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Time-series forecasting application achieving 95% accuracy for 3-day predictions using LSTM and Graph Signal Processing. Selected for college-level Demo-Day with 90%+ appliance-level energy disaggregation accuracy. Read more
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GenAI-powered e-commerce platform enabling personalized merchandise creation from social media content using Stable Diffusion. Processes 300+ daily requests with sub-2-second latency using Next.js, Node.js, and Printrove API integration. Read more
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Full-stack MERN application managing 1000+ student records, currently in active production. Reduces manual record-keeping time by 85% and eliminates 95% of data-entry errors using MongoDB Atlas with 99.99% uptime. Read more
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Dual-sided platform connecting freelancers and employers with separate dashboards, MVC architecture, and real-time notifications. Built with React.js, Node.js, MongoDB, and Firebase for instant messaging and job management. Read more
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Full-stack platform serving 15+ lawyers with AI-powered document automation and LaTeX compilation. Reduced manual document preparation time by 97% using React.js, Node.js, Firebase, and LLM integration. Read more
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GRU-based emotion classification system achieving 95% accuracy using physiological biosignals (ECG, EMG, GSR, respiration, BVP). Implemented SHAP/LIME explainability and fairness-aware techniques reducing demographic bias by 30%. Read more
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Production-ready budgeting application with AI-powered transaction parsing using Google Gemini. Full-stack solution with React.js frontend, Node.js/Express backend, Firebase authentication, and comprehensive analytics dashboard. Read more
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Self-correcting multi-agent RAG system for querying academic research papers through natural language. Built with LangGraph, FAISS, and MCP — featuring a critic-refine loop, intelligent query routing, and Claude Desktop integration. Read more
IEEE Conference, March 18-20, 2023 Google Scholar
Published on June 1, 2023. This work aims to produce reliable short-term forecasting using machine learning methods such as Linear Regression, Random Forest Regression, and Decision Tree Regression. Results show 99% accuracy for the proposed models. Read more
Recommended citation: A.R. Kaushik, S. Padmavathi, K.S. Gurucharan, and S.Charles Raja, "Performance Analysis of Regression Models in Solar PV Forecasting," IEEE Conference, March 18-20, 2023.
2023 International Conference on Energy, Materials and Communication Engineering (ICEMCE), December 14-15, 2023 Google Scholar
Published on February 21, 2024. This study utilizes an Activity of Daily Living (ADL) dataset collected from 30 participants who performed six distinct activities while wearing smartphones equipped with sensors. Explainable AI (XAI) techniques like LIME and SHAP are used to understand the attributes significantly influencing model predictions. Read more
Recommended citation: A. R. Kaushik, K. S. Gurucharan and S. Padmavathi, "Enhancing Human Activity Recognition: An Exploration of Machine Learning Models and Explainable AI Approaches for Feature Contribution Analysis," 2023 International Conference on Energy, Materials and Communication Engineering (ICEMCE), Madurai, India, 2023, pp. 1-6, doi: 10.1109/ICEMCE57940.2023.10434184.
Presented at Conference on July 6, 2025 GitHub
Presented on July 6, 2025. This paper presents important contributions toward state-of-the-art drone classification systems that are deployable in challenging environments. Building on the groundwork laid by existing drone categorization methods, we provide two major contributions: (i) a new processing pipeline that converts RF signals into optimized spectrogram images for computer vision applications, and (ii) an extensive analysis of nine state-of-the-art CNN models. Read more
Recommended citation: Kaushik A R, Annaamalai U, and Padmavathi S, "Enhanced Drone Classification using Transfer Learning and Optimized RF-Spectrogram," Presented at Conference, July 6, 2025.
Published:
This is a description of your talk, which is a markdown file that can be all markdown-ified like any other post. Yay markdown! Read more
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field. Read more
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post. Read more
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post. Read more