computer engineering / machine learning / systems

Ashesh Kaji

Computer engineering graduate student at NYU Tandon. Background in cognitive science, machine learning, neuroimaging research, and applied ML systems.

profile archive
01 / profile

Profile

I am Ashesh Kaji. I study Computer Engineering at NYU Tandon and completed a BS with Honors in Cognitive Science at UC San Diego, specializing in Machine Learning and Neural Computation.

My work includes ML systems, RAG pipelines, neuroimaging research, local-first media tooling, portfolio optimization research, and hardware-aware acceleration.

This site contains public project links, research materials, coursework, archive entries, and a browser-based assistant interface.

graduate study NYU Tandon / computer engineering
undergraduate study UCSD / cognitive science, ML and neural computation
areas Rust, Python, neuroimaging, quantized models, hardware
languages English, Gujarati, Hindi
02 / experience

Experience

Consulting AI Engineer

SageX Global / remote

Consulting on AI tooling pipelines for LLM deployment, data transformation, and production MLOps.

Artificial Intelligence Engineer

SageX Global / remote

Built LLM and SLM workflows, semantic memory retrieval systems, statistical mapping models, and multimodal data pipelines.

Machine Learning Intern

UniQreate / remote

Designed extraction pipelines and chat interfaces with LLMs and vector databases, including a production RAG product with Azure integration and serverless local-model deployment.

Undergraduate Research Assistant

UC San Diego / Dr. Mary Boyle's Lab

Worked with UK BioBank and ABCD study data on peripheral iron, NAFLD, neurodegeneration, vape-related metal exposure, and MRI-derived measures.

03 / education

Education

MS in Computer Engineering

NYU Tandon School of Engineering

01/2026 - 12/2027 expected

Graduate coursework in systems, ML infrastructure, and hardware-software co-design.

BS with Honors in Cognitive Science

UC San Diego

09/2021 - 06/2025

Specialization in Machine Learning and Neural Computation, with honors work around metal exposure and brain imaging.

International Baccalaureate Diploma

SVKM's JV Parekh International School

2019 - 2021 / 39 of 45

Pre-university coursework across science, mathematics, and humanities.

04 / projects

Projects

Selected repositories, research writeups, and project pages.

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05 / skills

Skills

language

Python, Rust, C++, JavaScript, TypeScript, shell

machine learning

PyTorch, NumPy, Pandas, Scikit-Learn, RAG, NLP, vector databases

infrastructure

Linux, Docker, Git, Azure, AWS, serverless workers, WebGPU experiments

specialized

FPGA and hardware design, ZKP acceleration, statsmodels, neuroimaging workflows

06 / assistant

Site assistant

The assistant uses published site context. It does not have access to private information. Local Bonsai can be loaded below when the browser supports WebGPU.

site context local WebGPU option remote API option
Local Bonsai interface
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Local Bonsai interface. Requires WebGPU. Loads the q1 ONNX model in the browser.

Pass condition: WebGPU ready plus a real model generation event.