Konstantin Tolskiy, Developer in Redmond, WA, United States
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Konstantin Tolskiy

Verified Expert  in Engineering

Software Developer

Location
Redmond, WA, United States
Toptal Member Since
September 28, 2020

Konstantin is a senior programmer with over 20 years of progressive software development and research experience in the fields of 3D graphics, machine learning, graph theory, and so on. Along with having a strong analytical/mathematical background, Konstantin is the author of 12 scientific papers that primarily focus on numerical methods.

Portfolio

Microsoft
C++17, Windows 10, DirectX
Facebook Reality Labs
Python 3, NVIDIA CUDA, C++17, Linux, GPU Computing, Image Processing...
Allign Tegnology
Splunk, Multithreading, OpenGL, Windows 10, Microsoft Visual C++

Experience

Availability

Full-time

Preferred Environment

Android, Linux, Windows

The most amazing...

...project I've worked on was a Python script that created and visualized depth maps based on 2D pictures.

Work Experience

Senior Software Engineer

2020 - 2024
Microsoft
  • Decreased Teams rendering power consumption by 40%.
  • Create a subsystem for image dumping, which simplifies the debugging process.
  • Modified the telemetry system for black and frozen frames detection.
Technologies: C++17, Windows 10, DirectX

Software Engineer IV (Contract)

2020 - 2020
Facebook Reality Labs
  • Designed and implemented software for AR/VR research and 3D scene reconstruction.
  • Checked the quality of reconstruction using Ray tracing.
  • Accelerated tests by 400% without losing quality as well as incorporating additional tests.
  • Converted code from Nvidia CUDA GPUs to Intel CPUs.
Technologies: Python 3, NVIDIA CUDA, C++17, Linux, GPU Computing, Image Processing, Artificial Intelligence (AI), Computer Vision

Senior 3D Software Engineer

2017 - 2019
Allign Tegnology
  • Developed new features for orthodontics and the UI for parameter control.
  • Optimized shapes of the features to create the best experience for patients.
  • Improved the performance and quality of 3D mesh generation.
Technologies: Splunk, Multithreading, OpenGL, Windows 10, Microsoft Visual C++

Software Engineer

2016 - 2017
Bitanimate
  • Built depth maps based on 2D pictures using machine leaning.
  • Developed stereo landscape visualizations based on NASA WorldWind and parsed using Open3D building data.
  • Created stereo landscape visualizations based on Google Earth.
Technologies: Linux, Windows 10, TensorFlow, OpenGL, C#, JavaScript, Java, Python, C++, Deep Learning, Artificial Intelligence (AI), Convolutional Neural Networks (CNN)

Software Engineer IV

2014 - 2016
Mentor Graphics
  • Designed and implemented an algorithm for finding cutting pairs in linear time.
  • Developed an algorithm for finding separation pairs in linear time.
  • Composed an algorithm that discovers cutting triplets in near linear time.
  • Improved heuristics for graph-coloring algorithms.
Technologies: Graphs, Linux, C++

Software Developer

2010 - 2013
ESRI
  • Designed and implemented 2D and 3D visualization systems for GIS.
  • Built optimization structures for a data exchange which resulted in a 1000% acceleration.
  • Implemented the dynamic creation of 3D objects and developed effective methods for their selection.
Technologies: Multithreading, OpenGL, Direct3D, NVIDIA Nsight Systems, VTune, C++, Visual Studio, NVIDIA CUDA, GIS

Creation of Depth Maps Based on 2D Pictures

I composed a Python script that created and visualized depth maps based on 2D pictures. I was the sole contributor. My work included studying of the state-of-art, designing and implementation CNN models on Windows 10 and Linux platforms. I used AWS severs for training.

Video separation.

This is a video segmentation project. The most complicated part is dividing feet and a floor. Segmentation was done in real time using cameras that provided depth information. The software was implemented using C++ 17, CUDA, etc.
1977 - 1983

Master of Science Degree in Physics

Lomonosov Moscow State University - Moscow, Russia

JUNE 2018 - PRESENT

Machine Learning

Stanford University | via Coursera

Libraries/APIs

OpenGL, TensorFlow, OpenCV, DirectX

Tools

Microsoft Visual C++, Splunk, GIS, Visual Studio, VTune, NVIDIA Nsight Systems, Direct3D

Languages

C++, C, Python, C++17, Python 3, Java, JavaScript, C#

Platforms

Windows, Linux, NVIDIA CUDA, Android, Amazon Web Services (AWS)

Other

Linear Algebra, Numerical Methods, Calculus, Windows 10, Multithreading, GPU Computing, Graphs, Machine Learning, Deep Learning, Maps, Image Processing, Artificial Intelligence (AI), Computer Vision, Convolutional Neural Networks (CNN), Data Processing, Server Infrastructure, Video Encoding

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