Engineering graduate student places second in international research competition

Sarah Small
January 07, 2021

UNIVERSITY PARK, Pa. — Mahabubul Alam, a doctoral candidate in electrical engineering at Penn State, was recently awarded second place in the Association of Computing Machinery (ACM) Student Research Competition at the International Conference on Computer-Aided Design.

A headshot of a man in a light blue shirt against a light gray background

Mahabubul Alam, doctoral candidate in electrical engineering at Penn State.

IMAGE: Abdullah Ash Saki

The competition, which is sponsored by Microsoft, gives students an opportunity to “present their original research at well-known ACM sponsored and co-sponsored conferences before a panel of judges and attendees,” according to ACM’s website.

The competition begins with a poster session, where the student researchers display their posters and talk to judges about their research. Selected semi-finalists move on to the second round of competition, which consists of a short presentation of their research before the judges. 

Alam’s project that earned second-place recognition was titled “Analysis and Optimization Methodologies for Quantum Approximate Optimization Algorithm.”

“Mahabubul is a leading researcher in the area of quantum circuit compilation,” said Swaroop Ghosh, Joseph and Janice M. Monkowski Career Development Associate Professor and Alam’s adviser. “He is an out-of-the-box thinker and a problem solver. His doctoral research deserves this recognition.”

Alam worked at Qualcomm and Intel in the summers of 2018 and 2020, respectively. After receiving his bachelor's degree from Bangladesh University of Engineering and Technology in 2015, he worked as a physical design engineer before coming to the United States to begin his doctoral studies at Penn State in the spring of 2018. 

His research is primarily focused on the electronic design automation (EDA) of quantum computing. He investigates the impacts of noise on the performance of quantum algorithms and develops EDA techniques to mitigate them. He is broadly interested in quantum computing, EDA, very large-scale integration and applied statistical learning.

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Last Updated January 07, 2021