Azar Dastouri

- Application of advanced ML, AI, Data Science in DFM - MLOps - Generative AI & LLM solutions for data automation - Computer Vision - PCB Design optimisation - Factory SMT/FATP process Data monitoring & Alerts - database design/data Pipelines / Cloud infrastructure

• Competence lead of applied data science in ASML Wilton • Architecting solution frameworks to develop, deploy and implement data-driven ML models. • Predictive models for manufacturing and production data e.g. predictive maintenance, defectivity detection, failure analysis, … • Data modeling and supervised/unsupervised Machine learning (Classification, Regression, Data clustering (K-means), tSNE, PCA/ICA, neural network, time series analysis,…) • Simulation/Software developer: Matlab, Python(pandas, NumPy, Scikit-learn, Keras,…), Sql, spotfire, Spark, Google cloud platform, TensorFlow, … • Sensor data modeling and analytics • Mathematical and statistical modeling (model estimation and optimization, signal processing, noise detection, design of experiments, probability theory, uncertainty analysis, Bayesian framework) • Semiconductor, lithography and metrology • Database design and management

-Development, algorithm design and implementation of discrete adjoint formulation and optimisation technique in an adjoint solver for a commercial CFD code - Improving the efficiency (run time and memory) and robustness of the optimization solver for big size industrial test cases (parallelization using MPI) - Embedded system implementation, Algorithm design for external function call, Pattern recognition (Python) -Neural network augmented inverse problem for uncertainty quantification of model parameters.

Developing data models and simulations in a design context for various industrial projects -Machine Learning and Data Analysis (data driven models-model reduction-neural network) -Statistical Analysis (Experimental design and sampling-Hypothesis tests-probability theory -Bayesian Statistics) -Mathematical Modeling of Physical/Mechanical problem

• Optimum design of sewer network. • Geographic Information System (GIS) data analysis