We are proud to recognize the inaugural recipients of the Kahlert Impact Prize.

The Kahlert School of Computing offers the Kahlert Impact Prize to two graduate students who, whether through research or service, show a track record of success and a compelling story of the high impact of their work. Honorees receive a scholarship of $2,000 each.

Amit Samanta
PhD Student

Amit works in the area of system design and implementation. His recent work has focused on serverless computing platforms, which are often deployed by large cloud services. Cloud workloads demand massive resources, and they are often dynamic and unpredictable. Amit’s contributions improve resource utilization while targeting performance and sustainability metrics.

Amit has published many papers at top systems conferences, earning him multiple awards. He has collaborated with industry professionals on some of his work. A key novelty is the deployment of scheduling algorithms that consider cutting-edge technologies like persistent or disaggregated memory. More recently, the carbon footprint of cloud platforms has come under scrutiny – Amit’s ongoing work explores carbon-aware and sustainability-aware network routing schemes. Amit has a long track record of service to his research community, including engagement in program committees, artifact evaluation committees, and event organizing.

Maitrey Mehta
PhD Candidate

Maitrey works to expand the impact of AI to low-resourced languages. While most recent large language model advancements (like ChatGPT) are evident for English, progress in other languages has languished. Maitrey has focused on his native language of Gujarati, with hopes that it provides a roadmap to extend AI technologies to the many other languages spoken by the world’s population. 

Maitrey’s vision is to give every human the right to interact with technology in one’s native language. To achieve this, he focuses on a key ingredient for developing this technology: data. Data is the fuel that powers modern LLMs, and there is an unfortunate data disparity across languages. His research aims to find efficient methods to close this resource gap. Maitrey contributed the first semantically annotated dataset in the Gujarati language that also captures cultural nuances. Subsequently, this dataset has been used to create dependency treebanks and other basic language tools like parsers and taggers. Maitrey has collaborated with industry and other groups on campus. He has helped the research community by serving on program committees and through mentorship roles. Among many talks on AI, he has also presented to an audience of veteran business owners at the 7th Annual Utah Veteran Business Conference in 2023.