aaparikh - Personal Portfolio

About Me

Innovating with AI & Data Science

I am an AI & ML Developer, Product Strategist, and Co-Founder passionate about building AI-driven solutions that create real-world impact. My expertise spans AI research, LLM development, cloud computing, and multi-agent systems.

Key Highlights:

🚀 Co-Founder & CPO at BrainGnosis – Developing LLM-powered multi-agent AI systems.
💰 Managing $600K+ in AI contracts with leading tech and research organizations.
🏥 Building AI-powered healthcare assistants at Purdue University for early disease prediction.
🤖 Created CookGPT – an advanced RAG system reducing search times by 85%.

I am always open to collaborations that push the boundaries of innovation. Let's build the future together!

Download Resume

Currently learning and practicing

Cloud Computing

Breaking down the complexities to build scalable and secure applications.
AI/ML Development

Building intelligent systems that learn from data and improve over time preserving privacy. Main focus on healthcare AI.
Data Enginnering

Building data pipelines, data lakes, and data warehouses to enable data-driven decision making.
Data Analysis

Analyzing data to extract insights and make data-driven decisions.

Technical Skills

Python

SQL

Shell Scripting

Machine Learning

Deep Learning

LLMs

Computer Vision

Time Series Analysis

NLP

LangChain

TensorFlow

PyTorch

MLOps

Azure AI

Flask

Django

FastAPI

ONNX

Cloud Computing

A/B Testing

Project Management

Technical Writing

Experience

BrainGnosis

AI and Product Strategy (Co-Founder, CPO)

West Lafayette, IN, USA Jan 2025 – Present

Created an LLM Agent framework - SciBorg to rapidly deploy MultiAgent systems for organizations, with features like Modularity, advanced benchmarking, Finite State Automata (FSA), and dynamic memory for Agent to Agent communication.
Managing $600K+ worth of AI contracts with leading tech and research companies.
Spearheading the development of an AI operating system for enhanced process efficiency in enterprises.

Purdue University

AI and Software Developer

West Lafayette, IN, USA Jan 2024 – Present

Developed AI-powered healthcare assistants for Cleveland Clinic using LangChain and time-series models (LSTM,TimeVAE, Online Learning) to predict brain hemorrhage risks with 97% accuracy, enabling early intervention.
Built advanced RAG automation pipeline for personalized medical insights and automated alert systems.
Built pluggable AI tools, such as automated PubChem integration for chemical information access and instrument drivers for controlling and running chemical instruments in AI-driven smart labs.
Co-authoring research papers on AI applications in healthcare and scientific research, in collaboration with the NIH.

Cook Medical

Machine Learning Engineer

Bloomington, IN, USA Jun 2024 – Aug 2024

Engineered a "Complaints Forecasting" model using Azure ML pipelines, achieving an R² score of 0.92 to accurately predict priority products for quality checks and hence minimize the losses.
Developed "CookGPT" leveraging Azure AI (Search Service, Datalake, OpenAI API) to implement an advanced search and retrieval (RAG) system within Cook Medical's internal knowledge base, drastically reducing the search time by 85%, averaging to 3 minutes.
Led data mining & cloud automation strategies, building real-time monitoring dashboards in Power BI.

AbbVie

Graduate Student Researcher - Data Mine Purdue

West Lafayette, IN, USA Jan 2024 – Apr 2024

Engineered multi-touch sequence-based attribution models using XGBoost with SHAP values for interpretability, optimizing marketing spend and maximizing ROI for pharmaceutical campaigns.
Deployed a Streamlit app for real-time analysis.

Purdue University

Graduate Research Assistant

West Lafayette, IN, USA Sep 2023 – Jan 2024

Applied data analytics and image processing tools (SOAX, OpenCV, NumPy, Pandas) to analyze actin microfilaments.
Engineered algorithms, developed performance metrics, and created a phenotype-specific registry for diverse plant types.

Labellerr

Software Developer (ML)

Chandigarh, India Jan 2023 – May 2023

Developed the Autolabel Jobs feature for automated dataset labeling using domain-specific and zero-shot models, boosting annotation speed by 82%, and integrated it into the product demo for customer engagement.
Implemented and deployed models including CLIP, DINOv2, YOLOv8, and semi-supervised learning techniques to reduce manual labeling across large-scale vision datasets.
Contributed to data engineering, model evaluation, competitive analysis, and technical knowledge sharing through presentations, blogs, and cross-functional collaboration with marketing.

Defence Institute of Advanced Technology

AI developer - Contract Project

Remote, India Oct 2022 – May 2023

Developed automated AI pose estimation model for learning and correcting multiple army drills exercise, using OpenCV, Mediapipe, and YOLOv8 for underprivileged area with no resources/internet connection.
Deployed a real-time offline pose-tracking and feedback system with automated pose correction guidance report and video snippets.
Designed and Created UI/UX using Figma and user-friendly web application using Flask.

Technological University of the Shannon

Automation Developer

Remote, Ireland Aug 2022 – Jan 2023

Built a data extraction pipeline for Enterprise and Hertz invoices using OCR, NLP, and machine learning, achieving 98% accuracy and reduced manual entry time
Outperformed RPA tools such as BluePrism and UIpath with improved anomaly detection and 75% faster processing

Digital Darwin

Data Scientist

Remote, India Jun 2022 – Aug 2022

Contributed to the development of the company's core AI-based product, executing end-to-end pipelines from raw data collection to on-device model deployment with optimization.
Worked on Pose Estimation and Image-based models, ensuring efficient training and inference tailored for real-world applications.
Participated in an NVIDIA-powered startup hackathon and established a long-term strategy for data collection and in-situ dataset curation.

Apna

Data Analyst

Remote, India Nov 2021 – Feb 2022

Built interactive internal dashboards using Retool, integrating tools like Metabase and Twilio to streamline operations and communication.
Analyzed user response data via Google Sheets and SQL to inform product and design decisions.
Created clear, insightful visualizations using Plotly.js to support data-driven decision-making across teams.