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Krishna Chaitanya Rao Kathala
University of Massachusetts Amherst
Amherst, Massachusetts
 

Dr. Krishna Chaitanya Rao is the program director of the Masters of Translational Data Analytics (MTDA) program at The Ohio State University, where he also serves as a senior researcher at the Translational Data Analytics Institute (TDAI). In this role, he leads interdisciplinary research and drives the academic vision of the MTDA program, ensuring students receive rigorous, real-world training in responsible artificial intelligence (AI), data science, and translational research. Krishna holds a PhD and Master's in data science from the University of Massachusetts Amherst.

At TDAI, Krishna focuses on responsible data science. Prior to Ohio State, Krishna led responsible and trustworthy AI initiatives at Vanguard, where he developed enterprise-wide frameworks for fairness, explainability, and ethical AI governance. At UMass Amherst, he advanced global engagement and experiential learning, spearheading international partnerships to support educational research and workforce development. With the Government of Telangana, he worked to strengthen the regional innovation ecosystem, supporting startups, social innovation, and digital education strategy. He is also the cofounder of an EdTech startup focused on expanding access to science, technology, engineering, and mathematics (STEM) and data literacy.

Krishna is a coauthor of the Springer Nature book Privacy in the age of innovation, holds four international patents, and has judged more than 25 global hackathons. He has reviewed over 150 scholarly papers and received honors such as the Association of International Education Administrators (AIEA) Harold Josephson Professional Promise Award and Top 1% Global Mentor from ADPList.

He is frequently invited to speak at global forums, where he advocates for responsible AI and promotes broader participation in STEM.


     

Replication in requirements engineering: the NLP for RE case
Abualhaija S., Aydemir F., Dalpiaz F., DellAnna D., Ferrari A., Franch X., Fucci D. ACM Transactions on Software Engineering and Methodology 33(6): 1-33, 2024.  Type: Article, Reviews: (2 of 2)

This paper addresses the important problem of replication in the realm of natural language processing for requirements engineering (NLP4RE). The authors acknowledge a significant lack of replication research in this field, despite the increasing u...

 
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