Bonab, Addanki Awarded College’s Dissertation Writing Fellowships

Doctoral candidates Hamed Bonab and Raghav Addanki have been selected to receive Spring 2022 Manning College of Information and Computer Sciences Dissertation Writing Fellowships. Each fellowship provides a $16,500 stipend, granted to students who are nearing the end of their dissertation writing and are planning to defend their dissertations and graduate. Students are nominated by their faculty advisors, based on the strength of their dissertations and its significance to computing theory and practice. 

Bonab, who was admitted to doctoral candidacy with distinction and defended his proposal, "Neural Approaches for Language-Agnostic Search and Recommendation," in July 2021, is advised by Professor and Chair of the Faculty James Allan. The work underlying his proposal has been published at four conferences, including the 2020 ACM Special Interest Group in Information Retrieval and the 2021 ACM International Conference on Information and Knowledge Management. 

Working as a research assistant at the Center for Intelligent Information Retrieval, Bonab has significantly contributed to the development of cross-lingual information retrieval systems, including MATERIAL, the Machine Translation for English Retrieval of Information in Any Language, and BETTER, a program designed to extract fine-grained semantic information across multiple languages and problem domains. 

Addanki is advised by Professor Andrew McGregor and Assistant Professor Cameron Musco, and proposed his thesis, "Combinatorial Algorithms for Graph Discovery and Experimental Design," in October 2021. He proposes to study problems arising in experimental design from an algorithmic perspective, focusing on causal discovery and group testing. The work leading up to his thesis has been published in the International Conference on Machine Learning, Neural Information Processing Systems, and the International Conference on Algorithmic Learning Theory.

Bonab is currently finishing an internship at Amazon, working with the global search quality team on an industrial project related to his dissertation. He received his master's in computer engineering from Bilkent University, Turkey, in 2016, and his bachelor's in computer engineering from Iran University of Science and Technology in 2013.

Addanki's research is focused on the design and analysis of algorithms for data science, in particular in identifying connections between discrete optimization and causal inference. Starting in January 2022, he will participate in the Causality program at the Simons Institute for the Theory of Computing at University of California, Berkeley. He completed his undergraduate degree in computer science at Indian Institute of Technology Madras in 2016.