Gangtok student Ingsa Hang Subba secures Harvard MDes admission

Ingsa Hang Subba of Gangtok has secured admission to Harvard University’s Graduate School of Design for its Master in Design Studies (MDes) programme. He is set to begin his studies in September and will work on a research topic that connects Himalayan languages with artificial intelligence, along with possible links to early detection of neurological conditions.

From applied mathematics to design research

Ingsa completed his schooling at Taktse International School. He later pursued a Bachelor’s degree in Applied Mathematics from Endicott College in the United States. Over time, his academic interests moved beyond mathematics and into philosophy, reflecting a shift toward broader questions about knowledge and culture.

His education and experience also show an interdisciplinary path. Professionally, he has worked across areas such as journalism, communication design, cultural interpretation and technology. Much of his work has focused on the cultures, histories and knowledge systems of the Eastern Himalayas.

Research project ties language, sound and technology

At Harvard, Ingsa plans to develop Sound Topographies, a project that studies indigenous Himalayan languages through computational design and artificial intelligence. The work examines patterns in language and sound to understand historical connections related to geography, migration and cultural exchange across the Himalayan region.

The project is also linked to his interest in the ancient Silk Routes, and to the idea of the Himalayas as a historic meeting point where people and ideas moved and changed over centuries. In addition, he believes the approach could have future relevance for healthcare. Research worldwide is exploring whether changes in speech and language may serve as early indicators of cognitive decline and conditions such as Alzheimer’s, but many indigenous and low-resource languages are not well represented in AI datasets.

Ingsa said his long-term goal is to build linguistic datasets and computational methods that could support research involving indigenous and underrepresented communities. He also indicated that reaching medical applications would require collaboration with specialists such as medical researchers, linguists and clinicians.