Arnoldas Kurbanovas
lead software engineer at NYS center of excellence in Weather and climate analytics
Education:
Bachelor of Science (B. S.) in Computer Science from the University at Albany (UAlbany), State University of New York (SUNY Albany)
Master of Science (M. S.) in Computer Science from the University at Albany (UAlbany), State University of New York (SUNY Albany)
Main Project/Thesis:
Applied machine learning techniques to develop a custom neural network machine learning model that predicts the price for a specific cryptocurrency based on trends and Twitter data sentiment analysis to guide investment decisions
Used Numpy in Python to analyze datasets of images
Developed a web app using node, JavaScript, and D3 visualization tools to view cryptocurrencies sentiment
Relevant Experience:
Tutored high school and college students in the areas of computer science (data analytics as well as machine learning algorithms and methods) and information technology, including putting systems together, installing operating systems, and managing systems
Taught Logic, Python, Java, Java Script, HTML, CSS, and agile programming techniques via in-person classes and webinars
Front end and back end development:
Security mobile and web application for private use in React Native and NodeJS
Student Freelancer Marketplace cross-platform mobile application in React Native (CampusPro App)
Publicly available via Google Play store and Apple IOS store
Areas of Expertise or Specialties:
Data Analytics
Hardware Set Up and Maintenance
Image Classification
Machine Learning
Mobile and Web Applications
Script Automation
Software Engineering
Current Projects:
Providing software engineering and data analytic services in the development of software tools to support research and development projects
Developing machine learning models, image classification tools, and automated scripts
Building/configuring, installing, testing, and maintaining complex systems, mobile and web application software, and system management tools
Installing and managing data storage, NVIDIA high-end GPUs, and computer servers in the xCITE lab and the UAlbany Data Center
Configuring and maintaining Kubernetes and SLURM computer clusters for production applications and high-speed GPU workloads
Mentoring undergraduate students and teaching them machine learning techniques and data analytic tools, while working in an agile programming environment
Setting up and supporting a Jupyterhub server integrated with Kubernetes and Docker containers on an Ubuntu cluster
Standing up state-of-the-art infrastructure and equipment in technology for the xCITE laboratory, including building HPC and Visualization clusters, workstations, and displays
Providing IT technical support for xCITE students and researchers, including environment setup, computer setup, SLURM, and k8s usage guides, as well as showcasing and maintenance of the Science on a Sphere (SoS)
Using a Convolutional Neural Network in machine learning to train HRRR meteorological data to develop fly/no-fly prediction models for specific Unmanned Aerial System drones