research Institute University Project funding award- Awardee of the 2017 and 2018 MTRAC Advanced Transportation programs- Finalist in the 2018 Michigan Business Challenge- Competitor in the 2018 Rice Business Plan Competition, the world's foremost graduate-level student startup competition. For this invitation-only event, 42 university startups were selected from a global pool of top candidates.

- Authored a process to fabricate resin micro-rings with a targeted cross-sectional shape, predicted by simulations to exhibit unique behavior under linear, low-Reynolds-number flow- Achieved structurally resilient, multi-layer particles which remain stable at aspect ratios of up to 100- Increased the number of unique light exposures per silicon wafer by over 400%, lowering the time to ascertain new exposure parameters from 2-3 days to 5 hours per batch- Defined and documented a procedure for achieving crisp SEM images of particle cross-sectional geometries

Lab Spend is a software startup which I joined through University of Michigan's Startup Career Fair in February 2016. This was a short experience, less than 3 months, but I still learned quite a bit as it was my first real experience in the startup world.My role was not focused on software development nor any other engineering work. I simply worked on tasks wherever I was most needed, from writing emails to customer service to product demos.I did get to write one Python program, for scraping product prices and other metadata from the websites of various lab supply vendors. This task began as manual data-entry work, but I quickly realized that even my own amateurish Python skills were more than enough to automate the task. This remains quite memorable to me, as it was the first time that I ever wrote code as a job!

- Explored layer-by-layer assembly of various nanoparticle-polyelectrolyte pairs in the context of developing an ocular implant for stable, long-term drug delivery- Experimentally determined the effects of particle size, solution pH, and polymer molecular weight on LbL deposition mechanics- Co-authored paper on layer-by-layer growth kinetics, published in ChemPhysChem (December 2016)