Ruslan Nikolaev

Founding a successful startup is a lifelong dream of mine, so that's what I'm working on now.
To stay up to date, follow me on twitter.

I used to work on Data, AI and Computer Vision problems. You can check out some of my work below. I used to write on these topics and other tech related subjects from time-to-time on my Medium.

I also used participate in international case competitions representing the Lazaridis School of Business and Economics around the world.

Professional Experience:

Theia Labs
Supercharging businesses with computer vision analytics

2019 - Waterloo

  • This failed for a few reasons:
    • We wanted to build around an idea that can be validated quickly, and people in retail were very hard to reach and didn't seem open to try new things.
    • This might have been one of those ideas where we built the product around the technology and we all know that's a big no-no.
Uber ATG
Perception Engineering Intern

2018 - Pittsburgh

  • Projects:
    • Built a testing pipeline to test individual parts of the vision stack improving testing efficiency by 5x.
    • Working on object tracking algorithms within the Perception team
    • Solving the jumping bike problem (when card predicts that bikes will drive off the rack any time)
Perception Engineer

2018 - Waterloo

  • Projects:
    • Developing a traffic light and sign detector and classifier
    • Developed a data aggregation pipeline to standardize numerous public object-detection datasets.
Data Science Intern

2018 - Ottawa

  • Projects:
    • Analyzed Data and built internal reports to understand consumer behaviour on the platform using SQL and Python.
    • Built a dimensional model to aggregate data on daily platform usage improving query time by 10x.
    • Developed features and build a customer maturity machine learning model to serve customized content to users and guide internal business decisions.
Software Lead

2017 - Waterloo

  • Projects:
    • Responsible for managing over 30 software developers to create and deliver innovative design for the embedded and software in the Hyperloop the pod.
    • Wrote a research paper on the topic of Embedded-Systems in Hyperloop Pod describing design decisions in the system.
    • Created a Node.js web-socket server for bi-directional streaming of data from sensors on the pod to a group of remote devices, that allow to control the pod in real time.
Software Engineering Intern

2017 - Guelph

  • Projects:
    • Full-Stack Development of time tracking Jira plugin, used Jira APIs to effectively integrate time tracking.
    • Researching and Developing web-push notifications and a serverless client to send out batch notifications increasing notification conversion by 1.8x.
    • Creating various interactive and mobile-friendly interstitials.
Python Developer Intern

2016 - Kazan, Russia

  • Projects:
    • Part of development team working on Russian Cloud Systems solution at TionixLabs.
    • Designed an autocomplete algorithm in Python to improve customer experience when controlling the cloud system through a command line interface.
    • Working with open source projects such as: OpenStack, Django, Sphinx, Pymongo to build a complete suite of cloud software and services such as Virtual Desktop and Compute Intances.

Research Work:

Software Systems in Hyperloop Pod


  • Overview of the Software System developed to control the pod during the high-speed launch in the in the annual SpaceX Hyperloop Pod competition. Reliance of redundant multi-nodal command execution with RAFT consensus algorithm and an on-board CAN network to enable modular design and data collection from Pod's sensors.


Drake Lyric Generation


  • Generating Drake Style Lyrics using LSTMs and Language Models. Over 30 forks on GitHub and 5k claps on Medium. Used by profs in Portugal to teach AI courses.
Amazon Go @RuHacks


  • Winners of the 2017 RUHacks Hackathon with a POC Amazon Go store built in 36 hrs. Read our story on Medium
How Much @QHacks


  • Solving optimization problem to find best meal for the money near the user. Tomato API integration for restaurant menu listing and Price Discrimination Algo. All packaged into a mobile app.
Tryify @Decode Hackathon


  • In partnership with Shopify, instagram-feed-like shopping experience Shopify merchants's products. Ruby backend with intelligent product search and Shopify checkout API integrations.
Medium API package


  • Medium's API to get all posts made by a user or a publisher. Over 500 downloads.
Medium API package


  • Medium's API to get all posts made by a user or a publisher. Over 500 downloads.
US Mass Shootings Analytics


  • Extensive visualization and statistical analysis of historical data on Mass Shootings in US.
Driver Face + Eye Tracking


  • YOLO and Haar Cascades face and eye detection and tracking CV pipeline. Open/closed eyes Deep Net classifier, critical component for safe AV testing.
ML-Utils library


  • Machine Learning utilities library for Python, simple image labelling web-tool
Snack Classifier


  • Solving problem of uneducated trips to the snack shelf in the office using IoT and Computer Vision. CNN for snack classification.


2nd. @HICC


  • International business case competition in Florida, HICC'19
1st. Solvers Cup


1st. @UNICC


  • International business case competition in Spain, UNICC'18
Wilfrid Laurier Delegate @JDC Central


  • Selected to represent Laurier's Digital Strategy team at the JDCC business case competition
1st. @RuHacks


  • Amazon Go Implementation