— Tell us about your academic and professional journey so far.
— I came to HSE University because of its strong reputation for innovation, global connections, and academic excellence in computer science. I wanted to study in an environment that combined theory with real-world applications and offered opportunities to work on research projects that have a real social and technological impact.
HSE encourages students to work on applied research and industry projects. During my studies, I worked on real datasets, collaborated with companies, and presented my findings at academic events. This hands-on approach built a strong link between theory and practical application.
During my studies, I did an internship in the IT department of Sialkot International Airport (Pakistan), where I worked with databases and data management systems. This experience helped me connect theory to real-world technology.
After completing my Master’s in Data Science at HSE, I continued onto a PhD in Artificial Intelligence. I also work remotely for Flomad Labs R&D (Austin, Texas) as an AI/ML developer intern, where I work on automation and AI-driven backend systems. My days are a blend of research and development. I work on my PhD research—improving low-resource language processing models—and also develop AI automation pipelines at Flomad Labs. It’s a direct continuation of what I studied at HSE: combining AI theory with practical innovation.
— How did your studies prepare you for your current activities?
— I gained perseverance and adaptability. Research often requires patience and creative problem-solving, and HSE taught me how to stay focused and curious, even when facing challenges. These qualities now help me navigate both academic research and applied AI development.
The demanding coursework and hands-on projects at HSE trained me to think critically, manage complex data problems, and communicate my ideas clearly.
I learned how to turn abstract theories into practical solutions—a skill that directly supports my work as an AI/ML developer and researcher
The courses in Natural Language Processing, Machine Learning, and Statistical Modelling guided me toward my current research interests, and mentors such as Prof. Vasilii Gromov, Prof. Victor Popov, and Prof. Sergei Kuznetsov encouraged me to combine linguistic analysis with AI methods. This deeply inspired my research direction and later became the foundation of my PhD topic of low-resource language technologies.
One of my major accomplishments was born directly from my HSE research work: my paper on ‘Building a Clean Bartangi Language Corpus and Training Word Embeddings for Low-Resource Language Modeling,’ which I presented at the RANLP 2025 Conference.
— Apart from academic knowledge, what are the other benefits of an HSE education?
— HSE’s reputation for academic excellence and research makes its degrees highly respected worldwide. Employers recognise that HSE graduates are well-prepared, analytical, and adaptable—qualities that are essential in the technology and AI sectors.
While some courses were quite challenging, they taught me the importance of consistent effort and collaboration.
Working through complex assignments helped me understand that learning is not just about results, but about the process of exploring, failing, and improving
HSE’s environment also helped me become confident in multicultural teamwork. Studying and collaborating with peers from different countries taught me to respect diverse perspectives and adapt my communication style—a skill that’s been very useful in my international research collaborations and my current remote internship.
In addition, the HSE alumni network has been incredibly supportive. It connects students and professionals from around the world who share similar experiences. I’ve met many alumni who have offered advice, mentorship, and even research collaborations, both in academia and industry.
— What are your plans for the future? What advice do you have for people starting out on the same path?
I aim to continue contributing to research at the intersection of AI, language technology, and sustainability. My long-term goal is to develop intelligent systems that promote digital inclusion and social impact. HSE has given me the academic foundation, research experience, and global confidence to pursue this path.
My advice is not to limit yourself to just classroom learning—get involved in research early, take part in competitions, and build your own projects
These experiences teach problem-solving and teamwork, which are essential for success in AI and data science. Embrace challenges and never hesitate to ask questions. Every obstacle is an opportunity to learn something new. Even when the path feels uncertain, it’s important to stay open-minded and keep exploring—HSE rewards curiosity.
© Photo by Victoria Proskurova
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