Alexander Konovalov is a Chief Data Scientist and entrepreneur with 18 years of experience building applied machine learning and analytics solutions across healthcare, consulting, and research settings. He combines hands-on engineering—from full-stack UI improvements on notable open-source projects like CSrankings to backend NLP model work—with leadership roles at startups and as founder of Wabbit Consulting. Trained at MIPT and Ohio State (MS in Applied Machine Learning), he has deep roots in information extraction and social media analytics from his graduate research. At Clearsense and Compellon he translated complex data requirements into production-ready products, focusing on scalable pipelines and practical model deployment. Based in Toronto, he blends academic rigor with product sensibility and a knack for improving user-facing interactions, evidenced by UI-focused contributions that fixed bugs and added interactive controls to research tools. Known for bridging research code and robust engineering, he thrives on turning experimental models into dependable, user-centered systems.
18 years of coding experience
9 years of employment as a software developer
Bachelor of Science (B.S.), Applied Physics and Mathematics, Bachelor of Science (B.S.), Applied Physics and Mathematics at Moscow Institute of Physics and Technology (State University) (MIPT)
Master of Science - MS, Computer Science and Engineering (Applied Machine Learning), Master of Science - MS, Computer Science and Engineering (Applied Machine Learning) at The Ohio State University
Contributions:133 commits, 3 PRs, 6 pushes in 6 years 1 month
Contributions summary:Alexander integrated contributions from another developer and worked on adding annotations to an API. They made significant changes to the `SemiSupervisedPOSTagger.java` file, focusing on model file handling, execution directory creation, and output functionalities. The user also made changes to various other Java files within the project related to tweet tagging.
A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.
Role in this project:
Full-stack Developer
Contributions:23 commits, 5 PRs, 5 pushes in 1 year 4 months
Contributions summary:Alexander primarily worked on enhancing the frontend of the web application. They added JavaScript files, likely for user interface functionality, and implemented a slider control system, generating the necessary code with a Python script. The user also modified the HTML to incorporate the slider controls and address a bug in the system. The contributions indicate a focus on improving the user interface and interactive elements of the application.
dblpreactscienceresearch-outputselective
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