education

msc advanced computer science (ai)

university of leeds | 2025 — 2026

b.tech ai & data science

viit, pune | 2021 — 2025

experience

founding ai engineer · hopps

september 2024 — june 2025 | pune, india

led cross-functional product development for a food-tech platform serving ::y::70+ restaurant partners:: and 20+ beta users.
engineered an ai-powered recommendation system using ::b::gemini api::, firebase, and flutter to deliver personalized dining suggestions.
architected evolution from keyword extraction to ::p::embedding-based semantic retrieval::, identifying production bottlenecks in api latency and cost-per-query constraints.
implemented production safeguards including ::y::rate limiting:: (3 ai bio generations/user/day) and api key rotation for cost management during beta.
mentored 2 engineering interns on recommendation system architecture and mobile development, conducting code reviews and technical guidance.

research intern · iim udaipur

september 2023 — april 2024 | remote

built an automated classification system processing ::y::250,000+ nft records:: using python and hugging face to differentiate ai-generated vs. human-created content.
engineered asynchronous data collection infrastructure using ::b::asyncio and multithreading:: to scrape 113,000+ web pages with optimized throughput.
explored cloud-based distributed scraping architecture on ::p::gcp cloud functions:: for ip rotation and scalable data collection.
developed automated preprocessing workflows applying nlp techniques that led to ::y::two research manuscripts::.

ai intern · konverge.ai

august 2023 — october 2023 | nagpur, india

applied statistical modeling and machine learning for customer segmentation, purchase prediction, and profitability analysis.
built ::b::sentiment classification model:: using nlp techniques to analyze user reviews and extract actionable insights.
developed data preprocessing pipelines and visualizations to communicate model performance and business recommendations.

projects

maira · ai companion system live demo

engineered a ::p::rag-based memory system:: integrating ::b::gemini 2.0 api:: with sqlite embedding retrieval using semantic similarity thresholds for context injection.
designed a parallel memory pipeline leveraging gemini to analyze message history, extracting ::y::categorized memories with importance scoring:: and redundancy detection.
built full-stack architecture using flutter, firebase, getx, and gcp cloud functions to track persistent user context and emotional states.
implemented fluid chat ux inspired by ::p::imessage design principles:: for judgment-free companionship with long-term context persistence.

engineered a tiktok-style recommendation engine using ::y::python, flask, and faiss:: for semantic video retrieval.
implemented ::b::indexivf clustering:: with approximate nearest neighbor search to efficiently query 3072-dimensional embeddings across 500+ videos.
designed ::p::sliding window user preference model:: (last 5 interactions) with 70-30 exploitation-exploration split to balance relevance and discovery.
built multi-signal scoring system across 6 interaction types to capture nuanced user preferences.

brewstories · llm fine-tuning for creative text generation

fine-tuned ::y::tinyllama transformer (1.1b parameters):: on 10,000-story dataset using pytorch and hugging face transformers.
developed end-to-end training workflow including dataset preparation, tokenization, fine-tuning, and evaluation for generative text modeling.
achieved ::b::runner-up recognition:: at visionary techfest 24 ai/ml hackathon organized by binghamton university.

distributed training infrastructure · fraud detection full project overview

architected ::p::federated learning system:: enabling privacy-preserving collaborative training across 3 distributed clients over 10 rounds.
engineered data processing pipeline for highly imbalanced ethereum datasets (90%+ class imbalance), applying ::y::smote oversampling:: and feature engineering.
developed fraud detection classifier achieving ::b::99.7% auc-roc and 96.6% recall:: on transaction pattern analysis.
built flask-based visualization dashboard to monitor performance metrics and communicate fraud pattern insights.

research

“attention span and its correlation with mental health”

richa shah, sarthak rak, ayush patne, dr. laxmi bewoor

4th asian conference on innovation in technology, august 2024
led research design analyzing correlation between attention span metrics and mental health indicators across 84 participants.
defined analytical approach utilizing ::p::knn clustering:: for behavioral segmentation and pattern identification.

technical skills

programming: python (pandas, numpy, scikit-learn), pytorch, tensorflow, hugging face transformers
ai/ml: nlp, generative ai, llms, transformer architectures, prompt engineering, fine-tuning (lora/peft)
infrastructure: aws, gcp (cloud functions, firebase), langchain, flask, git, distributed training systems, model deployment
specializations: rag systems, semantic similarity, asynchronous data pipelines, model evaluation

leadership & achievements

hackathon lead organizer — viz-a-thon (dataviz), viit
runner-up — ai/ml domain, visionary techfest 24 hackathon (binghamton university)
media team head — tedxviit
video & photography head — ai student association, viit
class representative — ay 2021-22

certifications

machine learning specialization — stanford online & deeplearning.ai
generative ai with large language models — deeplearning.ai & amazon web services