👋 Hello! I'm Sam, a Full Stack Data Scientist with a background in Chemical Engineering, currently pursuing an M.Sc. in Polymer Science at Freie Universität and Humboldt Universität Berlin. I'm passionate about solving complex problems at the intersection of data science, explainable AI and materials science.

• 🔬 Full Stack Data Scientist with experience in NLP, medical entity extraction, and patient-study profile matching
• 🎓 Currently pursuing M.Sc. in Polymer Science at FU and HU Berlin
• 👨‍🏫 Regular corporate trainer in Generative AI, Causal Discovery and Inference, Linear Algebra, and Machine Learning
• 💻 Proficient in Python, with expertise in Pandas, NumPy, Langchain, and FastAPI
• 🧮 Strong background in mathematical modeling of physical systems and optimization
• 🤖 Experience with Large Language Models (RAG and Agent)
• 🌍 Multilingual: Fluent in English, Hindi, Malayalam; Proficient in German, Tamil, and Telugu; still dabbling with French and Spanish!

I'm currently working on exciting projects that combine my expertise in data science with my studies in Polymer Science:

• 🧪 Applying machine learning techniques to index and search polymer material properties
• 🔍 Developing recommendation engines for polymer materials based on required properties
• 🔗 Integrating knowledge from thermodynamics, chemistry, and physics to create comprehensive models
• 📊 Utilizing data-driven approaches to accelerate materials discovery and optimization
• 🔍 Exploring Causal Discovery and Inference techniques in materials science and beyond

This interdisciplinary research aims to bridge the gap between traditional polymer science, causal inference, and cutting-edge machine learning techniques, potentially revolutionizing how we design and select materials for specific applications.

• Python (Pandas, NumPy, Langchain, FastAPI)
• Mathematical modeling and optimization
• Large Language Models (RAG and Agent)
• Natural Language Processing
• Azure DevOps and AWS
• Data reconciliation and process optimization
• Image processing and deep learning
• Polymer science and characterization
• Causal Discovery and Inference

Here are some projects I've worked on:

1. Polymer Property Predictor

   • Machine learning model to predict polymer properties based on chemical structure

2. Medical Entity Extraction

   • NLP project for extracting medical entities from clinical texts

3. Patient-Study Profile Matching

   • AI-powered system to match patient profiles with suitable clinical studies

4. Water Network Management Optimization

   • Large-scale integer optimization for efficient water network scheduling

5. Blast Furnace Data Reconciliation

   • Data reconciliation project for improving blast furnace efficiency

• 💼 LinkedIn: linkedin.com/in/sammathewai
• 🐙 GitHub: github.com/samiit

• 📚 I'm deeply interested in causal inference and its applications in data science. Judea Pearl's "The Book of Why" has been a significant influence on my thinking in this area.
• 🧠 I love exploring the intersection of machine learning, causal inference, and materials science.
• 📖 My reading interests span history, philosophy, technology, and scientific advancements.
• 🧗 In my free time, you can find me hiking or cycling.
• 🌍 I've lived and studied in India, Germany, and the Netherlands.
• 🧬 I'm fascinated by the potential of combining materials science with machine learning and causal inference to solve real-world problems.

Feel free to explore my repositories and don't hesitate to reach out if you'd like to collaborate on a project, discuss the exciting world of polymer science and machine learning, or explore the depths of causal inference!