Resume

Education

Vanderbilt University | Nashville, TN, USA –> Aug. 2017 - Mar. 2022

• Ph.D. in Civil Engineering (GPA: 3.88)
• Thesis title: Physics-informed machine learning for uncertainty quantification and optimization
  • Explored the integration of physics-based models and experimental data to craft diverse physics-informed machine learning models. These models, designed for optimization under uncertainty, achieved a remarkable 300x reduction in computational effort while preserving accuracy.
  • Spearheaded the development of adaptive sampling and multi-level Bayesian calibration strategies. These advancements were applied to a complex multivariate time-dependent multi-component system, resulting in a noteworthy enhancement of computational efficiency and accuracy by a factor of 120 and 16%, respectively.

Delft University of Technology | Delft, The Netherlands –> July 2015 - Nov. 2016

• MSc in Applied Mathematics

University of Erlangen-Nuremberg | Erlangen, Germany –> Aug. 2014 - May 2015

• MSc in Computational Engineering

Bilkent University | Ankara, Turkey –> Sep. 2010 - June 2014

• BSc in Mechanical Engineering

Relevant Experience

Capital One

• Principal Associate, Data Scientist – Applied Research –> Nov. 2023 – Present AI Foundations Team

  • My work encompasses pretraining, fine-tuning, and optimizing both training and inference processes, leveraging Kubernetes for efficient resource management and scalability.
  • My expertise lies in Natural Language Processing (NLP), with a strong focus on cloud-based machine learning solutions. I am deeply engaged in MLOps engineering, which includes designing robust inference solutions and training pipelines.
  • Building Foundation Models using multi-node multi-process architectures via Kubernetes.
  • Responsible for building and maintaining the infrastructure required for hosting these large language models, ensuring their seamless integration and performance within our financial ecosystem.

• Principal Associate, Data Scientist –> Nov. 2022 – Nov. 2023

  • Collaborated closely with a cross-functional team of data scientists, software engineers, and product managers to deliver precise forecasts for Comprehensive Capital Analysis and Review (CCAR) and routine business operations. Executed pivotal adjustments to the model forecast, resulting in a significant total allowance impact of $600M.
  • Applied a diverse technology stack, including Python, AWS, and Spark, to enhance the precision of loss forecasts. Conducted comprehensive sensitivity analysis on account-level loss models across different economic scenarios, leading to the identification and resolution of a data issue with a consequential impact of $700M in provision.
  • Engineered a custom Continuous Integration/Continuous Deployment (CICD) pipeline to create a summarization and visualization tool. This tool enables the broader team to efficiently summarize model outputs and visualize these summaries on Tableau, fostering streamlined communication and decision-making processes.

InspiRD, Inc.

• Machine Learning, Modeling and Simulation Engineer –> Jan. 2022 – Oct. 2022
  • Engineered machine learning models for both regression and classification tasks, seamlessly integrating them into the company’s simulation framework. These models significantly improved prediction accuracy and decision-making processes.
  • Collaborated with domain experts to develop novel algorithms for uncertainty quantification and optimization. Leveraged Python, MATLAB, and TensorFlow to create robust solutions that addressed real-world challenges.
  • Conducted extensive sensitivity analyses and explored multi-objective optimizations, ensuring robustness and reliability in complex systems.

Skills

• Programming Languages: Python, MATLAB, Fortran, C++, Java, R, SQL
• Data Tools: AWS, Spark, Matplotlib, Seaborn, Plotly, Tableau
• Machine Learning: TensorFlow, PyTorch, Keras, pandas, numpy, scikit-learn, XGBoost, LightGBM
• Deep Learning: CNN, RNN, LSTM, GANs, Transfer Learning
• Technologies/Tools: Git, VSCode, Jupyter Notebook, Docker, Abaqus FEA, COMSOL, LaTeX
• Statistical Analysis: Hypothesis Testing, Regression Analysis, Time Series Analysis
• Languages: Turkish (native), English (fluent), German (intermediate)

Find the complete resume here.