About Me

Hello, I'm Raghavan Srinivas

I'm an undergraduate at the University of California, Berkeley, double majoring in Computer Science and Data Science with a minor in Business Economics.

I'm passionate about natural language processing, large language models, machine learning, and back-end development. More than anything, I'm driven by the challenge of leveraging AI and using data to build solutions that create real-world impact.

Raghavan Srinivas - Photo 1
Raghavan Srinivas - Photo 2
Raghavan Srinivas - Photo 3

Experience

AI Consultant

Scale AI

July 2025 - September 2025
  • Annotated and reviewed over 10,000 data samples across NLP and computer vision tasks, achieving a 98% accuracy rate and contributing to high-quality model training datasets
  • Provided detailed feedback to improve model outputs and task flows, collaborating with cross-functional teams to iterate on prompt design and labeling strategies
  • Identified and documented recurring model failure patterns, enabling a 15% reduction in false positives through targeted dataset improvements and model refinements

Software Development Intern

GlidelyAI

June 2025 - July 2025
  • Leading the development of internal automation infrastructure at GlidelyAI, streamlining workflows between external platforms and internal tools to enhance operational efficiency
  • Developing scalable, maintainable software systems that integrate third-party APIs and browser automation, supporting key product and growth initiatives at GlidelyAI
  • Building and maintaining robust browser-based data pipelines to support product intelligence, outbound engagement, and CRM enrichment

Machine Learning Intern

Balnce AI

January 2025 - May 2025
  • Developing AI-driven agents that autonomously analyze user interactions to extract and categorize intent, preferences, and behavioral insights, optimizing personalization and decision-making, improving recommendation personalization by 22%
  • Integrating advanced memory storage and retrieval mechanisms, leveraging vector and graph databases to enhance AI agents' ability to adapt, reason, and execute complex tasks efficiently
  • Engineered a synthetic data generation and validation pipeline using LLMs to create high-quality training data for intent detection, enabling scalable model fine-tuning and accelerating iteration cycles across agent workflows

Data Science Intern

CA State Water Resources Control Board

August 2024 - Present
  • Recognized with the Award of Excellence in Large Language Modeling at UC Berkeley's Fall 2024 Research Symposium for contributions to evaluating de facto wastewater reuse risks using machine learning and data scraping techniques
  • Developing and prototyping an NLP-driven data scraping tool to efficiently extract and analyze 100K+ wastewater contaminant data from literature over 250K+ academic papers, improving predictive modeling of contaminant loading
  • Fine-tuning LLM prompts to enhance extraction of quantitative data (e.g., graph coordinates, concentration values), boosting precision in wastewater contaminant identification for regulatory risk assessment

AI Intern

Liner

September 2024 - December 2024
  • Integrated Liner's AI-powered research tools to enhance information retrieval for over 10K students and professionals while conducting user research to refine AI-driven workflows for academic and industry applications
  • Partnered with Liner's team to design and deploy generative AI solutions that boosted research efficiency by over 40%, streamlined automation workflows, and enhanced knowledge discovery

Undergraduate Research Intern

UC Berkeley

September 2024 - Present
  • Collaborated with Professor David Romps to build a real-time "feels like" temperature visualization by integrating heat index and surface temperature data from weather stations across the U.S.
  • Designed and deployed a cloud-based data pipeline using AWS Lambda, S3, and EC2 to automate data processing and visualization updates at regular intervals
  • Conducted exploratory data analysis to validate heat index calculations and ensure geographical and temporal accuracy, contributing to an accessible tool for public climate awareness

UC Berkeley Involvement

Big Data at Berkeley

Bootcamp Head Instructor

Big Data at Berkeley

  • Lead instructor of a cohort of 30 students in data science fundamentals, including data collection, EDA, data analysis techniques, and basic machine learning
  • Spearheaded curriculum design and continuous refinement of instructional materials, ensuring engaging, up-to-date content aligned with industry practices and student feedback
Piedmont Consulting Group

Director of Technical Strategy

Piedmont Consulting Group

  • Lead the scoping, technical direction, and execution of technical client projects—managing cross-functional student teams, establishing project pipelines, and directly engaging with companies to deliver tailored, high-impact solutions
  • Collaborate with startups and enterprise partners on projects involving AI agents, API testing, machine learning models, and intelligent system design
AI Entrepreneurs at Berkeley

Machine Learning Researcher

AI Entrepreneurs at Berkeley

  • Developed personalization features for an AI-powered home search platform that matches users with housing options based on lifestyle preferences using NLP and intent modeling
  • Refined recommendation logic and integrated large language models in collaboration with a cross-functional team to improve user experience and decision support
AI Ventures at Berkeley

AI Researcher

AI Ventures at Berkeley

  • Explored generative AI workflows and contributed to AI product development by enhancing user research tools in collaboration with Liner
  • Gained hands-on experience with large language models and applied emerging AI trends to real-world use cases within a fast-paced research environment

Projects

GTO Copilot

GTO Copilot

An AI-powered game theory optimal poker assistant that provides real-time strategy recommendations and analysis for optimal decision-making in poker scenarios.

Machine Learning Game Theory Custom Model Training
easyATS

easyATS

An intelligent applicant tracking system that uses NLP and ML to streamline recruitment processes, automatically screen resumes, and match candidates to job requirements.

Claude AI Natural Language Processing Plotly Dash
LectureLens

LectureLens

An AI-powered platform that analyzes lecture videos, generates summaries, creates study materials, and provides intelligent Q&A capabilities for enhanced learning.

Computer Vision Flask Transcription
SoberSignal

SoberSignal

A machine learning-based system for detecting impairment levels through behavioral analysis, designed to enhance safety and support recovery programs.

Cloudflare Workers PostgreSQL Twilio
RecovAI

RecovAI

An AI-driven platform for addiction recovery support, providing personalized treatment recommendations, progress tracking, and predictive relapse prevention.

MongoDB Atlas Node.js Gemini AI Chatbot
Conflict Predictor

Conflict Predictor

A machine learning model that analyzes geopolitical data and social indicators to predict potential conflict zones and assess regional stability risks.

Pandas Random Forest Data Analysis
AquaDrone

AquaDrone

An autonomous drone system for water quality monitoring and environmental assessment, using IoT sensors and AI for real-time aquatic ecosystem analysis.

Robotics Google Vision C/C++
NBA Speech Stats

NBA Speech Stats

A natural language processing system that analyzes NBA player interviews and generates statistical insights about performance, sentiment, and team dynamics.

HTML/CSS Python Text to Speech
HoverRaiders

HoverRaiders

A multiplayer drone racing game with AI-powered opponents, featuring real-time physics simulation, intelligent bot behavior, and competitive gameplay mechanics.

Circuits Electornics Prototyping

Skills

Programming Languages

Python
Java
JavaScript
C/C++
R
SQL
HTML/CSS

AI/ML

TensorFlow
PyTorch
Scikit-Learn
HuggingFace
OpenAI
MLflow
Langchain
Google Vertex AI
OpenCV
NLTK
spaCy
Transformers
Keras
XGBoost
LightGBM

Data Science

Pandas
NumPy
Matplotlib
Seaborn
Plotly
Jupyter Notebook
Tableau
Power BI
Apache Spark
Apache Kafka
Statsmodels
SciPy

Frontend

React
Vue.js
Angular
Bootstrap
Tailwind CSS
SASS/SCSS
TypeScript
React Native

Backend

Flask
Node.js
Express.js
Spring
FastAPI
MongoDB
PostgreSQL
AWS
Google Cloud Platform
Docker
Git
Kubernetes
Redis
GraphQL
REST APIs

Contact Me

Let's Get in Touch

I'm always interested in hearing about new opportunities and interesting projects. Feel free to reach out if you'd like to collaborate!

raghavan.srinivas@berkeley.edu
Berkeley, CA
UC Berkeley - Computer Science & Data Science