My Projects
Machine Translation
Developed an NLP model to translate Russian to English with high accuracy, enabling seamless cross-lingual communication.
Impact: Achieved 95% BLEU score, used in multilingual research platforms.
Machine Translation System
Project Overview
Designed and implemented a custom Neural Machine Translation (NMT) system for Russian-to-English translation, achieving state-of-the-art performance metrics.
Challenge
Create a high-accuracy translation system that preserves linguistic nuances while being computationally efficient.
Solution
Hybrid architecture combining custom RNNs with pre-trained transformer models for optimal performance.
Technical Implementationb
- Designed sequence-to-sequence model with GRUs and ReLU activation for efficient language translation
- Integrated 11M parameter Hugging Face transformer model to enhance accuracy
- Achieved 95% BLEU score in evaluations of linguistic fluency and adequacy
- Optimized training pipeline, reducing training time by 65% (12hrs → 4hrs)
- Implemented visualization tools using Matplotlib to analyze loss convergence
- Deployed model in multilingual research platforms for practical use
Technologies Used
Waze User Churn Analysis
Advanced analytics project to predict and prevent user churn for navigation app Waze.
Impact: Developed actionable retention strategies through predictive modeling.
Waze User Churn Analysis
Project Overview
Conducted an end-to-end capstone project as part of the Google Advanced Data Analytics Professional Certificate, focused on identifying user churn in the Waze application and developing strategies for retention.
Challenge
Identify at-risk users and develop data-driven retention strategies to reduce churn rate.
Solution
Advanced predictive modeling and statistical analysis of user behavior patterns.
Technical Implementation
- Executed comprehensive EDA using matplotlib and seaborn to visualize churn trends and user behavior
- Applied advanced statistical techniques (ANOVA, ANCOVA, MANOVA, MANCOVA) to evaluate relationships
- Built and evaluated multiple ML models with XGBoost outperforming others in accuracy
- Authored executive summaries to communicate findings to non-technical stakeholders
- Generated strategic insights for improving user retention through predictive modeling
Technologies Used
Crime Prediction AI
Created a predictive model to forecast crime hotspots using historical data, aiding law enforcement resource allocation.
Impact: Reduced response times by 15% in simulated urban scenarios.
Crime Prediction AI System
Project Overview
Developed an advanced AI system combining predictive modeling and large language models to forecast crime patterns and enhance law enforcement strategies.
Challenge
Improve public safety through data-driven crime prediction while maintaining AI ethics.
Solution
Hybrid AI system combining XGBoost for predictions and LLMs for strategic insights.
Key Achievements
- Integrated XGBoost with 7B-parameter LLM for comprehensive crime forecasting
- Conducted comparative analysis of Logistic Regression, Random Forest, and XGBoost
- Implemented automated crime reporting and strategic advice generation using NLP
- Presented at All India Police Science Congress to senior law enforcement officials
- Selected for World Criminology Conference based on innovative methodology
Implementation Details
Data Pipeline
- Historical crime records
- FIR narratives and legal SOPs
- Facial biometric data for pattern recognition
- Gandhinagar authenticated crime dataset
Model Architecture
- XGBoost for primary predictions
- 7B-parameter LLM for strategic insights
- Vector database for knowledge retrieval
- CNN submodel for visual patterns
Technologies Used
AI Assistant
Built a personal AI assistant capable of executing background tasks, system-level commands, and voice-triggered automation for enhanced personal productivity.
Impact: Reduced daily manual workload by automating over 75% of repetitive actions.
Personal AI Assistant
Project Overview
Developed a lightweight personal AI assistant capable of running in the background, automating daily tasks, and executing system commands through voice interactions.
Challenge
Simplify personal workflow by reducing reliance on manual repetitive actions and system navigation.
Solution
Created an AI agent that integrates with the OS, listens for voice commands, and automates system-level functions in real time.
Key Features
- Runs silently in the background and triggers on custom wake words
- Executes system commands (file operations, application launch, etc.)
- Voice-controlled automation for tasks like emails, reminders, media playback
- Learns frequent tasks and optimizes based on usage patterns
- Secure offline mode for local command processing
Technologies Used
Emotion Analysis
Built a deep learning system to detect emotions in text and facial expressions, enhancing human-computer interaction.
Impact: Improved sentiment analysis accuracy by 20% for customer feedback systems.
Emotion Analysis System
Project Overview
Developed a multimodal emotion recognition system combining facial expression analysis with text sentiment detection for comprehensive emotion understanding.
Challenge
Improve accuracy of emotion detection beyond traditional sentiment analysis.
Solution
Hybrid model combining computer vision for facial analysis with NLP for text sentiment.
Technical Implementation
- Facial emotion recognition using CNN architecture with OpenCV
- Text sentiment analysis using BERT transformer model
- Multimodal fusion layer to combine visual and textual signals
- Real-time processing pipeline for live emotion detection
- Custom dataset creation with labeled emotional expressions
Technologies Used
Smart City Dashboard
Created an AI-powered dashboard for urban automation and energy efficiency in smart city infrastructure.
Impact: Presented at IEEE conference on smart grid systems.
Smart City Dashboard
Project Overview
Developed an integrated dashboard system for smart city management, combining IoT sensor data with AI analytics for urban optimization.
Challenge
Centralize and make sense of diverse urban data streams for efficient city management.
Solution
Unified dashboard with real-time monitoring, predictive analytics, and automated controls.
System Components
- Energy consumption monitoring and optimization simulation
- Traffic pattern analysis and congestion prediction
- Waste management route optimization
- Smart grid dual channel communication for transformers using Azure AI
- Environmental quality monitoring (air, noise, water)
Technologies Used
Project Categories
AI & Machine Learning
Cutting-edge artificial intelligence projects including NLP, computer vision, and predictive modeling.
Data Science
Advanced analytics, visualization, and data-driven decision making systems.
Security & Forensics
Public safety applications, predictive policing, and cybersecurity solutions.