- Building tools such as Piplio, utilizing search and deep learning models in NLP and NLU. (​Piplio​)
- Reproducing and applying state of the art research in the field of machine intelligence.
- Teaching applied educational projects in computer science and machine learning.

Applied Researcher and Founder

<p>Besides research, we built various products such as:</p><p>[NEAR Atlas](https://nearatlas.com/#/) : an online on-chain analytics platform.</p>

Senior Research and Data Engineer

- Built matching algorithms for founders using graph models and deep learning.
- Designed internal data gathering tools to create interpretable models.
- Guided the team into building user engagement tools, such as an automated interest based event tool. 

Head of Machine Learning

- Built energy and HVAC data simulator to model various unsupervised machine learning tasks.
- Applied NLP/NLU models on tickets / issues to be categorized by types.
- Integrated Slack API with custom conversational agents (chatbot) using Reinforcement Learning and NLP. 

I work as a researcher around machine learning.
From research to modeling and building production level models / applications within machine learning.

Python was the first programming language that I actually build things with. I used it back in college to build a text-engine.

Python libraries and community is very strong, specially in terms of scientific work. In case of automation, scripting and machine learning nowadays as well.

1- I've used it in building scrapers using beautifulsoup.
2- Building web applications with Django.
3- Building APIs using Flask.
4- Building machine learning models using several available frameworks such as Keras and OpenDeep.


I've been a rubyist for about 5 years now, aside of using Ruby with Ruby On Rails, I've used it for other different occasion such as automation and scripts that are better of with Ruby rather than Python.

I've been building big scale, small scale and any scale web applications with Ruby On Rails for quite a while now.

I have built products like:
1- Analytic dashboard / administration app.
2- An Online School to serve as a MOOC.
3- Real-time messaging application.
4- A video Web API.
5- A community network application.

It's not the answer to every web solution, but it's a pretty neat one most of the time.

I've used Javascript almost all the time side by side with other languages for different scenarios. JS community have come a long way to achieve it's current status, so it's fun to work around it.


I've been working around RDBMS since early days of building web applications.

Since then I've developed the "database guy" skills to customize queries, cache and clustering databases.

I've got a hang of developer operations on my own over time. It's a part of making maintainable and 24/7 online services.

Having good traffic anomaly detection and error-handling could avoid a lot of issues with high traffic products.

I've done infrastructure engineering before, though with AWS it's next level.

I got the chance to work and connect several services and technologies pretty quickly over time.

NoSql is a good way to deal with unstructured data.

I usually use them when I'm building an MVP, or scraping data, or just something among those lines where it needs less structure but more persistence.


I've got a hang of developer operations on my own over time. It's a part of making secure APIs for machine learning models.


I love building web apps, using existing frameworks, low-code no-code tools or using any relevant products.

Applied Machine Learning Researcher

Yad Konrad

Notes and summaries on several machine learning and reinforcement-learning subjects.


Study Reinforcement Learning (open source)

a simple demonstration of using Python API with VueJS for search and various other applications withing machine learning.

Flask and Vuejs Boilerplate (open source)

Keras Implementation of End to End Learning for Self-Driving Cars by (Baris Kayalibay, Grady Jensen, Patrick van der Smagt) 

Nvidia Autopilot using GTA as enviuroment using Keras (open source)

- Developed the MVP of the product into production to find product market-fit.
- Built an in house streaming service with using AWS and out of the box video encoding tools.
- Hired a great team of designers, engineers and editors to expand the product.

DraperTV and Online School

- Applied NLP/NLU models on tickets / issues to be categorized by types.
- Integrated Slack API with custom conversational agents (chatbot) using Reinforcement Learning and NLP.

Personal details

Yad K.

Summary

Technical skills

Work Experience

Personal Projects