Mohd Zamin Quadri
MSc Mathematics in Science & Engineering at TU Munich. Building intelligent systems at the intersection of mathematics, machine learning, and software engineering.
About Me
I am a Master's student in Mathematics in Science and Engineering at the Technical University of Munich, with a deep passion for applying mathematical rigor to real-world AI challenges.
My journey spans from theoretical mathematics at Aligarh Muslim University to hands-on AI engineering at BP-ITCS, where I build production-grade machine learning systems. I have experience in NLP, computer vision, time-series analysis, and end-to-end MLOps pipelines.
I thrive at the intersection of mathematics and software engineering, using tools like Python, TensorFlow, PyTorch, and SQL to transform complex data into intelligent systems. From optimizing neural network architectures to building interactive dashboards, I bring a data-driven approach to every problem.
AI & Machine Learning
Building production-grade ML pipelines, from data preprocessing to model deployment with TensorFlow, PyTorch, and scikit-learn.
Mathematics & Research
Strong foundation in mathematical optimization, statistics, numerical methods, and neural network theory from TU Munich.
MLOps & Engineering
End-to-end ML systems with CI/CD, Docker, model monitoring, and automated retraining pipelines for production environments.
Data Analytics & BI
Transforming complex data into actionable insights with Power BI, advanced Excel, SQL, and statistical analysis.
Work Experience
A journey through research, engineering, and data science across academia and industry.
Working Student - AI Engineer
BP-ITCS (IT Consulting & Solutions)
- Developing and deploying production-grade ML models for business process automation and predictive analytics
- Building end-to-end data pipelines and implementing MLOps best practices for model monitoring and retraining
- Collaborating with cross-functional teams to translate business requirements into AI-driven solutions
Master's Thesis Researcher
Technical University of Munich (TUM)
- Conducted research on neural network identifiability analysis, investigating theoretical properties of deep learning architectures
- Developed mathematical frameworks for analyzing convergence and uniqueness properties of neural network solutions
- Implemented computational experiments using PyTorch to validate theoretical results on synthetic and real datasets
Seminar Participant - Advanced ML
Technical University of Munich (TUM)
- Participated in advanced seminar on modern machine learning topics including transformers, attention mechanisms, and self-supervised learning
- Presented research paper reviews and critical analyses of state-of-the-art deep learning methods
Research Assistant - Programming
Technical University of Munich (TUM)
- Assisted in developing programming exercises and course materials for undergraduate computer science modules
- Created automated testing frameworks and grading scripts for student submissions
- Provided tutoring and support for students in programming fundamentals and data structures
Intern - Data Analytics
AUDI AG
- Analyzed supply chain data to identify bottlenecks and optimize logistics processes using advanced analytics
- Built interactive Power BI dashboards for real-time KPI monitoring and executive reporting
- Implemented VBA automation scripts reducing manual data processing time by 40%
Research Assistant - MATLAB
Technical University of Munich (TUM)
- Developed numerical simulation tools in MATLAB for mathematical modeling research projects
- Implemented finite element methods and optimization algorithms for engineering applications
Summer Research Intern
IISER Bhopal
- Conducted research in mathematical analysis and computational methods under faculty supervision
- Applied analytical and numerical techniques to solve research problems in applied mathematics
Featured Projects
A selection of projects spanning machine learning, deep learning, NLP, data analytics, and MLOps.
MLOps End-to-End Pipeline
Complete MLOps pipeline with automated training, model versioning, CI/CD, Docker containerization, model monitoring, and drift detection for production ML systems.
NLP Text Classification with Transformers
Fine-tuned BERT and RoBERTa models for multi-class text classification, achieving state-of-the-art accuracy with custom training pipeline and comprehensive evaluation.
Neural Network Identifiability Analysis
Master's thesis research on theoretical properties of neural network identifiability, investigating convergence and uniqueness of deep learning solutions.
Insurance Claims Prediction
End-to-end ML pipeline for insurance claim prediction using ensemble methods, feature engineering, and model interpretability with SHAP analysis.
Supply Chain Analytics Dashboard
Interactive analytics dashboard for supply chain KPI monitoring, demand forecasting, and bottleneck identification using real-world logistics data.
Battery SOC Estimation with ML
Machine learning approach for battery State of Charge estimation using time-series sensor data, LSTM networks, and feature engineering for EV applications.
Technical Skills
A comprehensive toolkit spanning programming, ML frameworks, data analytics, and infrastructure.
Programming & Core
Machine Learning & AI
Data Science & Analytics
Tools & Infrastructure
Also experienced with:
Academic Background
Munich, Germany
MSc Mathematics in Science and Engineering
Technical University of Munich (TUM)
Specializing in machine learning, optimization, and numerical analysis. Coursework includes deep learning, statistical learning theory, advanced numerical methods, and mathematical foundations of ML.
- Master's Thesis: Neural Network Identifiability Analysis
- Advanced Seminars in Machine Learning
- Research Assistant in Programming & MATLAB
Aligarh, India
BSc (Hons) Mathematics
Aligarh Muslim University (AMU)
Strong foundation in pure and applied mathematics including real analysis, linear algebra, differential equations, probability theory, and computational mathematics.
- Summer Research Intern at IISER Bhopal
- Focus on Computational & Applied Mathematics
- Dean's List Recognition
Certifications & Courses
Improving Deep Neural Networks
Hyperparameter tuning, regularization, optimization algorithms, batch normalization, and practical aspects of building deep learning systems.
Neural Networks and Deep Learning
Foundations of deep learning — building and training neural networks, vectorization, gradient descent, and understanding forward/backward propagation.
Python for Data Analysis
Data manipulation and analysis with Python, including Pandas, NumPy, data cleaning, transformation, and exploratory data analysis techniques.
Introduction to SQL
Fundamentals of SQL for data querying, filtering, aggregation, joins, subqueries, and database management for analytics workflows.
Introduction to Python
Core Python programming concepts including data types, control flow, functions, OOP, file handling, and libraries for data science.
Get In Touch
Interested in collaborating or have a question? I'd love to hear from you. Let's build something together.