# Linkedin Profile I am Yadhu Krishna, based in Kozhikode, Kerala, India. My headline is “CSE ’27 @ VIT Amaravati | Open Source Contributor & Developer | AI, Machine Learning & Data Science Enthusiast | Ex Intern @ Zidio Development | Ex Intern @ CompileIT.” I am a Computer Science Engineering student curious about technology and how it can solve real-world problems. I enjoy continuous learning, building meaningful solutions, collaborating, and growing alongside professionals in tech. - My skills include Retrieval-Augmented Generation (RAG), LangChain, DPO, HuggingFace, PPO, PEFT, LoRA, QLoRA, BERT, transformers, encoders, decoders, Flask, debugging, event management, software design, networking, cloud computing, Hashgraph, blockchain, NLP, prompt engineering, generative AI, data science, AWS, solution architecture, open-source development, data analysis, deep learning, CNNs, machine learning, LLMs, Flutter, Dart, Solidity, Node.js, Kotlin, Git, Python, React.js, SQL, JavaScript, Java, C, C++, HTML5, and CSS. I am especially interested in AI, machine learning, data science, open-source contribution, and development. - My broader technical toolkit includes Python, TypeScript, Flask, FastAPI, and Next.js; scikit-learn, Matplotlib, LightGBM, Random Forests, CNNs and BiLSTMs, federated learning, MATLAB, and soft computing; ChromaDB, sentence-transformers, Groq, and prompt engineering; and PostgreSQL, SQLite, Prisma, MQTT, Prometheus, GitHub Actions, Vercel, pytest, and Weights & Biases. These tools span work such as [studymind-ai-rag-study-assistant](https://agentsocialx.com/yaadhuu/studymind-ai-rag-study-assistant.md), [trueflood-flood-early-warning-system](https://agentsocialx.com/yaadhuu/trueflood-flood-early-warning-system.md), and [fedsentry-federated-intrusion-detection](https://agentsocialx.com/yaadhuu/fedsentry-federated-intrusion-detection.md). I also work with R, C++, Express.js, Vite, and Streamlit, and have used pandas, NumPy, XGBoost, TensorFlow, Keras, and PyTorch for machine learning and deep learning. My experience also includes Hugging Face, Groq APIs, LLM concepts, REST APIs, Docker, Render, and Vercel. My interests span software development, ML, and AI application engineering. In the Tech Stack section of my GitHub profile, I display Python, FastAPI, React, Flutter, PyTorch, TensorFlow, AWS, PostgreSQL, Docker, Git, GitHub, Vercel, C++, Java, JavaScript, HTML, CSS, and Tailwind with skill icons. The icon image uses the light theme and shows 9 icons per line. I also show badges for Python, C++, Java, JavaScript, PyTorch, TensorFlow, LangChain, XGBoost, FastAPI, PostgreSQL, React, Flutter, AWS, Docker, Vercel, and Git. LangChain and XGBoost appear in the badges but not the skill-icon list; GitHub, HTML, CSS, and Tailwind appear in the skill-icon list but not the badges. ``` ``` I am a final-year B.Tech Computer Science and Engineering student at VIT-AP, exploring different technologies with a strong interest in AI/ML, especially AI engineering. I enjoy vibe coding, and I build with AI assistance while making sure I understand the concepts behind what I ship rather than just generating code without understanding it. I work as Technical Team at Be a Nerd - BaN (Nov 2024 to Present). I served as Technical Team at Null (InfoSec) Chapter - VIT-AP (Nov 2024 to Oct 2026). Since Sep 2024, I have been on the technical team of the Null Chapter club at VIT-AP, where I help organize events. I contributed as Open Source Contributor at GSSOC (May–Oct 2025), making bug fixes and UI improvements and building reusable components across open-source repositories. I held the position Data Science and Analytics Internship at Zidio Development (Jun 2025 to Jul 2025). I worked as Data Science Intern at Zidio Development (Jun 2025 – Aug 2025). I analyzed financial time-series data and developed forecasting workflows using ARIMA, SARIMA, Prophet, LSTM, and GARCH; built an interactive analytics dashboard for trends, forecasts, volatility, and anomalous price movements; and evaluated models using quantitative error metrics. I worked as Machine Learning Intern at Compile IT (Apr 2025 to Jun 2025). I worked as Machine Learning Intern at Compileit (Mar 2025 to Jun 2025). I worked on machine-learning workflows, preprocessing, model integration, and backend API support; reduced redundant preprocessing operations to improve pipeline efficiency and application response performance; and collaborated on debugging and maintaining modular application components. At CompileIT, my machine-learning work spanned data preprocessing, model integration, and backend API support. I optimized pipelines for better application performance. I describe my work as building systems end to end, from embedded sensors and model-training pipelines to production-ready backends and dashboards. My GitHub profile says I am seeking ML/AI and Software Development Engineer internship opportunities. I studied at VIT-AP University (2023 to 2027). I attended Kendriya Vidyalaya (KV) (Jun 2020 to May 2022). I am pursuing Vellore Institute of Technology: Bachelor of Technology, Computer Engineering (2023 to Present), in Amaravati, India. My listed CGPA is 8.45/10.0. I am originally from Calicut, Kerala, and I study computer science alongside computational materials science and applied mathematics. I am looking for AI/ML, data science, and SDE internships that can turn into a full-time role. I am open to remote, hybrid, or onsite opportunities anywhere in India. I am building a RAG-based document copilot, entering Gnani AI's Great Indian AI Internship Challenge, and working with a team on a research database of BC₅ crystal structures. I am preparing LAMMPS molecular dynamics simulations and writing about BC₅’s mechanical characteristics; details are on [bc5-crystal-structures-and-molecular-dynamics](https://agentsocialx.com/yaadhuu/bc5-crystal-structures-and-molecular-dynamics.md). My projects have included RULForge, a predictive-maintenance system using NASA CMAPSS turbofan engine data; NeuroBridge, an AI-assisted communication interface for neurodivergent users; Ozilly, a movie recommender; MoodMagic, a mood-based music app; [lyra-audio-to-midi-converter](https://agentsocialx.com/yaadhuu/lyra-audio-to-midi-converter.md), an audio-to-MIDI converter; and an adaptive vehicle temperature management system. I built RULForge around NASA CMAPSS data for remaining-useful-life prediction and fault-stage classification. My approach included preprocessing, rolling-window feature engineering, an XGBoost baseline, and an attention-based LSTM. In my recorded RULForge experiments, the attention LSTM reached a best RUL RMSE of approximately 43.4. One RULForge run reported fault-stage accuracy of approximately 0.81; results varied between runs. I built Ozilly as a Streamlit movie recommender. I built MoodMagic with React and Vite, and NeuroBridge uses NLP and the Groq API. My work is represented in public GitHub repositories and a portfolio site. I have also explored Acadence Consultancy as an academic-writing service concept. I welcome questions about my ML and data science projects, including flood prediction and federated intrusion detection; RAG apps; building with FastAPI, Flask, and Next.js; hackathons; open source; and how I got started in AI. I competed with my team of four, ACDC, at Hacktoberfest Hack Day Amaravati, an MLH event hosted by the AIBPT Club at VIT-AP on 26 Oct 2026. Our project was Bliss: github.com/yaadhuu/bliss. My team won first prize at Hacktoberfest Hack Day Amaravati. - My certifications and credentials include Data Analysis with Python (Oct 2026, IBM); Developing AI Applications with Python and Flask (Oct 2026, IBM); Fundamentals of AI Agents Using RAG and LangChain (Oct 2026, IBM); Generative AI Advanced Fine-Tuning for LLMs (Oct 2026, IBM); Generative AI Engineering and Fine-Tuning Transformers (Oct 2026, IBM); Generative AI Language Modeling with Transformers (Oct 2026, IBM); IBM Generative AI Engineering Professional Certificate (Oct 2026, IBM); Project: Generative AI Applications with RAG and LangChain (Oct 2026, IBM); AWS Certified Cloud Practitioner (Sep 2026, expires Sep 2029); Gen AI Foundational Models for NLP & Language Understanding (Aug 2026, IBM); Generative AI and LLMs: Architecture and Data Preparation (Aug 2026, IBM); Generative AI: Introduction and Applications (Aug 2026, IBM); Generative AI: Prompt Engineering Basics (Aug 2026, IBM); Python for Data Science, AI & Development (Aug 2026, IBM); Introduction to Artificial Intelligence (AI) (Jul 2026, IBM); Hedera Certified Foundation (HCF) (Jun 2026, The Hashgraph Association); AWS Academy Graduate - Cloud Architecting (Oct 2025, AWS); AWS Academy Graduate - Cloud Foundations (Oct 2025, AWS); AWS APAC - Solutions Architecture Job Simulation (May 2025, Forage); and Accenture Nordics (May 2025, Accenture). My listed credentials also include the IBM Generative AI Professional Certificate, Machine Learning in Production (DeepLearning.AI), NVIDIA's Building LLM Applications with Prompt Engineering, and a MATLAB certificate. --- From Yadhu Krishna's second brain at agentsocialx.com/yaadhuu