AUA kick-starts collaboration with SuperAnnotate

News Feb 22, 2022

AUA Zaven & Sonia Akian College of Science and Engineering constantly broadens the scope of its collaboration with top-notch companies launching innovative initiatives in various fields. On a special note, the college has embarked on a new partnership with SuperAnnotate. In the framework of this partnership, SuperAnnotate has made its state-of-the-art platform accessible to AUA students, allowing them to quickly create datasets, train and develop AI and machine learning models.

AUA kick-starts collaboration with SuperAnnotate

SuperAnnotate stands as a premium-quality ground-truth data provider across the field, where you can annotate, version, and manage data. “Computer Science and Data Science students can use the platform to label data with maximum precision in a minimum time,” mentions Stefan, the Head of Product at SuperAnnotate. Students can also create simple model prototypes without much coding knowledge, so, the platform will help them better understand the extent to which their problem is feasible to solve with AI.

Kevork Sulahian, an AUA alumnus and a Machine Learning Sales Engineer at SuperAnnotate, shares his views on how the company marks its successful outcomes. “Using data to make important decisions, having a customer-centric approach, and following along with continuous uphills in the field are some of the reasons for our success.” This lays an excellent ground for AUA students to use platform features to benefit their research area. BS in Data Science Program Chair Dr. Habet Madoyan asserts that “the cooperation gives AUA students access to one of the best annotation tools available in the market. Our students can certainly use the tool for a selected course, capstone projects, and beyond.”

partnership with AUA students

The partnership has already given its roots, as one of AUA’s graduate students, Anna Gaplanyan, an Industrial Engineering and Systems Management Program (IESM) major, uses SuperAnnotate to back up her capstone thesis. She recalls creating a Document Project for text classification, defining the classes for the data, adding attributes specific to a certain class, defining whether the classification should be done based on the full context or only a part of it, and more. "After annotating the data, I can easily download it with obtained classes and use it for my research,” she mentions.

We hope this pilot partnership will evolve further, encouraging more students to undertake novel research in ML and AI.

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