Research AI Engineer · Machine Learning

Nhoojah
Maharjan

Machine learning, reinforcement learning, and world models —
building agentic systems that hold up in the real world.

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Nhoojah Maharjan
About

Hi, I'm Nhoojah

Computer Science undergraduate at the University of Southern Mississippi (GPA: 4.0), working across machine learning research and the data infrastructure that research depends on. I study reinforcement learning and world models, and publish on segmentation and machine unlearning. Alongside that I build production systems — NOAA oceanographic data platforms, public-health data pipelines, and LLM agent surfaces.

Research Interests

Machine learning, reinforcement learning, and world models — with a particular interest in causal reasoning, sample-efficient exploration, and deployable agentic systems that support reliable, real-world decision-making. Open to new directions across ML and autonomous systems.

University of Southern Mississippi
B.S. Computer Science · Minor in Economics & Data Analysis · GPA 4.0
Aug 2024 – May 2028 (expected) · Hattiesburg, MS
Coursework: Data Structures & Algorithms · Artificial Intelligence · Linear Algebra · Probability & Mathematical Statistics · Discrete Mathematics · Computer Systems · Computer Networks · Database Concepts · Secure Software Development · Cyber Law & Ethics
Resume Academic CV GitHub LinkedIn
Areas of Focus
01
Reinforcement Learning & World Models

Model-based RL for task-agnostic exploration — action-rooted causal affordance models, compositional capability graphs over open-world environments, and planning in latent imagination with uncertainty-gated grounding.

02
Foundation Models & Unlearning

Cross-domain benchmarking of vision-language models against supervised baselines, and exact machine unlearning that lets fine-tuned models forget specific training data without a full retrain.

03
LLM Agents & Tooling

Agentic workflows, RAG, and Model Context Protocol surfaces that expose large scientific catalogs to LLM clients, backed by GCP-hosted inference.

04
Data & Systems Engineering

Multi-source ingestion and indexing pipelines, typed RPC services in Go, high-throughput backends, and Terraform-managed cloud infrastructure across GCP, AWS, and Azure.

Research Experience
  • Research AI Engineer
    Nov 2025 – Present
    Institute for Advanced Analytics and Society (IAAS) · NOAA-funded · Hattiesburg, MS
    • Contributing to AQUAVIEW, a production cloud-native platform giving researchers and downstream pipelines programmatic access to over a century of NOAA oceanographic and Earth-observation data.
    • Building and maintaining the Python data library, REST API, and MCP surface — the interfaces that expose the catalog to human researchers and to LLM/agent clients.
    • Supporting the multi-source ingestion and indexing pipeline (Dagster + STAC/SFEOS on Elasticsearch), unifying 40+ heterogeneous NOAA sources into a single searchable catalog covering 125+ years of ocean data.
    • Prototyped LLM-based tagging and classification for platform metadata, and helping build agentic LLM workflows on GCP for downstream data-product impact analysis by NOAA stakeholders.
  • Undergraduate Researcher
    Apr 2025 – Present
    Advised by Dr. Rabab Abdelfattah · University of Southern Mississippi
    • Co-authored the first comprehensive benchmark of deep-learning architectures for cross-domain thin-object segmentation — a 5-family taxonomy (CNNs, Transformers, GANs, classical, foundation models) evaluated across biomedical, infrastructure, and remote-sensing datasets (IEEE Internet of Things Journal, 2026).
    • Stress-tested vision-language foundation models (SAM, DIS-SAM, CLIPSeg, GSVA) against supervised baselines under zero-shot and prompt-engineered conditions, quantifying up to a 13% absolute precision increase on infrastructure benchmarks.
    • First-authoring SEU (Siloed Exact Machine Unlearning) — an architecture that lets fine-tuned models exactly forget specific training data by pairing a frozen foundation encoder with isolated adapter heads, making deletion a targeted reset rather than a full retrain (~8,700× faster than exact retraining while matching a from-scratch model).
  • Undergraduate Researcher
    Jun 2026 – Present
    Advised by Dr. Alen Hajnal · Perception, Action & Cognition Lab, USM
    • Developing a model-based reinforcement learning (MBRL) framework for task-agnostic exploration that replaces standard pixel-prediction dynamics with an action-rooted Causal Affordance World Model.
    • Designing compositional capability graphs over open-world environments (Minecraft, Crafter) where each edge encodes an agent-centric causal intervention; planning happens in latent imagination and drops into the real environment only when the model ensemble is uncertain about a specific affordance edge.
    • Formalizing self-termination via graph completeness — the framework inherently prunes the classic "Noisy TV" pathology, since uncontrollable dynamics produce no stable causal links.
  • Undergraduate Researcher
    Fall 2024
    Advised by Dr. Partha Sengupta · University of Southern Mississippi
    • Investigated Virtual Reality Exposure Therapy (VRET) for PTSD, phobias, and anxiety, weighing clinical effect sizes against biometric-data privacy, dissociation risk, and the security gaps that come with immersive data collection.
    • Presented findings as a poster at the 89th Mississippi Academy of Sciences Annual Conference, Biloxi Gulf Coast Convention Center.
Industry Experience
  • Data Engineering Intern
    May 2026 – Present
    Gulf South Center for Community Engaged Health Research and Innovation · Hattiesburg, MS
    • Building ETL/ELT pipelines that unify heterogeneous public-health datasets (CDC Social Vulnerability Index, MRI imaging, U.S. Census, CDC surveillance) into a common access layer for interdisciplinary research teams.
    • Designing multi-layer APIs and metadata cataloging so researchers can pull cross-source datasets without dealing with schema differences or curation overhead.
    • Implementing versioned dataset snapshots so downstream analyses stay reproducible against precisely dated slices of federal data.
  • Optimization Modeling Intern
    Jan – May 2026
    Optimal Answers LLC · Gulfport, MS
    • Architected prescriptive analytics models using Dataform (Optimal Modeling Language) on Azure to solve Linear and Integer Programming problems, modeling qualification criteria, solution constraints, and reduced-cost marginal-value outputs across procurement, portfolio, and supply chain pipelines.
    • Modeled large economic datasets from the Gulf Coast Business Council and Restoration Fund to optimize grant selection and resource allocation, defining multi-period constraint hierarchies and attribute logic to maximize goal achievement under strict bounds.
  • Software Developer
    May – Aug 2025
    Dabuli (Nonprofit, 501(c)(3)) · Seattle, WA
    • Architected a microservices backend in Node.js/Express sustaining 15,000+ req/min at sub-100ms p99, cutting query latency 40% via Redis caching and compound indexing.
    • Instrumented OpenTelemetry distributed tracing and automated recovery pipelines, reducing MTTR from hours to under 10 minutes.
Technical Skills

Languages

Python · TypeScript · Go · Java · C/C++ · SQL

ML & AI

PyTorch · HuggingFace Transformers · JAX · PEFT/LoRA/QLoRA fine-tuning · DeepSpeed/FSDP distributed training · model quantization (ONNX, GPTQ) · LM-Eval-Harness · WeightWatcher · machine unlearning

LLMs & Agents

LangGraph · Model Context Protocol (MCP) · RAG · vector databases (Pinecone, Weaviate) · vLLM/TGI inference · prompt engineering · foundation-model APIs (Claude, GPT, Gemini)

Systems & Web

FastAPI · Spring Boot · Node.js/Express · Next.js · React · ConnectRPC/gRPC · GraphQL · Protobuf · WebSockets · Apache Kafka

Cloud & DevOps

GCP (Vertex AI, Cloud Run, GKE) · AWS (ECS, Fargate, S3) · Azure · Docker · Kubernetes · Terraform · GitHub Actions · OpenTelemetry (Grafana, Tempo, Loki)

Data

PostgreSQL · MongoDB · Elasticsearch · Redis · Firebase · Supabase · Apache Airflow · dbt

Publications & Presentations
  1. From Classical Pipelines to Promptable Foundation Models: A Cross-Domain Study of Thin-Object Segmentation
    A. Hossain, N. Maharjan, M. Hasan, R. Abdelfattah, M. Ezz-Eldin, X. Wang, M. M. Fouda, K. Abdelfattah
    IEEE Internet of Things Journal 2026
  2. SEU: Siloed Exact Machine Unlearning for Fine-Tuned Models
    N. Maharjan, B. Khadka, R. Abdelfattah
    Under Review
  3. Exploring the Promise of Virtual Reality Exposure Therapy (VRET) While Navigating Security Risks in a Digital Age: Examining the Positive and Negative Effects of VR
    N. Maharjan, B. Khadka, A. Kharal
    Poster 89th MAS Annual Conference, Biloxi Gulf Coast Convention Center, MS 2024
Awards, Honors & Funding
Technology for Health Award
College of Nursing and Health Professions, University of Southern Mississippi · Summer 2026 — competitive research grant funding technology work in community health.
Hatchery Checkpoint Award
$500 seed funding awarded for a project pitch, University of Southern Mississippi.
Honors Keystone Scholar
University of Southern Mississippi.
President's List
Awarded every semester of enrollment, University of Southern Mississippi.
Academic Excellence Scholarship
Full tuition, University of Southern Mississippi.
Projects
Enterprise Data Toolkit

Long-running AI coding agents orchestrated in Daytona sandboxes via Vertex AI, streaming incremental output over WebSocket with SSE fallback and reconnect-safe session handling for durable workspace state. Owns the Protobuf API contracts behind a ConnectRPC Go microservice that abstracts the full sandbox lifecycle, with OpenTelemetry tracing on Terraform-managed GCP.

GoNext.jsConnectRPCProtobufVertex AIGCPTerraform
Research.it

Multi-stage LLM pipeline (extract → normalize → gap-detect → verbalize) that ingests papers, extracts citations, and builds a knowledge graph of the surrounding research landscape — a regex-first/LLM-fallback extractor cut parse failures ~85%. Rendered in real time via Sigma.js + ForceAtlas2 with sub-second layout on 500+ node graphs, streamed over FastAPI WebSockets + uvloop for a 60% drop in perceived latency.

Next.jsFastAPIGemini 2.5 FlashSigma.jsWebSockets
Vinaya Journal

Privacy-first, offline-capable desktop journaling app with a local LLM + RAG pipeline (Ollama), mood classification, and semantic search across entries. Electron/React frontend, Spring Boot REST backend on SQLite, and a FastAPI microservice for embeddings and vector search — 35+ active users, 150+ GitHub stars across Windows and Linux.

ElectronReactSpring BootFastAPIOllamaSQLite
Learnova

AI-powered educational app with personalized course generation, adaptive quizzes, and smart flashcards powered by Gemini API and Firebase real-time sync.

React NativeExpoFirebaseGemini
HiveFind

Find hackathon teammates by skill match. AI-assisted task generation, real-time chat with AI suggestions, and invitation-based team formation.

React NativeExpoFirebaseJavaScript
Contact

Let's work together

Open to research collaborations, engineering roles, and interesting projects. Reach out anytime.

[email protected] Hattiesburg, MS