Rahil Parikh
AI EngineerResearcherKaggle Notebooks Master

I'm an AI Developer at EvolveNXT, where I build LLM-powered systems for audio compliance auditing and client onboarding automation. I hold an MS in Computer Science with a focus on AI from USC, and my research spans LLMs for multivariate time-series classification, AI for healthcare, model explainability, and generative models for computer vision. My work has been recognized with two Best Paper Awards in generative AI and medical image classification, and I’ve contributed more than 50 pull requests to scikit-learn.

Experience

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EvolveNXT

AI Developer

(Jun 2026 - Present)

  • Designed a RAG-powered chatbot that answered 100+ questions regarding commissions for health insurance brokers.
  • Developed an AI system to audit 200+ health insurance sales calls for CMS compliance and reporting requirements.
  • Streamlined web enrollment workflows for 500+ brokers and major insurance companies using AI-based automation.
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University of Southern California

Computer Vision Research Assistant

(Sep 2024 - Jan 2026)

  • Segmented and extracted 5 vital clinical glaucoma biomarkers using U-Net, achieving an accuracy of 99.758%.
  • Initiated the development of a scalable biomarker extraction pipeline containing over 15 features to identify glaucoma.
  • Trained a multimodal model leveraging ViTs and CNNs for glaucoma classification with an accuracy of 91.383%.
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TourScout

Machine Learning Intern

(Jun 2025 - Jul 2025)

  • Led a team of 2 to develop a RAG-based LLM chatbot capable of answering questions related to concert venues.
  • Created an AI assistant to plan tours and generate performance insights, driving a 40% increase in artist engagement.
  • Deployed an E2E chatbot system with Cloudflare and AWS Lambda, capable of handling 10k+ monthly queries.
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DeepCytes Cyber Labs

Machine Learning & Cybersecurity Intern

(Jan 2024 - Jun 2024)

  • Led a team of 7 to build an application powered by LLMs to answer questions related to the IPC (Indian Penal Code).
  • Prototyped red team tools to identify security vulnerabilities and improve threat detection efficiency by 30%.
  • Directed a team of 10 in detecting fake images and videos leveraging CNN and LSTM models.
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Microsoft Learn Student Ambassadors

Beta Microsoft Learn Student Ambassador

(Mar 2023 - Jun 2024)

  • Offered mentorship to a fellow student ambassador on how to manage and conduct public speaking events.
  • Hosted an event to teach 40+ undergraduate students about AI, data science and machine learning.
  • Conducted workshops to teach students about the latest trends in technology.
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Cognition

AI Software Engineer (Part-Time)

(Apr 2024 - May 2024)

  • Calibrated LLM outputs through tailored instruction fine-tuning on 5 different software engineering tasks.
  • Instructed Devin in applying 3 VQA models for image-based QA tasks
  • Engineered an LLM based system to convert 250+ JavaScript web scrapers to Python based scrapers.

Education

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University of Southern California

Master of Science in Computer Science (Artificial Intelligence)

(Aug 2024 - May 2026)

GPA: 3.80/4

K. J. Somaiya College of Engineering logo

K. J. Somaiya College of Engineering

Bachelor of Technology in Computer Engineering

(Jul 2020 - Jun 2024)

CGPA: 9.52/10

Research

Generative AI Platform for Applying Artistic Styles to Images paper

Generative AI Platform for Applying Artistic Styles to Images

Uchit Mody, Prasanna Shete, Rahil Parikh, Jai Rajani
Best Paper Award

2024 International Conference on Computing and Data Science (ICCDS)

A Transfer Learning Approach for Classification of Knee Osteoarthritis paper

A Transfer Learning Approach for Classification of Knee Osteoarthritis

Rahil Parikh, Shreyas More, Nandita Kadam, Yash Mehta, Harsh Panchal, Himanshu Nimonkar
Best Paper Award

2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)

Dual-Branch Synergistic Learning with Randomized Convolutional Kernels and Parameter-Efficient LLM Fine-Tuning for Multivariate Time Series Classification paper

Dual-Branch Synergistic Learning with Randomized Convolutional Kernels and Parameter-Efficient LLM Fine-Tuning for Multivariate Time Series Classification

Hao Ji*, Muhammad Sakib Khan Inan*, Rahil Parikh*, Quanchao Lu, Shuo Shi, Kewen Liao

*Co-first author

Neurocomputing 2026 (paper submitted, pending acceptance)

Multimodal Glaucoma Classification Using Segmentation Based Biomarker Extraction paper

Multimodal Glaucoma Classification Using Segmentation Based Biomarker Extraction

Rahil Parikh, Van Nguyen, Anita Penkova

Knowledge-Based Systems 2026 (Volume 349)

UniExplorer: Revolutionizing the College Experience Through Comprehensive Opportunity Management paper

UniExplorer: Revolutionizing the College Experience Through Comprehensive Opportunity Management

Rahil Parikh, Himanshu Nimonkar, Aditya Ved, Om Ghadia, Ashwini Dalvi, Irfan Siddavatam

2024 4ᵗʰ International Conference on Technological Advancements in Computational Sciences (ICTACS)

Enhancing Student Welfare: A Comprehensive Analysis of the User Interface for a University Mental Health Counselling App paper

Enhancing Student Welfare: A Comprehensive Analysis of the User Interface for a University Mental Health Counselling App

Rahil Parikh, Himanshu Nimonkar, Saikrishna Karra, Ashwini Dalvi, Irfan Siddavatam

Advancements in Smart Computing and Information Security (ASCIS 2023)

Contact

For research collaborations, Kaggle competitions, hackathon judging, or general speaking, please feel free to reach out to me: rahilparikh2002@gmail.com.

You can also find me on social media:

© 2026 Rahil Parikh