# Aryan Mudgal - AI/ML and Data Science Practitioner
Source: https://hello.cv/aryanmudgal
Delhi

## Links
- LinkedIn | https://www.linkedin.com/in/aryanmudgal03

## About
Highly motivated AI/ML and Data Science practitioner with 2 years of hands-on experience, specializing in developing scalable, intelligent systems leveraging LLMs, Reinforcement Learning, and Generative AI. Proven expertise in prompt engineering, LangChain, Agentic AI, and RAG pipelines, with a strong drive to deliver high-impact ML solutions that address real-world challenges and drive significant efficiency gains.

## Work
### Data Science Intern | Veersa Technologies
As a Data Science Intern, Aryan developed and deployed advanced AI/ML solutions, focusing on LLM-based document intelligence, multi-agent systems, and NLP pipelines to drive significant operational efficiencies.
- Developed vfileManager, an LLM-based document intelligence system leveraging LangChain and FAISS, automating file clustering and semantic QnA to reduce document retrieval time by 60%.
- Architected a multi-agent Agentic AI Assistant for medical recommendations, interaction checks, dosage validation, and automated report dispatch, cutting manual doctor workload by 50%.
- Deployed Profanity Pulse, an LSTM classifier for 7-category text toxicity scoring, achieving 91% accuracy in content moderation.
- Implemented vChat, fine-tuned GPT-3 with an internal RAG pipeline, increasing response relevance by 35% for conversational AI.
- Led the Post-call Summary and Classification NLP pipeline for client analytics, cutting manual summary time by 65%.
- Automated the EDC Platform for HealthCat by streamlining Databricks DAB orchestration, reducing effort by 70%.
- Enhanced vExtract, a medical form parser using LLM + FastAPI, enabling 80% automation in data extraction.
- Designed a Capacity Planner, a rolling-window prediction engine using XGBoost and SHAP, improving accuracy by 22%.
### AI/ML Intern | AI-Shala
As an AI/ML Intern, Aryan trained and engineered advanced AI/ML models, including Reinforcement Learning agents, Seq2Seq translation models, and LLM guardrails, to solve complex challenges.
- Trained Reinforcement Learning (RL) agents (Q-Learning, PPO, SAC, DDPG) using d3rlpy, developing a Swing Trading RL Bot.
- Constructed LSTM-based Seq2Seq and Transformer models for English-Hindi translation, achieving high accuracy in language processing.
- Simulated a custom RL environment for Systematic Investment Planning (SIP) and explored TimeGPT for time series analysis.
- Engineered LLM Guardrails for hallucination, toxicity, and code clone detection using Tree of Thoughts, enhancing model reliability.
### AI/ML Intern | Summer Training/Internship
During this AI/ML Internship, Aryan applied machine learning techniques to design a fraud detection system and implement computer vision models, while performing foundational data analysis.
- Designed an Audit Fraud Detector for detecting fraudulent transactions, achieving 94.5% accuracy and a 0.96 AUC score.
- Implemented CNNs, RNNs, GANs, and autoencoders for vision and anomaly detection tasks.
- Performed dimensionality reduction, data cleaning, and exploratory data analysis on real-world datasets to prepare for advanced modeling.
### Data Science Intern | Coincent
As a Data Science Intern, Aryan gained practical experience in core data science methodologies, including data cleaning, feature engineering, ML modeling, and model evaluation techniques.
- Applied comprehensive data cleaning, feature engineering, machine learning modeling, and model evaluation techniques to real-world datasets, enhancing predictive accuracy.

## Education
### Maharaja Surajmal Institute of Technology | Computer Science and Engineering

## Languages
- English
- Hindi

## Certificates
### Azure Data Fundamentals
Microsoft
### Data Analytics
IBM SkillsBuild
### Microsoft Azure DP-900 certification in Data Fundamentals
Microsoft | 2023-08-01

## Skills
### Programming Languages
- Python
- SQL
- C
- C++
- JavaScript
### AI/ML Frameworks & Tools
- TensorFlow
- PyTorch
- NumPy
- Pandas
- d3rlpy
- LangChain
- FastAPI
- Flask
- MLflow
- Azure ML
- XGBoost
- SHAP
- FAISS
- Tree of Thoughts
### Data Analysis & Visualization
- Power BI
- Tableau
- Microsoft Excel
- Data Cleaning
- Feature Engineering
- Exploratory Data Analysis
### Machine Learning & AI Concepts
- LLMs
- Reinforcement Learning (RL)
- Generative AI
- Databricks
- ML Pipeline Automation
- Prompt Engineering
- Agentic AI
- RAG Pipelines
- NLP
- Computer Vision
- Anomaly Detection
- Time Series Analysis
- Fraud Detection
- LSTM
- CNNs
- RNNs
- GANs
- Autoencoders
- Seq2Seq
- Transformers
### Cloud & DevOps
- Git
- Azure Data Fundamentals
- Databricks DAB Orchestration

## Projects
### Credit-Card Fraud Detection using Autoencoders
Developed a robust credit-card fraud detection system utilizing autoencoders to identify anomalies in transaction data.
### Disease Prediction from Call Recordings between Patient and Medical Staff
Designed and implemented a system to predict diseases by analyzing call recordings between patients and medical staff, leveraging natural language processing techniques.

## Source
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