Irem Boybat Kara
Contact InformationIBM Research - Zurich Säumerstrasse 4 8803 Rüschlikon, Switzerland phone: +41 (0)44 724 8879 Advisor: Prof. Yusuf Leblebici Microelectronic Systems Laboratory (LSM)
Irem Boybat joined IBM Research – Zurich as a pre-doctoral researcher in November of 2015. She is a member of the Cloud & Computing Infrastructure department, where her focus is on Neuromorphic Computing.
Prior to this, Irem was a research scholar at IBM Research – Almaden, San Jose, California for 6 months where she worked on cognitive computing with non-volatile memory devices.
Irem is working toward her PhD degree in Electrical Engineering (EDEE) at the École Polytechnique Fédérale de Lausanne (EPFL) in Lausanne, Switzerland. She earned her Master of Science degree in Electrical and Electronic Engineering, also from EPFL, in August of 2015 and her Bachelor of Science degree in Electronics Engineering from Sabanci University, Istanbul, Turkey, in 2013.
S. R. Nandakumar; M. Le Gallo; I. Boybat; B. Rajendran; A. Sebastian et al. : A phase-change memory model for neuromorphic computing; Journal Of Applied Physics. 2018-10-21. DOI : 10.1063/1.5042408.
S. R. Nandakumar; M. Le Gallo; I. Boybat; B. Rajendran; A. Sebastian et al. : Mixed-precision architecture based on computational memory for training deep neural networks. 2018-01-01. IEEE International Symposium on Circuits and Systems (ISCAS), Florence, ITALY, May 27-30, 2018.
N. Gong; T. Ide; S. Kim; I. Boybat; A. Sebastian et al. : Signal and noise extraction from analog memory elements for neuromorphic computing; Nature Communications. 2018. DOI : 10.1038/s41467-018-04485-1.
I. Boybat; M. Le Gallo; S. Nandakumar; T. Moraitis; T. Parnell et al. : Neuromorphic computing with multi-memristive synapses; Nature Communications. 2018. DOI : 10.1038/s41467-018-04933-y.
S. Ambrogio; P. Narayanan; H. Tsai; R. Shelby; I. Boybat et al. : Equivalent-accuracy accelerated neural-network training using analogue memory; NATURE. 2018. DOI : 10.1038/s41586-018-0180-5.
S. Sidler; J.-W. Jang; G. W. Burr; R. M. Shelby; I. Boybat et al. : Nonvolatile Memory Crossbar Arrays for Non-von Neumann Computing; Advances in Neuromorphic Hardware Exploiting Emerging Nanoscale Devices; New Delhi: Springer India, 2017. p. 129-149.
G. W. Burr; R. M. Shelby; A. Sebastian; S. Kim; S. Kim et al. : Neuromorphic Computing Using Non-Volatile Memory; Advances in Physics: X. 2016. DOI : 10.1080/23746149.2016.1259585.
S. Sidler; I. Boybat; R. M. Shelby; P. Narayanan; J. Jang et al. : Large-scale neural networks implemented with non-volatile memory as the synaptic weight element: impact of conductance response. 2016. European Solid-State Device Research Conference (ESSDERC) 2016, Lausanne, Switzerland, September 12-16, 2016. DOI : 10.1109/ESSDERC.2016.7599680.
I. Boybat; J. Sandrini; D. Sacchetto; G. W. Burr; Y. Leblebici : Cognitive Computing with Non-Volatile Memory Elements ; MemoCIS Training School, Alghero, Italy, May 9-11, 2015.
G. W. Burr; R. M. Shelby; I. Boybat; S. Sidler; C. di Nolfo : Non-volatile memory crossbar arrays for non-Von Neumann computing. 2015. Electronic Materials Conference (EMC), Columbus, Ohio, USA, June 2015.
G. W. Burr; R. M. Shelby; S. Sidler; P. Narayanan; I. Boybat et al. : Crossbar arrays for Storage Class Memory and non-Von Neumann computing. 2015. European Phase-Change and Ovonic Symposium (E\PCOS), Amsterdam, Netherlands, September 6-8, 2015.
R. M. Shelby; G. W. Burr; I. Boybat; C. Di Nolfo : Non-volatile memory as hardware synapse in neuromorphic computing: A first look at reliability issues. 2015. 2015 IEEE International Reliability Physics Symposium (IRPS), Monterey, CA, USA, 19-23 April 2015. p. 6A.1.1-6A.1.6. DOI : 10.1109/IRPS.2015.7112755.
G. W. Burr; R. M. Shelby; S. Sidler; C. Di Nolfo; J. Jang et al. : Experimental Demonstration and Tolerancing of a Large-Scale Neural Network (165 000 Synapses) Using Phase-Change Memory as the Synaptic Weight Element; Ieee Transactions On Electron Devices. 2015. DOI : 10.1109/Ted.2015.2439635.
I. Boybat; S. Sidler; C. Di Nolfo; R. M. Shelby; P. Narayanan et al. : PCM for Neuromorphic Applications: Impact of Device Characteristics on Neural Network Performance. 2015. European Symposium on Phase Change and Ovonic Science 2015, Amsterdam, Netherlands, September 6-8, 2015.
G. Burr; P. Narayanan; R. Shelby; S. Sidler; I. Boybat et al. : Large-scale neural networks implemented with nonvolatile memory as the synaptic weight element: comparative performance analysis (accuracy, speed, and power). 2015. International Electron Devices Meeting (IEDM 2015), Washington, DC, 7-9 December, 2015.
A. Akin; I. Baz; B. Atakan; I. Boybat; A. Schmid et al. : A Hardware-Oriented Dynamically Adaptive Disparity Estimation Algorithm and its Real-Time Hardware. 2013. 23rd ACM International Great Lakes Symposium on VLSI (GLSVLSI-2013), Paris, France, May 2-4 2013. p. 155-160. DOI : 10.1145/2483028.2483082.
A. Akin; Y. Leblebici; A. Schmid; I. Baz; I. Boybat et al. ; Hardware-Oriented Dynamically Adaptive Disparity Estimation Algorithm and its Real-Time Hardware. US9756312 ; US2015319419 . 2015.