Daevin User

- Designed and implemented a custom RISC processor in VHDL; utilized waveform analysis to optimize software-hardware handshakes, reducing latency.
- Designed a 5‑stage pipelined 16‑bit reduced instruction set computer (RISC) processor in VHDL for a Xilinx Artix‑7 (Nexys 4 DDR) FPGA, with basic arithmetic, load/store, and branch instructions, plus on‑board interfaces like a 7‑segment program counte

- Architected a scalable Python simulation framework for a 6-DOF robotic arm using MuJoCo and Gymnasium, improving convergence speed.
- Built a MuJoCo/Gymnasium simulation environment with Soft Actor-Critic (SAC) reinforcement learning agents controlling a 6‑DOF robotic arm, using Python and standard reinforcement learning libraries.
- This setup lets the arm learn reliable reach‑and‑place motio

Helped students with MATLAB and signal analysis.
Assisted with grading and lab material

TRELLIS Kaolin Research - AI and 3D generation technology.
Capstone Research - Electrical power systems at VCU.
Drone Imaging & ArcGIS - Drone-based 3D modeling
Coding Workflows - Building tools and workflows across environments and VMs.

- Built an embedded wearable vision assistant that pairs an Espressif ESP32‑C6 microcontroller board with a Raspberry Pi 5, a camera, and Claude APIs to answer questions about what the user is looking at.
- The device turns a small, battery‑powered wearable into a hands‑free interface for getting information from the real world, under tight constraints on latency, connectivity, and power.
- I

- Designed a 5‑stage pipelined 16‑bit reduced instruction set computer (RISC) processor in VHDL for a Xilinx Artix‑7 (Nexys 4 DDR) FPGA, with basic arithmetic, load/store, and branch instructions, plus on‑board interfaces like a 7‑segment program counter (PC) display.
- The design and its bare‑metal demo programs show how a simple CPU can drive real FPGA hardware through memory‑mapped I/O, and h

- Developed and maintained a Python/Selenium room‑reservation bot that automated web‑based booking workflows and was used by multiple student organizations to reliably secure spaces.
- Designed a headless automation engine using Python and Selenium, saving users 150+ manual hours per month with a near 100% success rate

- Built training code around a pretrained Generative Pre‑trained Transformer 2 (GPT‑2) language model using PyTorch and Hugging Face Transformers, wiring together data loaders, prompt formatting, tokenization, and training loops for grammar‑correction tasks.
- Adapting a pretrained language model to correct grammar in short English sentences is a concrete example of how large language models can

Pursuing a Bachelor of Engineering in Computer Engineering, focusing on systems and software engineering.