Tempe, Arizona · Mathematics (Statistics) @ ASU

Aarsh
Nandra.

Applied AI Engineer
& Researcher

I build AI systems, research infrastructure, and intelligent products—from multi-agent simulations and multimodal evaluation systems to full-stack AI applications.

Working set2025—now
BUILDSYSTEMSAI / MLPRODUCTSMULTI-AGENTSRESEARCHSYSTEMSEVALUATION& DATA

A practice built around ambiguous problems, rigorous evaluation, and working software.

Selected work

Things I've made
work in the real world.

Five projects at the intersection of applied AI, research engineering, and product systems.

Applied AI · Full stackIndependent MVP

InsuranceAI

AI-assisted life-insurance intake, preliminary guidance, document review, and broker handoff.

AI / MLFull StackSystems
Research infrastructureAAAI manuscript in preparation

EduCAST Evaluation

Multimodal evaluation infrastructure for closed-loop personalized educational-video generation.

ResearchAI / MLData
Mobile AI · ResearchASU Next Lab

Dementia Assistant

Voice-first mobile AI research prototype for dementia caregiving support.

AI / MLFull StackSystems
Speech AI · ResearchFURI funded

VoxProof

A speech-first academic-integrity system exploring evidence of human-originated creation.

ResearchAI / MLSystems
Agent-based simulationOngoing research

Classroom Simulation

Concordia-based research into teacher-student interaction and emergent classroom patterns.

SimulationResearchAI / ML

Research

Research is where I learn to ask better technical questions.

At ASU's DaRL Lab, I work on educational AI evaluation infrastructure and the emerging problem of multi-agent classroom simulation—taking seriously both what a system does and how we know it works.

EduCAST

Co-first author; AAAI manuscript in preparation. Multimodal evaluation pipelines for personalized educational-video generation.

Classroom simulation

Ongoing Concordia-based research into teacher-student interaction, interventions, and emergent patterns.

Engineering experience

Applied AI Engineer ASU Next Lab

Voice-first mobile AI prototype for dementia-caregiving research.

Undergraduate Researcher DaRL Lab · ASU

Multimodal evaluation and research infrastructure for educational AI.

AI Systems Engineer Ender-IT

Recruiter-facing matching and workflow infrastructure.

Project archive

More systems, experiments, and prototypes.

HiNC Local AI PDF Q&A

Fully local, multi-document semantic Q&A with page-level sources and no cloud AI pipeline.

AI / ML · Data · SystemsGitHub ↗

BlogPostAI

Modular autonomous pipeline that researches, synthesizes, styles, and renders long-form articles from one prompt.

AI / ML · SystemsGitHub ↗

HealthInsightEngine

Personal-health data analysis infrastructure using rule-based reasoning, statistics, and trend detection.

Data · AI / MLGitHub ↗

Ender-IT Recruiting Platform

Internally deployed recruiter workflow with resume parsing, candidate state, matching, retrieval, and job management.

Full Stack · Systems · AI / MLInternal deployment

CarbonIQ

Award-winning Solana prototype connecting wallet transactions, estimated carbon impact, and staking incentives.

Full Stack · Systems · DataGitHub ↗

Technical toolkit

Useful tools,
organized by the work.

AI & ML

LLM systems · multimodal AI · RAG · embeddings · vector search · Whisper · scikit-learn

Research & evaluation

experimental design · benchmarking · human evaluation · ablations · agent-based simulation · statistics

Product & backend

Python · FastAPI · REST APIs · SQLAlchemy · document processing · rate limiting

Frontend & mobile

React · React Native · Expo · TypeScript · Vite · Tailwind CSS

Data & infrastructure

SQL · PostgreSQL · Supabase · pandas · NumPy · synthetic datasets

Core languages

Python · JavaScript · TypeScript · Java · SQL

About

I like making complicated things concrete.

I'm a Mathematics (Statistics) student at Arizona State University's Barrett, The Honors College. I work across AI research and engineering because I enjoy understanding complex systems: how they behave, how they can be evaluated, and how to turn an ambiguous idea into software people can use.

I'm especially interested in intelligent systems, simulation, machine learning, and difficult technical problems that reward careful reasoning.