Devin S. Email & Phone Number

California, United States

Mountain View, California, US

- Co-founded an AI company that uses ML to identify and fix vulnerabilities in smart contracts, raising $1.7M from investors like Alchemy and Symbolic Capital with advisors/angels from Meta, Apple, and Ledger- Trained a lightweight graph neural network (GNN) with NetworkX and PyTorch Geometric to classify cross-contract and cross-function reentrancy from.

Durham, North Carolina, US

- Collaborated with postdocs to create a shallow U-Net in TensorFlow to segment neurons in 2-photon calcium imaging videos called SUNS- Created an active learning pipeline that selectively labels neurons based on their frequency and SNR in successive SUNS runs, which reduces the need for labeled neurons to reach SOTA by 50x- Developed sets of Bash scripts.

San Mateo, California, US

- Implemented an approach in PyTorch to estimate training data influence by tracing gradient descent with Weights and Biases logs and Torch Studio- Extended approach to object detection for detection of false negatives in human-labeled datasets; treated mislabeled instances as its own class based on mixed confidences from its original labeled classes.

Burlingame, California, US

- Led a team of 3D engineers and ML research scientists in leveraging domain-randomized synthetic data to train product recognition algorithms, utilizing Unity for simulation and PyTorch for model development, hosted on Azure Cloud for scalable processing- Developed a product auto-labeling pipeline that utilizes instance segmentations from simulation data.

Palo Alto, CA, US

- Conducted experiments to increase the NGFR+ percentage (editing rate) for FOXP3 gene editing in hematopoietic stem progenitor cells (HSPCs) at the Bacchetta Lab- Utilized a design of experiments approach to optimize CRISPR-Cas9 editing of HSPCs, resulting in a published paper in Cytotherapy Journal- Performed cost analysis to demonstrate a reduction in.

Durham, NC, US

- Collaborated with KORA (Kinetic Operating Room Assistant) to develop a camera-based vision system as a foundation for machine learning solutions in the operating room, focusing on autonomous lighting and camera systems for image acquisition and touchless operating area illumination- Utilized Python scripts and BLE (Bluetooth Low Energy) technology to.

Computer Science And Biomedical Engineering

Education record