Radu Balaban, Software Architecture Developer in Baia Mare, Maramureș County, Romania
Radu Balaban

Software Architecture Developer in Baia Mare, Maramureș County, Romania

Member since May 17, 2017
Along with a master's degree in machine learning from Georgia Tech, Radu is a software engineer with over 15 years of experience in the industry. He's passionate about bringing the latest advances in computer science to performant and reliable real-world applications.
Radu is now available for hire

Portfolio

Experience

Location

Baia Mare, Maramureș County, Romania

Availability

Part-time

Preferred Environment

Linux, IntelliJ IDEA, Visual Studio Code

The most amazing...

...thing I've coded uses the Parzen density estimate to create painting-like time-lapse videos from still photographs.

Employment

  • Front-end Engineer

    2019 - 2019
    KF Software Solutions, Inc. (via Toptal)
    • Developed a new web single-page application (client) that allows the management of data related to forestry stock management.
    • Implemented a functionality such as data viewing, editing, and searching.
    • Wrote support for exporting reports in Excel, PDF or CSV formats.
    • Developed a new application that significantly improved the performance of the system compared to the previous implementation (which was a server-centric).
    • Added functionality to another part of the system: an offline-capable React mobile application.
    Technologies: JavaScript, React, React Hooks, Redux, Redux Offline, Material-UI
  • Machine Learning Engineer

    2018 - 2019
    Key Network Services, Ltd. (via Toptal)
    • Developed an ML model that validates medical prescriptions issued at vet clinics. The model can identify the most likely mistakes in the prescription and also suggest missing items.
    • Created the interface for domain experts to validate and improve the model.
    • Added support for auditing the prescription issuing flow.
    Technologies: .NET, VB.NET, Math.NET Numerics, Java
  • Machine Learning Engineer

    2018 - 2018
    Fintech Startup (via Toptal)
    • Built a model that computes the optimal portfolio given certain risk tolerance.
    • Computed technical indicators such as SMA, Bollinger bands, and did feature engineering to enhance input data.
    • Ran experiments in order to evaluate the predictive value of different machine learning models related to securities prices.
    Technologies: Python, Pandas, Scikit-learn, Jupyter Notebooks, Matplotlib
  • Machine Learning Engineer

    2018 - 2018
    Consumer Internet Labs (via Toptal)
    • Implemented a neural network-based digit recognition system for a web application running on mobile devices.
    • Built a system that supports recognizing multiple digits drawn by touch on the mobile screen and the recognition process runs entirely on the client-side.
    • Ensured a superior accuracy by sending the system logs with failed digit classifications to a server written in Flask and then this data is then used to periodically retrain the network.
    Technologies: TypeScript, Scikit-learn, Python, Flask
  • Front-end Engineer

    2017 - 2017
    Crypto Plus Certified (via Toptal)
    • Developed a web single-page application (SPA) client app for managing assets across multiple exchanges.
    • Implemented API connectivity—both towards the application server and towards external services (exchanges).
    • Implemented the payments flow.
    • Made the application mobile-friendly by using responsive components.
    Technologies: TypeScript, React, Redux, SVG, WebSockets
  • Machine Learning Engineer

    2014 - 2017
    E&P Data Sense
    • Implemented a cross-platform application for monitoring streams of data from a variety of sensors in drilling or production oil and gas installations. The system analyzes the data and can send notifications in real-time.
    • Created an anomaly detection system for finding hazardous or deficient operation parameters in order to send automated alerts to supervisors.
    • Developed a sand detection feature that monitors the sand production in the well (sand can quickly deteriorate equipment). The detection process uses data from an acoustic sensor connected to the pipeline.
    Technologies: R, Python, Data Science, Machine Learning
  • Software Architect

    2011 - 2017
    Eelloo
    • Led the development of a new product: a job search application based on psychological profile matching. It uses psychological testing results from the company’s main product to recommend the most appropriate jobs and career paths to users. The matching is done using machine learning techniques.
    • Worked as part of the company’s R&D team—focused on data visualization, and graph visualization in particular—that won several prizes at the International Symposium on Graph Drawing and Network Visualization for several years in a row.
    • Was actively involved in the product design for the main projects of the company.
    • Led the migration of the company’s main product from a Flex and Java 1.4 servlets application to HTML5/React.js and Spring MVC. The product—a large software suite for psychological testing—was targeted mainly towards enterprises and is currently in use at several large Dutch companies (such as ING).
    Technologies: Java, Spring, Machine Learning, TypeScript, React, Oracle, PostgreSQL
  • Software Architect | Co-founder

    2004 - 2011
    Software Business Partners
    • Co-founded this outsourcing company.
    • Discussed the requirements with the clients, explained possible technology choices and proposed a development plan.
    • Implemented key areas of the projects, assigning tasks to the team members as well as creating training materials for the team.
    • Worked on a large number of projects, using diverse technologies, for both the desktop and the web.
    • Developed a screencasting streaming server for Flash— low-level C protocol work which required reverse engineering the Flash screen capture codec data.
    • Created a line of business desktop applications, implemented with .NET Windows Forms, WPF, and Silverlight.
    • Completed the most challenging project at the company—embedding the IBM Lotus Symphony in the browser on Windows and Mac. Symphony was a third-party pure desktop application without an embeddable ActiveX or applet.
    Technologies: C#, VB.NET, ASP.NET, C++, SQL Server

Experience

  • Fluid Calc (Development)
    https://bitbucket.org/radu-b/fluid-calc-desktop

    An open-source, multiplatform application that performs unit conversions and calculates formulas commonly used in well testing/drilling.

  • Painting Timelapse Videos from Photographs (Other amazing things)

    A small-but-fun Python app that I wrote. It analyzes a photograph and uses the color and intensity distribution to generate a painting-like timelapse video from it.

  • Antialiasing using Deep Learning (Development)
    https://github.com/radu-b/dl-antialiasing

    This application adds antialiasing (edge smoothing) to rough black and white images. It uses a UNet based on ResNet18. Implemented using PyTorch and Fast.AI

  • Intro to Python Image Processing in Computational Photography (Publication)
    Computational photography is about enhancing the photographic process with computation. While we normally tend to think that this applies only to post-processing the end result (similar to photo editing), the possibilities are much richer since computation can be enabled at every step of the photographic process—starting with scene illumination. In this article, Toptal OpenCV Expert Radu Balaban walks us through two examples of computational photography: low light and high dynamic range.

Skills

  • Languages

    C#, HTML/CSS, JavaScript, TypeScript, Java, R, Assembly, SQL, Python, C++
  • Frameworks

    .NET, Spring, ASP.NET MVC, ASP.NET, Flask
  • Libraries/APIs

    Win32 API, Windows Forms, React, OpenCV, NumPy, Pandas, Apache Lucene, DirectX, jQuery, Node.js, PyTorch, Fast.ai
  • Paradigms

    Object-oriented Programming (OOP), Data Science, Functional Programming
  • Platforms

    Windows, Oracle Database, Linux, Jupyter Notebook, Google Cloud Platform (GCP)
  • Other

    Machine Learning, Software Architecture, Software Engineering, Computer Graphics, Artificial Intelligence (AI), Computer Vision, AWS Cloud Architecture, Deep Neural Networks, Convolutional Neural Networks, Deep Learning, Deep Reinforcement Learning, Reinforcement Learning
  • Storage

    PostgreSQL, Microsoft SQL Server, Google Cloud

Education

  • Master's degree in Computer Science (Machine Learning)
    2016 - 2019
    Georgia Institute of Technology - Atlanta, GA, USA
  • Bachelor's degree with honors in Computer Science
    1998 - 2004
    Technical University of Cluj-Napoca - Cluj-Napoca, Romania

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