Projects

Mental Health Meme Classification

A multimodal NLP course project to classify anxiety and depression symptoms from internet memes using Vision-Language Models.

2025

Addressed single-label (anxiety) and multi-label (depression) classification from memes as part of NLP coursework.
Augmented dataset by extracting OCR text and semantic triplets (Cause-Effect, Figurative Reasoning, Mental State) using QWEN-2.5-VL-7B model.
Enhanced M3H architecture with visual feature maps and fine-tuned MentalBART model for classification.
Achieved 65% Macro F1 score for anxiety and 63% for depression classification tasks.
Developed end-to-end inference pipeline with Streamlit UI for interactive visualization of results.

PythonPyTorchHugging FaceStreamlitNLPMultimodal AI

Benchmarked and monitored a complex microservices application on Docker Swarm and GKE to evaluate performance and observability.

2025

Deployed Death Star Social Network across local Docker Swarm and cloud-based Google Kubernetes Engine (GKE) environments.
Benchmarked three configurations: single-node/single-replica, multi-node/single-replica, and single-node/multi-replica.
Integrated two-tier observability stack using Pixie for real-time visualization and Prometheus for fine-grained metrics.
Analyzed performance trade-offs in latency, resource utilization, and scalability across deployment strategies.

DockerKubernetesGKEPrometheusPixieMicroservicesObservability

Runner-up project at the KAVACH-23 National Cybersecurity Hackathon, building an end-to-end ANPR and Face Recognition system.

2023

Led a team of six and collaborated with Ahmedabad West traffic police for high-definition video data collection.
Engineered decoupled API using YOLOv8 for detection, achieving 92% precision and 91% recall on number plates.
Developed cross-platform React Native application for real-time monitoring on edge devices.
Implemented face recognition using ResNet embeddings with Siamese-style few-shot learning for low-illumination conditions.
Finished as national finalist (runner-up) among top 100 teams in KAVACH-2023 hackathon.

PythonPyTorchReact NativeYOLOv8Computer VisionANPR

State-level hackathon winner and published research on predicting student dropouts using machine learning and data visualization.

2023

Won the SSIP-22 State Level Hackathon by developing a dashboard and predictive analytics platform.
Created data pipeline using official government data from UDISE+ to analyze dropout trends.
Implemented Multiple Linear and Polynomial Regression achieving R² value of 0.9976 on custom EduDropX dataset.
Extended project into research paper published in IEEE I2CT 2024 conference.

PythonPandasMachine LearningData VisualizationScikit-learn

A centralized portal for academic resources that attracted over 3,000 visits in its first week and now ranks top on Google.

2022

Identified the need for unified platform and developed centralized website to host scattered academic materials.
Organized resources into intuitive structure by subject and semester, simplifying access for students.
Achieved 3,000+ visits and 1,000+ unique visitors within the first week of launch.
Platform ranks at the top for relevant keywords on Google search, becoming a go-to resource.

Web DevelopmentSEOContent ManagementWeebly