AI & Data Science undergraduate with published research in LLM hallucination reduction, cybersecurity topic modeling, and healthcare analytics using Machine Learning & Deep Learning. Currently working as an AI Automation Engineer at Softvence Delta, building end-to-end automation systems using n8n, Zapier, Make, OpenAI, Anthropic Claude, and Google Gemini APIs. Passionate about Large Language Models, AI workflow automation, NLP, and scalable intelligent systems that solve real-world business problems.
- Building AI automation systems using n8n, Zapier, Make, OpenAI, Claude, and Gemini APIs.
- Researching LLMs, NLP, hallucination reduction, and AI workflow optimization.
- Developing intelligent applications with Python, SQL, Deep Learning, and Machine Learning.
- Delivering client-focused automation solutions and scalable AI integrations.
- Computer Vision: CNN, Transfer learning, GAN.
- Machine Learning: Naive Bayes, Logistic Regression, SVM, Decision Trees, KNN.
- Neural Network: LSTM, RNN, GRU.
- AI Automation: n8n, Zapier, Make (Integromat).
- Large Language Models: Ollama, OpenAI, Gemini, Qwen, DeepSeek.
- NLP & Transformers: BERT, Self-Attention, Text Classification.
- Deployment & Integration: FastAPI, Model APIs, Workflow Automation.
- Designed a claim-level hallucination detection and correction framework for LLMs.
- Applied atomic claim extraction with self-evaluation and consistency checking.
- Used belief graphs and preference based fine-tuning to improve factual accuracy.
- Analyzed 2,300+ cybersecurity papers (2005–2025).
- Applied LDA, K-Means, Hybrid, and BERTopic.
- Compared models using coherence and clustering metrics.
