Projects

2025

Toward Engineering AGI Paper

Toward Engineering AGI: Benchmarking the Engineering Design Capabilities of LLMs

Research Paper

Conducted comprehensive benchmarking of Large Language Models' engineering design capabilities, evaluating their performance across various engineering design tasks and methodologies.

Skills: Python, Signal Processing, Computer Vision

NeurIPS 2025

Real-Time QVGA Video Streaming with Filters on FPGA

Joanna Li, Ayush Barik

ECE385 Class Project

Engineered embedded quantized live video streaming pipeline on a Spartan-7 FPGA to transmit data from an OV7670 camera, optimized for low power (0.35W) and minimal resources (813 LUTs, 28 BRAM, 309 Flip-Flops). Implemented additional video filters and on-screen sprites.

Skills: SystemVerilog, Python

2024

URSA Research Presentation

Multilingual LLM-TTS Framework with Digital Signal Processing for Context-Aware Conversational AI

Ayush Barik, Roger Xiao, Yueze (Hyouin) Liu

Undergraduate Research Symposium

Developed a text-to-speech (TTS) framework integrating an LLM (Qwen-7B) with a voice model (XTTSv2) to create a context-aware, multilingual conversational AI. Trained the system on a custom, scraped dataset of the character Ruan Mei from Honkai: Star Rail. The text-to-voice pipeline uses Digital Signal Processing techniques, including Wiener and Butterworth filtering, to enhance audio quality and clarity.

Skills: Python, Text-to-Speech (TTS), Large Language Models (LLMs), Digital Signal Processing (DSP), Data Scraping