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Remembering Jaime Carbonell

Jaime Carbonell, Founder of the CMU’s Language Technologies Institute (LTI), has passed away on February 28th, 2020, following an extended illness. The Distinguished CMU University Professor was a pioneer in Language Technologies. He foresaw a world where people could freely communicate with each other, no matter what language they spoke. He knew that making this dream a reality would require automation, so he spent his career building machines that could understand human language.

Carbonell founded the Language Technologies Institute (LTI) at CMU and under his direction, LTI became the largest and best-known organization of its kind. It has been a leader in areas including natural language processing, question-answering systems, and speech recognition and synthesis, and now boasts five graduate degree programs.

Carbonell created the CMU Ph.D. program in language technologies and gave his full support as Head of the Languages Technology Institute to establishing a dual Ph.D. degree in language technologies of the CMU Portugal Program. The dual degree Ph.D. program benefited immensely from Jaime Carbonell’s experience. He worked together with CMU Portugal Director at CMU, José M.F. Moura, and Isabel Trancoso, Professor at INESC – ID and Instituto Superior Técnico, and Alan Black, Maxine Eskenazi, and Robert Frederking at LTI, among others, to create the LTI dual degree Ph.D. program that now runs at CMU and in Portugal at Universidade de Aveiro, Universidade do Minho, Universidade do Porto, Universidade de Lisboa, Universidade Nova de Lisboa, and Universidade de Coimbra.

When Isabel and I first approached Jaime, he immediately grasped the concept of a dual degree program and enthusiastically gave us his support. He put together an LTI team to develop with us the dual Ph.D. degree program, acting as a facilitator all the way to make sure it happened,” said José M.F. Moura. “Jaime remained a valued partner, collaborator, and friend of the Program and will be dearly missed.”

Jaime’s enthusiasm and suggestions really helped to overcome the many difficulties of setting up the dual degree Ph.D. program in language technologies, bureaucratic and otherwise”, said Isabel Trancoso. She adds that “his vision for the future of language technologies helped make CMU one of the leading centers in this area worldwide. It was a privilege to have known him personally, to have listened to his insightful feedback during these discussions, to have shared with him the initial steps of this program that already led to significant advances in the state of the art and launched many students in successful careers”.

“Jaime always had astounding levels of energy and creativity,” said Robert Frederking, now SCS associate dean of doctoral programs. “I have never understood how he could advise maybe a dozen Ph.D. students, run the LTI, personally be the principal investigator on several research projects, teach regularly and travel to DC frequently to work with funding agencies.”And with all that going on,” he added, “if you ran a new technical problem by him, he would usually come up with three good suggestions for solution paths to investigate.”

Carbonell also advised Manuela Veloso, University Professor of Computer Science at CMU, now on leave while she directs AI research at financial services giant J.P. Morgan and CMU Portugal Faculty. She remembers him as a fantastic educator and mentor. “With Jaime I learned a lot of AI, but I also learned how to advise,” she recalled. “I became a faculty member at Carnegie Mellon, and I embraced a lot of what I learned from Jaime. Even now, I still look at Jaime as my advisor, and throughout my career have turned to him for different types of advice. As of now, I have graduated 40 Ph.D. students. I will always thank Jaime for having graduated me.”

Carbonell, who joined CMU in 1979, led teams that developed knowledge-based machine translation of the text as well as speech-to-speech translation. He invented several well-known algorithms and methods, including maximal marginal relevance (MMR) for summarizing text and a type of machine learning call proactive learning.

Getting the right information to the right people at the right time in the right language in the right medium with the right level of detail” became his mantra.

This article was adapted from the original published by CMU’s School of Computer Science. Additional information can be found here.