Irem Boybat  Irem Boybat photo         

contact information

In-memory computing
IBM Research | Zurich




Short biography

Irem Boybat has been a part of the In-memory computing group of IBM Research – Zurich since 2015. Her current research focus is on developing the next generation of AI systems where analog in-memory AI cores composed of non-volatile memory is expected to result in great energy and speed gains. Prior to this, Irem was a research scholar at IBM Research – Almaden, San Jose, California with similar research focus.

Irem earned her PhD degree in Electrical Engineering at the École Polytechnique Fédérale de Lausanne (EPFL) in Lausanne, Switzerland, in 2020, her Master of Science degree in Electrical and Electronic Engineering, also from EPFL, in 2015 and her Bachelor of Science degree in Electronics Engineering from Sabanci University, Istanbul, Turkey, in 2013.


Selected Talks

Invited talk, Symposium "Advanced neuromorphic computing hardware: Towards efficient machine learning" at DPG Spring Meeting, Dresden, Germany, March 2020

Invited talk, "Women in Tech 2020", Stockholm, Sweden, March 2020 (live-streamed video available)

Invited talk, "Jubilee Seminar: Peak Human?" at Royal Swedish Academy of Engineering Sciences, Stockholm, Sweden, December 2019 (live-streamed video available)

Invited talk, "Neuromorphic Computing day" at Sabanci University, Istanbul, Turkey, April 2019

Invited talk, "Neuromorphic computing and hardware Gothenburg - Stockholm joint workshop", Stockholm, Sweden, December 2018

Invited talk, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland, May 2018


In the news

NyTeknik news article (2020): How IBM wants to make AI systems 1,000 times more efficient

IBM blog (2020): International Women's day: Celebrating Science

Announcement (2020): President Yusuf Leblebici graduates his 50th PhD student

Announcement (2020): ISSCC Rising Stars 2020 Workshop

EU project (2019): MNEMOSENE (computation in-memory architecture for based on resistive devices)

IBM blog (2018): Novel synaptic architecture for brain inspired computing

IBM blog (2018): Machine learning for analog accelerators

IBM blog (2018): The future of AI needs better compute: hardware accelerators based on analog memory devices