I'm an AI/ML engineer working across computer vision and generative AI — from a real-time wildlife-conflict detection system published in IEEE Xplore, to offline-first AI companions that don't depend on a network connection. I care more about whether a system holds up under real conditions than whether the demo looks good.
I graduated with a B.Tech in CSE (AI & ML) from Vignan Institute of Technology and Science, Hyderabad, and I'm currently looking for my first full-time role in AI/ML engineering. WildGuardAI, my flagship project, predicts human–wildlife conflict in real time by analyzing detection, movement, and proximity from camera-trap-style footage — the work was published in IEEE Xplore.
Most of what I build tries to work with real constraints: JivanMitra and my research-agent projects run fully offline, because I'm more interested in systems that hold up without a safety net than ones that only work with an API key and a stable connection.
Contributed to hands-on AI/ML projects and tasks, building practical experience across the model development workflow.
Built interactive web platform features and visual content. Researched AI-driven ideas for recruitment tools and chatbots, and wrote reports and content for the platform.
Built a smart electricity demand & price forecasting system using Facebook Prophet time-series models, reaching ~95% accuracy on real market datasets. Developed the Flask backend and a Tailwind-styled UI for dynamic date-range inputs with real-time forecast visualization.
Developed an Air Quality Prediction System for Indian cities using Random Forest Regression on PM2.5, PM10, and NOx pollutant data, reaching ~96% AQI category accuracy. Built interactive CLI visualizations and data pipelines across multiple city datasets.
Built a movie recommendation engine suggesting personalized picks based on user preferences and historical data — the earliest version of what's now the Movie Recommendation System project in the archive below.
Deep learning system using YOLOv12n, BoT-SORT, and a Kalman Filter to detect animals crossing forest boundaries from live camera feeds. Flask backend with SQLite and GPS-based alerting notifies forest officers and villagers before dangerous encounters happen. Published in IEEE Xplore as "Wild Guard AI: Real-Time Wildlife Conflict Prediction" (2026).
Offline, voice-only AI caretaker for elderly users in India. Uses LangChain RAG, LLMs, and NLP to hold context-aware, multilingual conversations in local languages, without depending on a stable internet connection — built for accessibility, not tech fluency.
A research agent that reads and reasons over documents entirely offline. Rebuilt on Ollama and Mistral after the original API-dependent version proved too fragile for reliable local use.
Streamlit dashboard forecasting cybercrime trends across Indian states using ARIMA and Polynomial Regression, reaching ~93% accuracy, to support awareness and policy planning.
Offline research assistant using RAG, local embeddings, ChromaDB, and Ollama Phi-3 to analyze PDFs with multi-step reasoning.
Explore →An earlier, voice-first iteration of JivanMitra designed to support elderly users in India.
Explore →Hands-free navigation through voice commands in an immersive 3D browser environment, built for accessibility.
Explore →Analyzes and generates EEG signal patterns using deep learning techniques.
Explore →Converts photos or text prompts into downloadable 3D models using open-source AI/ML libraries.
Explore →Search, filter, and browse Pokémon by type and detail using the PokéAPI.
Explore →Predicts future electricity demand and price from historical data through a modern interface.
Explore →Personalized recommendations based on real-time weather conditions to help users make informed decisions.
Explore →A chatbot designed to help parents and elderly users navigate the digital world with confidence.
Explore →Evaluates and compares classification algorithms on the Indicators of Heart Disease dataset.
Explore →A reference implementation of core data analysis and machine learning algorithms in Python.
Explore →Suggests movies based on user preferences using the Nearest Neighbors algorithm.
Explore →Showcases fashion trends and lets users create personal style boards.
Explore →A scalable graph database system for secure healthcare data management with AI-powered insights.
Explore →Personalized fashion recommendations based on event details.
Explore →Browse stylish interior design ideas to inspire and enhance living spaces.
Explore →A flashcard app for efficient learning, with customizable cards and export options.
Explore →Flutter concepts including animations, API integration, and responsive design.
Explore →