Stefan Stavrev

Worked full-time at SAP and later at Broadcom, as a consultant through Avenga. More details in the SAP and Broadcom experience sections below.

- As part of VMware Professional Services Center of Excellence (PSCoE), I worked on a variety of projects with diverse technologies, with focus on vRealize Automation (vRA) and vRealize Orchestrator (vRO) to automate infrastructure and cloud processes based on customer needs. - Implemented TypeScript/JavaScript vRO workflows interacting with VMware and third-party APIs such as: vRA, HCX, NSX, vCenter, vROps, and Ansible API. I also worked on Java and Go projects.

- As part of the SAP Connectivity and Destinations teams I worked on a variety of projects with diverse technologies. - Developed a Java servlet application for availability monitoring. - Developed a monitoring solution for BOSH VMs in the form of bash scripts interacting with Java APIs to collect and process metrics, and pushing metrics to Dynatrace. - Developed Node.js applications (SAPUI5, TypeScript), a main Luigi application and two micro-frontend applications. - Other: python, bash, maven

Worked full-time at SAP as a consultant through Avenga. More details in the SAP experience section below.

- As part of the SAP Neo Evolve team, I maintained and extended a web application used for deploying SAP applications. My work focused on both the SAPUI5 frontend and Java backend services. - Added and removed SAPUI5 components to support new Java runtimes, ensuring compatibility across SAP landscapes. - Implemented unit tests for both frontend and backend components. - Analyzed Jenkins pipeline logs, identified build failures, and fixed bugs.

- Designed and lectured a Python programming course for around 20 students, with regular homework assignments and a final project. - Presented a webinar based on my previous work "Automated Data Science".

- Provided DevOps services as part of the SAP Lifecycle Management Team for the SAP Cloud Platform. - Supported/extended existing Concourse pipelines (YAML) for lifecycle management of various products. - Maintained SAP landscapes with internal command line tools. - Developed and optimized Python and bash scripts. - Monitored pipelines, analyzed logs and did root cause analysis to identify problems in failing pipelines. - Used Docker for local testing and validation. - Managed clusters in Gardener UI.

- Developed two MVPs: Data Science Platform (Django web app) and Data Science Knowledge Base (Flask API). - Presented my work at the ISTA 2020 Conference and on a webinar at Brainster Data Science Academy. - The Data Science Platform was a similar idea to RapidMiner where users can create and execute Data Science end-to-end pipelines with drag-and-drop. - Designed and developed a Python framework for creating end-to-end ML pipelines as DAGs composed of reusable OOP operators.

- Designed and developed a Python framework for creating and executing end-to-end ML pipelines as DAGs composed of reusable OOP operators, in a bottom-up way by extracting patterns from real-world use cases. - Implemented atomic operators for ingestion, aggregation, preprocessing, dimensionality reduction, outliers, categorical and numeric feature engineering, ML algorithms, and also composite operators including column transformer, fit-transform pipeline, model selection, HPO, validation, etc.

- Established foundations and roadmap for the new Data Science team. - Designed internal process based on CRISP-DM and initiated standardization inspired by the NIST Big Data standards. - Collaborated with managers, domain experts, data engineers, IT and security. - Applied tools from the Python and Hadoop ecosystems, including NumPy, pandas, matplotlib, scikit-learn, Jupyter Notebook, Hue, Hive, Pig and Impala. - Conducted data exploration, visualization, data preparation and ML on CAN bus sensor data.

- Development of core system for mobile terminal transactions and payments in C++. - Designed efficient data representation schemes for optimized data transfer. - Tested and validated functionality using mobile terminals.

Full stack web development of a social network analysis platform.

- Development of evolutionary optimization framework and its application on problems such as Knapsack, Traveling Salesman and Cutting Stock. - The framework was implemented in C++ with Java and C# ports, involving daily cross-language development and integration.

- Implemented around 30 machine learning algorithms in MATLAB based on the book "Computer Vision: Models, Learning, and Inference" by Simon J. D. Prince. - Wrote a comprehensive document with code and explanations. - Received positive feedback from Prof. Prince. - My code became a useful reference for students.

- Reviewed and graded Java-based homework assignments implementing image processing algorithms for the Image Processing course in the Bachelor's program. - Provided feedback and support to over 20 students.

- Implemented many image processing algorithms in C++ for both grayscale and color images: histograms, point operations, filters, morphological operations, detection of edges, lines and corners, etc. - Added various improvements: regions of interest, multithreading, command line tools, etc. - Unit testing - Code documentation

While working as software engineer in the industry, I passed two exams in the first semester of the Bioinformatics Master program with high grades: - Supervised Machine Learning - Probabilistic Graphical Models

I completed the first semester (5 courses) of the master program Interactive Media: - Advanced Computer Graphics - Hypermedia - Software Design Methods - Human-Computer Interaction - Semester Project: I ported FLANN (Fast Library for Approximate Nearest Neighbors) from C++ to Java

Grade: 9.56 (10.0 is highest) My bachelor thesis focused on studying a complete textbook on quantum computing and presenting the acquired knowledge through a comprehensive written report and oral defense.

I completed the first academic year with high grades. Coming from a background in 3D computer animation, I wanted to gain a holistic understanding of the entire movie production process.