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Congrats! Ayana and Dennis Earn Top Distinction in Scientific Reports

Ayana Ghosh’s and Dennis Trujillo’s article,  Electronic and Magnetic Properties of Lanthanum and Strontium Doped Bismuth Ferrite: A First-Principles Study, received 2,603 article downloads in 2019, placing it as one of the top 100 downloaded physics papers for Scientific Reports in 2019.

Scientific Reports published more than 1,072 physics papers in 2019, and so a position in the top 100 most downloaded articles is an extraordinary achievement.

Uche Was Inducted Into The John Lof Leadership Academy

Uche was inducted into the John Lof Leadership Academy, an exclusive society for UConn Engineering graduate students.

UConn John Lof Leadership Academy

(Photo Credit: Christopher LaRosa/UConn)

 

UConn John Lof Leadership Academy

UConn John Lof Leadership Academy

(Photo Credit: Christopher LaRosa/UConn)

 

 

John Lof Leadership Academy Mission

Without culturally competent visionaries that are able to communicate, collaborate, and create, there would be no progress in society. The John Lof Leadership Academy strives to inform and inspire these next-generation leaders in academia, industry, and beyond.

Through a “for us, by us” philosophy, John Lof Scholars aim to develop themselves through focused training, specialized workshops, and active learning through outreach and enterprise on and off the UConn campus.

John Lof Leadership Academy

Congratulations Dennis & Uche for Receiving MLSE Travel Awards

Dennis and Uche were both awarded travel grants to attend the Machine Learning in Science and Engineering Conference to be held at Georgia Tech on June 10-12.


The second-annual MLSE conference highlights advances in research that utilize methods of artificial intelligence, the development of new machine learning algorithms designed for science and engineering problems, and the ways these methods lead to innovations across various fields. Researchers from academia, government, and industry will gather to explore the future of research in science and engineering.

On May 10, 2017, an internal symposium known as Machine Learning in Science and Engineering was held at Carnegie Mellon University to identify ways in which these computational tools are advancing diversity in several fields. Based on the strong response at CMU, an open conference was held on June 6–8, 2018 at the CMU campus in Pittsburgh in partnership with Georgia Tech.

This conference surveyed advances in basic research that utilizes methods of artificial intelligence, the development of new machine learning algorithms designed for science and engineering problems, and ways that these methods are leading to innovations across these fields. Researchers from academia, government, and industry participated in a unique and fascinating forum on the future of research and innovation in science and engineering.

http://dsf.ideas.gatech.edu/events/mlse

 

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