DataFest Yerevan 2021 Conference Converges Machine Learning Experts

Among the many speakers this year were Stephen Papp, co-founder and managing director at Sophron Engineering, Victoria Muradyan, machine learning scientist at Picsart, and Stepan Sargsyan, Chief Scientist at Krisp. As far as academics, Khachatrian explained that unfortunately, “Armenia does not have many full-time professors teaching machine learning and artificial intelligence.” Thus, the majority of the speakers were from industry. In addition to lectures, the conference gave the opportunity for presenters, students, and professionals to network in person — a notable difference from last year.

In future iterations, Khachatrian hopes to have more workshop-style lectures and tutorials, diving deeper into complicated technical methods and concepts. For the long term, DataFest Yerevan hopes to create an event which will have broader regional interests and keep its focus on advanced topics. The biggest takeaway, in Khachatrian’s words, was that Armenia not only wants, but “needs more upper-level education and experts to advance the study and industry of data science in the country.”

In his view, the conference highlighted two main gaps of data science in Armenia. The first is a lack of professors and faculty in higher education teaching the latest and most important topics in machine learning and artificial intelligence. The second is the lack of mid-level and senior industry experts to fill in data science roles to match the growing demand for data science leaders and managers in the country.

As of today, Armenia has a much greater demand than supply of data science experts, who often receive a limited form of education in training centers and at universities. There is room for a lot more investment in data science research and academia in Armenia, and part of the issue is that the financial incentive for people to stay in research is low, an issue not exclusive to Armenia or data science. Until the country gets that infrastructure, Khachatrian thinks one potential solution to resolve the issue of lack of experts may be to make it easier for international specialists to come and get hired in these roles in Armenia.

Beyond DataFest Yerevan, if someone is interested in learning data science in Armenia, Khachatrian suggested pursuing degree programs at universities, such as the BS in Data Science at AUA, Yerevan State University’s joint Master’s Degree Program in Applied Statistics and Data Science, or Armenian State University of Economics Master’s degree in Applied Statistics and Data Science. There also opportunities to enroll in courses at training centers such as the Armenian Code Academy or sourcemind, which are primarily taught in Armenian but on occasion in English as well.

For those interested in supporting the development of machine learning/artificial intelligence in Armenia, Khachatrian suggested a few concrete ways to do so. The first is to move to Armenia, whether by joining local teams, starting a company there, or opening a branch of an existing company there. Some notable local and international data science companies with teams in Armenia include DISQO, SmartClick, and intelinair, not to mention the growing data science teams at other firms such as Picsart and SoloLearn. Another way to help, for those with the appropriate background, is by becoming a supervisor for students and contributing to the data science community (which is often online) through classes or lectures at events like DataFest Yerevan, which can have a major impact for those seeking more advanced studies not yet available. And finally, not only donating, but investing in Armenian startups, research teams and universities helps support the infrastructure for the industry to develop.