Professional Journey
My experience in AI research and development
Software Engineer I
Arrant TechLead AI Application Developer for LifeConnectApp, an autonomous AI agent system that monitors and automates social media interactions across multiple platforms. Building enterprise integrations using Workday Extend and developing secure authentication systems.
Key Achievements
- Lead AI Application Developer for LifeConnectApp, an autonomous AI agent system that monitors and automates social media interactions across multiple platforms (Google, LinkedIn, Facebook, Instagram)
- Architected core AI system components including GPT-4-powered NLP, real-time monitoring modules, and automated response generation capabilities
- Building enterprise integrations using Workday Extend to streamline business workflows and enhance system interoperability — including Workday HCM data access and custom Workday UI components
- Built secure authentication systems with JWT and OAuth 2.0, ensuring data privacy and encrypted storage solutions with MongoDB
- Developing Virtual Clean Rooms (VCR) Management System, a full-stack web application (Python + JavaScript) to digitize pharmaceutical clean room specification workflows
- Building ArrantMeet, an internal Workday Extend-based meeting management and scheduling application
- Managing multiple concurrent projects including Java-based applications while collaborating effectively in Jira-based agile development workflows
Artificial Intelligence Prompt Engineer
Community Dreams FoundationVolunteer contributor developing and refining AI prompts for ML-driven simulations, improving model reliability and collaborating on architecture optimization.
Key Achievements
- Volunteer contributor developing and refining 100+ AI prompts for ML-driven simulations, improving model reliability by 30%
- Collaborate on architecture optimization discussions to enhance platform scalability and performance
Artificial Intelligence Research Intern
Tokenization Challenges in Multilingual GPT
Kakatiya Institute of Technology and ScienceOptimized tokenization in multilingual language models, improving efficiency by 60% for non-English languages. Developed language-specific preprocessing pipelines, reducing token usage per prompt from 70-100 to 18-25.
Key Achievements
- Developed language-specific preprocessing, cutting prompt length and improving NLP efficiency by 60%
- Reduced token usage per prompt from 70-100 to 18-25 via Telugu script vs. transliterated text analysis
- Enhanced response speed and computational efficiency using transliteration-based preprocessing
- Published insights in ICIIRS-23, addressing multilingual challenges in AI text generation models
Machine Learning Research Intern
Fraud Detection in Automobile Insurance Claims using Machine Learning Algorithms
Kakatiya Institute of Technology and ScienceEngineered ML pipeline for fraud detection achieving 78% accuracy and 81% AUC using ensemble methods. Implemented data balancing and feature engineering techniques to optimize model performance on imbalanced datasets.
Key Achievements
- Developed ML models (RF, KNN, DT, SVM) for fraud detection, selecting Random Forest (78% accuracy, 81% AUC) as the optimal model
- Conducted extensive evaluation despite data imbalance, demonstrating RF's superior performance over other models
- Published findings in ICIIRS-23, showcasing ML's impact on real-world insurance fraud detection
Data Science Intern
3 CORTEX TechnologiesApplied innovative AI optimization techniques to solve complex challenges, improving project outcomes by 75%. Created interactive data visualizations to communicate insights and enhance cross-functional collaboration.
Key Achievements
- Applied inventive thinking techniques to tackle AI and ML challenges, boosting project outcomes by 75%
- Created robust visualizations tailored to specific challenge statements, improving clarity and fostering teamwork
- Developed optimized code solutions for AI and ML applications, achieving a 60% efficiency increase
Computer Vision Research Intern
A Quantitative Analysis of Basic vs. Deep Learning-based Image Data Augmentation Techniques
Kakatiya Institute of Technology and ScienceConducted research on deep learning-based image augmentation techniques, achieving 98.57% accuracy on MNIST dataset. Implemented and evaluated various data augmentation strategies to improve model robustness and generalization.
Key Achievements
- Conducted a quantitative analysis of basic vs. deep learning-based image data augmentation techniques on the MNIST dataset
- Achieved a highest accuracy of 98.57% and loss value of 0.301 using brightness adjustment
- Evaluated computational burden, storage requirements, and performance to recommend cost-effective augmentation strategies
- Published findings in IEEE ICSES 2021, contributing to enhanced robustness in deep learning pipelines
Technical Expertise
Core competencies and technologies
AI & Machine Learning
Programming
Data & Analytics
Academic Background
Foundation in artificial intelligence and computer science
University at Buffalo, State University of New York
Master of Science in Engineering Science
Artificial Intelligence
Pursuing advanced studies in artificial intelligence with focus on deep learning, natural language processing, and computer vision. Conducting research on multilingual NLP and reinforcement learning applications.
Key Courses
Kakatiya Institute of Technology and Science
Bachelor of Technology
Computer Science
Graduated with honors in Computer Science with specialization in artificial intelligence and machine learning. Completed thesis on 'Tokenization Challenges in Multilingual GPT' with distinction.
Key Courses
Professional Development
Continuous learning and skill enhancement
Deep Learning Specialization
Coursera - deeplearning.ai
2022
Completed 5-course specialization covering neural networks, CNN, RNN, and ML project structuring.
TensorFlow Developer Certificate
2022
Professional certification demonstrating proficiency in building TensorFlow models.
Machine Learning Engineering for Production (MLOps)
Coursera - deeplearning.ai
2023
Specialized training in deploying ML models to production environments.
Natural Language Processing Specialization
Coursera - deeplearning.ai
2022
Comprehensive training in modern NLP techniques and applications.
Computer Vision Nanodegree
Udacity
2021
Advanced computer vision techniques including object detection and image segmentation.
Data Science Professional Certificate
IBM
2021
Comprehensive data science training covering the entire data science workflow.