📸 Check out this awesome album from Skoltech’s first Master’s program selection!
Over 150 candidates visited our campus last weekend, while 73 others from 25 countries joined online. For the first time ever, applicants could do the process in Russian — chatting with professors, tackling entrepreneurship & innovation challenge, and taking math exams.
Want in? Apply by May 12 for the next round of Skoltech Master’s selections!
Over 150 candidates visited our campus last weekend, while 73 others from 25 countries joined online. For the first time ever, applicants could do the process in Russian — chatting with professors, tackling entrepreneurship & innovation challenge, and taking math exams.
Want in? Apply by May 12 for the next round of Skoltech Master’s selections!
⚡️Thai students, here’s your shot!
The H.R.H. Princess Maha Chakri Sirindhorn Skoltech Scholarship brings you a fully funded Master’s in Data Science, Materials Science, or Energy Systems.
What you’ll get:
✅ Full tuition covered
✅ Monthly stipend
✅ Free students dorms
✅ Covered flight
✅ Insurance
✅ World-class education fully in English
Apply by April 25. Check it out.
The H.R.H. Princess Maha Chakri Sirindhorn Skoltech Scholarship brings you a fully funded Master’s in Data Science, Materials Science, or Energy Systems.
What you’ll get:
✅ Full tuition covered
✅ Monthly stipend
✅ Free students dorms
✅ Covered flight
✅ Insurance
✅ World-class education fully in English
Apply by April 25. Check it out.
📸 Here’s the album from Skoltech's Open Doors!
We covered our academic programs, walked through the application and admission process, and took a tour of the campus and labs
‼️ By the way, our next event like this is happening the day after tomorrow, April 16.
We’ll dive into cutting-edge research in materials and energy!
Hurry up and register!
We covered our academic programs, walked through the application and admission process, and took a tour of the campus and labs
‼️ By the way, our next event like this is happening the day after tomorrow, April 16.
We’ll dive into cutting-edge research in materials and energy!
Hurry up and register!
⌛️ Deadlines are a tough topic, but you’ve got to keep them in mind.
Just a reminder: we’re accepting applications for the Skoltech Summer School of Machine Learning in China until the end of this week — April 20th included.
Participation is free, and you can apply for either in-person attendance (we’ll cover all expenses except the visa) or online.
Just a reminder: we’re accepting applications for the Skoltech Summer School of Machine Learning in China until the end of this week — April 20th included.
Participation is free, and you can apply for either in-person attendance (we’ll cover all expenses except the visa) or online.
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⚡️ Time to celebrate!
Alexander Tyurin, Assistant Professor at Skoltech AI Center and Head of a Research Group at AIRI Institute, has been named the laureate of the “AI Scientific Breakthrough of the Year” award at Data Fusion 2025.
The award, which includes a prize of 1 million rubles, was granted for a paper presented at NeurIPS 2024 in Vancouver. In this work, the authors explore decentralized asynchronous optimization—where system nodes operate independently without strict synchronization. They proposed optimal time complexity estimates that retain high accuracy while accelerating computations. This breakthrough opens up new possibilities for training large-scale neural networks and making more efficient use of distributed resources.
Alexander Tyurin, Assistant Professor at Skoltech AI Center and Head of a Research Group at AIRI Institute, has been named the laureate of the “AI Scientific Breakthrough of the Year” award at Data Fusion 2025.
The award, which includes a prize of 1 million rubles, was granted for a paper presented at NeurIPS 2024 in Vancouver. In this work, the authors explore decentralized asynchronous optimization—where system nodes operate independently without strict synchronization. They proposed optimal time complexity estimates that retain high accuracy while accelerating computations. This breakthrough opens up new possibilities for training large-scale neural networks and making more efficient use of distributed resources.