STATUS: ACTIVE // UMASS_AMHERST

Arav Adikesh
Ramakrishnan

>> MS Computer Science Student

>> AI/ML Engineer

>> Healthcare NLP Researcher

Graduate student at UMass Amherst (May 2026) specializing in AI/ML and Natural Language Processing. Building LLM-powered agentic systems and innovative solutions at the intersection of healthcare and artificial intelligence to make medical care more accessible across languages and cultures.

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>> SYSTEM SPECS

● KERNEL

arav@umass:~$ Bay State Scholar, AI/ML Engineer, and Healthcare NLP Researcher based in Amherst, MA.

Currently pursuing Master's in Computer Science at UMass Amherst with 4.0 GPA, specializing in Data Science and Natural Language Processing.

Research interests lie at the intersection of agentic AI, NLP, and healthcare — building LLM-powered multi-agent systems that make healthcare more accessible across languages and cultures.

Passionate about leveraging LangGraph, RAG, and agentic workflows to solve real-world challenges with production-ready, scalable AI solutions.

● LOADED MODULES

Python
TypeScript
JavaScript
Java
PyTorch
React
Node.js
Spring Boot
Flask
Express
LangGraph
AWS
Git
Docker
Kubernetes
Apache Spark
MySQL
PostgreSQL
Jira

>> EDUCATION RECORDS

// View Official Transcript
IN PROGRESS

Master of Science in Computer Science

University of Massachusetts Amherst

Expected: May 2026 | GPA: 4.0

// Concentration:

Data Science

// Achievements:

  • →Graduate Bay State Scholarship
  • →Data Science for the Common Good Fellow (Summer 2025)

// Coursework:

Machine LearningReinforcement LearningTrustworthy & Responsible AIAdvanced NLPAlgorithms for Data ScienceAdvanced Information RetrievalStatistics for Data Science
COMPLETED

Bachelor of Science in Computer Science

University of Massachusetts Amherst

Graduated: May 2024 | GPA: 3.93

// Minor:

Economics

// Achievements:

  • →Chancellor's Scholarship
  • →Dean's List (All Semesters)

// Coursework:

Software EngineeringData Structures & AlgorithmsAdvanced AlgorithmsOperating SystemsDatabase Management

>> EXECUTION LOG

// Work Experience

ACTIVE[2025-09-01 :: PRESENT]

Software Engineering Intern

UMass Center for Data Science and AI

Boston, MA

  • →Designed and deployed Model Context Protocol (MCP) servers to enable document generation (PDF, DOCX) directly through LLM chat interfaces, improving content workflow efficiency by ~40%.
  • →Implemented an MCP connector for Amazon Athena, enabling natural language querying of AWS-hosted databases through LLMs, cutting query formulation and debugging time by ~75%.
ARCHIVED[2025-05-01 :: 2025-08-31]

Data Science Fellow

UMass Center for Data Science and AI

Boston, MA

  • →Led development of Media Cloud classifier pipeline, a fully automated, containerized BERT-based classifier processing 100K+ news articles from a 2B+ corpus with 96% accuracy.
  • →Implemented Optuna-based hyperparameter optimization and dashboard-driven evaluation, boosting reproducibility and deployment-ready ML workflows.
ARCHIVED[2024-05-01 :: 2024-09-30]

Machine Learning Intern

Prime Focus Technologies

Los Angeles, CA

  • →Developed a RAG-powered support chatbot using LangChain and FAISS vector database to handle 500+ daily queries, achieving 88% user satisfaction.
  • →Created an automated query classification system that reduced manual triage and saved $15K annually in support costs.
  • →Deployed end-to-end production-grade conversational AI systems with JavaScript frontend, Spring Boot microservices, Flask APIs on AWS Lambda, and Kubernetes, achieving <200ms response time and 99.5% uptime.
ARCHIVED[2023-09-01 :: 2024-05-31]

Undergraduate Course Assistant

UMass Amherst

Amherst, MA

  • →Conducted 5+ weekly office hours, assisting 50+ students with code troubleshooting and learning support.
  • →Graded 200+ assignments with precision, offering constructive feedback to support student growth.

// Research Experience

ACTIVE[2025-01-01 :: PRESENT]

LLM Researcher

UMass BioNLP Lab

Amherst, MA

  • →Developed MedCOD framework integrating UMLS and LLM-KB knowledge sources to enhance English-to-Spanish medical translation — improving translation quality by 80% (BLEU ↑ from 24.47 → 44.23) through structured prompting and LoRA fine-tuning.
  • →Published research in EMNLP 2025 Findings, contributing a novel approach to domain-specific translation addressing healthcare communication barriers for limited English proficiency populations.
ARCHIVED[2024-08-01 :: 2024-12-31]

ML Engineer

UMass RescueBox

Amherst, MA

  • →Contributed to RescueBox, an open-source digital forensics platform developed by UMass Rescue Lab for processing large-scale digital evidence.
  • →Engineered and deployed modular forensic analysis plugins, including deepfake detection and perceptual hash-based image similarity systems.
  • →Optimized inference and data pipelines by converting PyTorch models to ONNX, achieving 3× faster inference speeds.

>> PROJECT ARCHIVE

Agentic Disambiguation for Ambiguous Question Answering

Research project investigating agentic RAG (Retrieval-Augmented Generation) for handling ambiguous open-domain questions. Implements LangGraph-based multi-agent system with HyDE (Hypothetical Document Embeddings), sub-query decomposition, and structured multi-interpretation synthesis. Achieved 8.6% F1 improvement over vanilla RAG on AmbigNQ dataset using hybrid retrieval (BM25 + FAISS).

// Dependencies:

PythonLangGraphRAGLLMsFAISSPySeriniOpenAI
SOURCEPAPER

Web Agent Security Research

Research project investigating security vulnerabilities and attack vectors in LLM-powered web agents. Analyzes potential risks and proposes mitigation strategies for autonomous agents interacting with web environments.

// Dependencies:

LLMsSecurityWeb AgentsResearch
POSTER
YOLO Knowledge Distillation

YOLO Knowledge Distillation

An optimized knowledge distillation framework for YOLOv8 using PyTorch. Trained and evaluated across CIFAR-10, Tiny-ImageNet, and Oxford Pets datasets.

// Dependencies:

PyTorchPythonDeep Learning
SOURCEPOSTER
UMass Outing Club Gear Locker

UMass Outing Club Gear Locker

Scalable REST API using Express.js/TypeScript with Firebase Real-time Database, handling 100+ daily transactions. Led a team of 3 developers implementing Agile methodologies.

// Dependencies:

TypeScriptExpress.jsFirebase
SOURCE
Run!

Run!

Educational game in C# and Unity inspired by Dead by Daylight. Players solve mental math puzzles to evade ghost pursuers. Implemented A* pathfinding with Unity's NavMesh for adaptive AI.

// Dependencies:

C#UnityGame Development
SOURCEPOSTER