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SHORT BIOGRAPHY:

Abu Sebastian was born in Kerala, India. He received a B. E. (Hons.) degree in Electrical and Electronics Engineering from BITS Pilani, India and M.S. and Ph.D. degrees in Electrical Engineering (minor in Mathematics) from Iowa State University. Since 2006, he is a Research Staff Member at IBM Research - Zurich in Rüschlikon, Switzerland. He was a contributor to several key projects in the space of storage and memory technologies and currently manages the research effort on in-memory computing at IBM Research - Zurich. He has published over 180 articles in journals and conference proceedings. He also holds over 50 granted patents.

Dr. Sebastian is a co-recipient of the 2009 IEEE Control Systems Technology Award and the 2009 IEEE Transactions on Control Systems Technology Outstanding Paper Award. In 2013 he received the IFAC Mechatronic Systems Young Researcher Award for his contributions to the field of mico-/nanoscale mechatronic systems. In 2015 he was awarded the European Research Council (ERC) consolidator grant and in 2020, he was awarded an ERC Proof-of-concept grant. He is an IBM Master Inventor since 2016. He was named Principal and Distinguished Research Staff Member in 2018 and 2020, respectively. In 2019 he received the Ovshinsky Lectureship Award for his contributions to "Phase-change materials for cognitive computing".

SELECTED PUBLICATIONS:

BOOK:

• S. Spiga, A. Sebastian, D. Querlioz, B. Rajendran, "Memristive devices for brain-inspired computing", Elsevier, 2020

IN-MEMORY COMPUTING:

• J. Feldmann, N. Youngblood, M. Karpov, H. Gehring, M. Stappers, M. Le Gallo, X. Fu, A. Lukashchuk, A. S. Raja, J. Liu, C. D. Wright, A. Sebastian*, T. J. Kippenberg*, W. H. P. Pernice*, H. Bhaskaran*, "Parallel convolution processing using an integrated photonic tensor core", Nature, 2021
• G. Karunaratne, M. Le Gallo, G. Cherubini, L. Benini, A. Rahimi*, A. Sebastian*, "In-memory hyperdimensional computing", Nature Electronics, 2020
• A. Sebastian*, M. Le Gallo, R. Khaddam-Aljameh, E. Eleftheriou, "Memory devices and applications for in-memory computing", Nature Nanotechnology, 2020
• V. Joshi, M. Le Gallo*, S. Haefeli, I. Boybat, S. R. Nandakumar, C. Piveteau, M. Dazzi, B. Rajendran, A. Sebastian*, E. Eleftheriou, "Accurate deep neural network inference using computational phase-change memory", Nature Communications, 2020
• C. Rios, N. Youngblood, Z. Cheng, M. Le Gallo, W. H. P. Pernice, C. D. Wright, A. Sebastian*, H. Bhaskaran*, "In-memory computing on a photonic platform", Science Advances, 2019
• I. Giannopoulos*, A. Sebastian*, M. Le Gallo, V. P. Jonnalagadda, M. Sousa, M. N. Boon, E. Eleftheriou, "8-bit precision in-memory multiplication with projected phase-change memory", Proc. IEDM, 2018 (Highlight paper)
• Le Gallo*, A. Sebastian*, R. Mathis, M. Manica, H. Giefers, T. Tuma, C. Bekas, A. Curioni, E. Eleftheriou, “Mixed-precision in-memory computing”, Nature Electronics, 2018
• Sebastian*, T. Tuma, N. Papandreou, M. Le Gallo, L. Kull, T. Parnell, E. Eleftheriou, “Temporal correlation detection using computational phase-change memory”, Nature Communications, 2017
• Hosseini, A. Sebastian, N. Papandreou, C. D. Wright, H. Bhaskaran, “Accumulation-based computing using phase change memories with FET access devices”, IEEE Electron Device Letters, 2015

NEUROMORPHIC COMPUTING:

• B. Rajendran, A. Sebastian, M. Schmuker, N. Srinivasa, E. Eleftheriou, "Low-power neuromorphic hardware for signal processing applications: A review of architectural and system-level design approaches", IEEE Signal Proc. Magazine, 2019
• A. Sebastian*, M. Le Gallo, G. W. Burr, S. Kim, M. BrightSky, E. Eleftheriou, "Tutorial: Brian-inspired computing using phase-change memory devices", J. Appl. Phys., vol. 124(11), 111101, 2018
• T. Moraitis*, A. Sebastian* and E. Eleftheriou, "Short-term plasticity in neuromorphic learning", IEEE Trans. on Nanotech., vol. 12(3), 45-53, 2018
• Boybat*, M. Le Gallo, S. R. Nandakumar, T. Moraitis, T. Parnell, T. Tuma, B. Rajendran, Y. Leblebici, A. Sebastian*, E. Eleftheriou, “Neuromorphic computing with multi-memristive synapses”, Nature Communications, 2018
• Gong, T. Ide, S. Kim, I. Boybat, A. Sebastian, V. Narayanan, T. Ando*, “Signal and noise extraction from analog memory elements for neuromorphic computing”, Nature Communications, 2018
• G. W. Burr, R. M. Shelby, A. Sebastian et al., “Neuromorphic computing using non-volatile memory”, Advances in Physics X, vol. 2(1), pp. 89-124, 2017
• Tuma, A. Pantazi, M. Le Gallo, A. Sebastian, E. Eleftheriou, “Stochastic phase-change neurons”, Nature Nanotechnology, 2016 (Cover)

EXPLORATORY MEMORY:

• M. Le Gallo and A. Sebastian, "An overview of phase-change memory device physics", J. Phys. D. Appl. Phys., 2020
• Salinga*, B. Kersting, I. Ronneberger, V. P. Jonnalagadda, X. T. Vu, M. Le Gallo, I. Giannopoulos, O. Cojocaru-Miredin, R. Mazzarello, A. Sebastian*, “Monatomic phase change memory”, Nature Materials, 2018 (Cover)
• Le Gallo, D. Krebs, F. Zipolli, M. Salinga, A. Sebastian, “Collective structural relaxation in phase-change memory devices”, Adv. Electronic Materials, 2018
• W. Burr, M. J. Brightsky, A. Sebastian et al., “Recent progress in phase-change memory technology”, IEEE Journal on emerging and selected topics in circuits and systems, 2016
• Le Gallo, A. Athmanathan, D. Krebs, A. Sebastian, “Evidence for thermally assisted threshold switching behavior in nanoscale phase-change memory cells”, Journal of Applied Physics, 119, 025704, 2016
• Le Gallo, M. Kaes, A. Sebastian, D. Krebs, “Subthreshold electrical transport in amorphous phase change materials”, New Journal of Physics., 2015
• C. A. Santini*, A. Sebastian*, C. Marchiori, V. P. Jonnalagadda,  L. Dellmann, W. W. Koelmans, M. D. Rossell, C. P. Rossel, E. Eleftheriou, “Oxygenated amorphous carbon for resistive memory applications”, Nature Communications, 2015
• W. Koelmans*, A. Sebastian, V. P. Jonnalagadda, D. Krebs, L. Dellmann, E. Eleftheriou, Projected phase-change memory devices, Nature communications, 6, 2015
• A. Sebastian*, M. Le Gallo, D. Krebs, “Crystal growth within a phase change memory cell”, Nature Communications, 5(4314), 1-9, 2014
• A.  Sebastian*, A. Pauza , C. Rossel, R. M. Shelby, A. F. Rodriguez, H. Pozidis and E. Eleftheriou, “Resistance switching at the nanometer scale in amorphous carbon”, New Journal of Physics, vol. 13, pp. 013020, 2011
• Sebastian*, N. Papandreou, A. Pantazi, H. Pozidis and E. Eleftheriou, “Non-resistance based cell-state metric for multi-level phase change memory”, Journal of Applied Physics, 110, 084505, 2011

NANOTECHNOLOGY:

• Shamsudhin, N. Laeubli, H. B. Atakan, H. Vogler, C. Hu, W. Haeberle, A. Sebastian, U. Grossniklaus and B. J. Nelson, “Massively parallelized pollen tube guidance and mechanical measurements on a Lab-on-a-Chip platform”, PLOS ONE, 11(12), 2016
• Tuma, A. Pantazi, D. R. Sahoo, P. Eib, G. Salis, H. Pozidis and A. Sebastian, “A high-bandwidth spintronic position sensor”, Nanotechnology, 25(37), 375501, 2014
• T. Tuma, A. Sebastian, J. Lygeros and A. Pantazi, “Four pillars of nanopositioning,” IEEE Control Systems Magazine, 2013
• Tuma, J. Lygeros, V. Kartik, A. Sebastian and A. Pantazi, “High-speed multiresolution scanning probe microscopy based on Lissajous scan trajectories,” Nanotechnology, 23(18), pp. 185501, May 2012
• A. Sebastian* and A. Pantazi, “Nanopositioning With Multiple Sensors: A Case Study in Data Storage,” IEEE Transactions on Control Systems Technology, vol. 20(2), pp. 382-394, Mar. 2012.
• Bazaei, S. O. R. Moheimani and A. Sebastian, “An Analysis of Signal Transformation Approach to Triangular Waveform Tracking”, Automatica, vol. 47(4), pp. 838-847, Apr. 2011
• H. Bhaskaran, B. Gotsmann, A. Sebastian, U. Drechsler, M. A. Lantz, M. Despont, P. Jaroenapibal, R. W. Carpick, Y. Chen and K. Sridharan, “Ultralow nanoscale wear through atom-by-atom attrition in silicon-containing diamond-like carbon”, Nature Nanotechnology, vol. 5, pp. 181-185, Mar. 2010
• Bhaskaran, A. Sebastian and M. Despont, “Nanoscale PtSi tips for conducting probe technologies”, IEEE Transactions on Nanotechnology, vol. 8, no. 1, pp. 128-131, January 2009.
• A. Sebastian* and D. Wiesmann, “Modeling and experimental identification of silicon micro-heater dynamics: A systems approach”, IEEE/ASME Journal of Micro-electromechanical Systems, vol. 17, No. 4, pp. 911-920, Aug. 2008.
• A. Sebastian*, A. Pantazi, H. Pozidis, and E. Eleftheriou, “Nanopositioning for Probe-based Data Storage,” IEEE Control Systems Magazine, pp. 26-35, August 2008
• Pantazi, A. Sebastian et al.,” IBM Journal of Research and Development, vol. 52, no. 4/5, Jul/Sep 2008.
• A. Sebastian* and S. Salapaka, “Design methodologies for robust nanopositioning”, IEEE Transactions on Control Systems Technology, vol. 13(6), pp. 868-876, Nov. 2005.
• A. Sebastian*, M. V. Salapaka, D. J. Chen and J. P. Cleveland, “Harmonic and power balance tools for atomic force microscopy”, Journal of Applied Physics, vol. 89(11), pp. 6473-6480, Jun. 2001.

SELECTED TALKS/LECTURES/PANELS:

Invited Tutorial, Photonics online meetup, Jan. 2021

Invited Talk, NEUROTECH educational program, Jan. 2021

Invited Lecture, Computer Architecture Fall 2020, ETH Zurich, Dec. 2020

Invited Talk, CASCON, Nov. 2020

Panelist, Vaishwik Bharatiay Vaigyanik Summit, Oct. 2020

Panelist, International workshop on network on chip architectures, Oct. 2020

Panelist, AICAS, Sep. 2020

Invited Lecture, University College London, March 2020

Invited Tutorial, IEDM, San Francisco, Dec. 2019

Invited Lecture, Institute of Neuroinformatics, Univ. Zurich., Nov. 2019

Invited Talk, Nature conference on neuromorphic computing, Beijing, Oct. 2019

Ovshinsky Lecture, EP\COS, Grenoble, Sep. 2019

Invited Talk, CLEO Europe, Munich, Germany, June 2019

Invited Talk, VLSI, Kyoto, Japan, June 2019

Tutorial, ISCAS, Sapporo, Japan, May 2019

Invited Lecture, Sabanci University, Istanbul, Turkey, April 2019

Invited Lecture, Bilkent University, Ankara, Turkey, April 2019

Invited Talk, DATE Workshop, Florence, Italy, March 2019

Invited Lecture, University of Oxford, Oxford, UK, March 2019

Plenary Talk, ICEE, Bangalore, India, Dec 2018

Invited Talk, NVMTS, Sendai, Japan, October 2018

Invited Talk, E/PCOS, Catania, Italy, September 2018

Invited Talk, CIMTEC, Perugia, Italy, June 2018

Invited Talk, MRS Spring Meeting, Phoenix, Arizona, USA, April 2018

Invited Lecture, Computer Systems Colloquium, Stanford University, Stanford, USA, Mar 2018

Invited Talk, mDAC: Memristor Technology, Desing, Automation and Computing, HiPEAC, Manchester, UK, Jan 2018

Keynote Lecture, 17th Non-volatile Memory Technology Symposium, Aachen, Germany, 2017

Keynote Lecture, International Conference on Memristive Materials, Devices and Systems, Athens, Greece, 2017

Invited Talk, Beyond CMOS: From Devices to Systems, Haifa, Israel, 2017

Invited Talk, MINDMEM Workshop, Lausanne, Switzerland, 2017

Invited Tutorial, MRS Spring Meeting, Phoenix, Arizona, USA, 2017

Invited Lecture, CDT Advanced Technology Lectures, Univ. of Cambridge, UK, 2016

Invited Talk, CIMTEC, Perugia, Italy, 2016

Invited Talk, E/PCOS, Cambridge, UK, 2016

Invited Talk, Memristive Symposium, Dresden, Germany, 2016

Invited Talk, Institute for Mathematics and its Applications, Minneapolis, Minnesota, USA, 2016

Invited Talk, MRS Spring Meeting, Phoenix, Arizona, USA, 2016

Keynote Talk, Memrisys, Cyprus, 2015

Invited Lecture, Univ. of Oxford, UK, 2015

Invited Talk, Swiss Nano Convention, Neuchatel, Switzerland, 2015

RESEARCH IN THE NEWS:

Light and in-memory computing help AI achieve ultra-low latency

IBM is using light, instead of electricity, to create ultra-fast computing

IBM adds noise to boost AI's accuracy on analog memory

The brains behind emerging AI

Photonic devices compute in memory: Nature highlight

In-memory computing using photonic memory devices

IBM reveals 8-bit analog chip with phase-change memory

Dual 8-bit breakthroughs bring AI to the edge

Brain-inspired architecture could improve how computers handle data and advance AI

Keep it simple: Towards single-elemental phase-change memory

Novel synaptic architecture for brain inspired computing

Glassy antimony makes monatomic phase change memory

IBM's new in-memory computing solution makes business AI training faster, easier

IBM: Our in-memory computing breakthrough will cut cost of training AI

IBM scientists demonstrate mixed-precision in-memory computing for the first time; Hybrid design for AI hardware

Understanding resistance drift in amorphous semiconductors

IBM Blog on National Inventor's day

IBM can run an experimental AI in memory, not on processors (MIT Tech Review)

Computational Memory (IBM Blog)

IBM PhD Fellowship to Nandakumar (IBM Blog)

Unsupervised learning with artificial neurons (IBM Blog)

Newsweek article on phase-change neuron

Kuenstliche Neuronen aus Rueschlikon

ERC Consolidator Grant (IBM Blog)

Projected memory (EE Times)

Projected Memory (Le Monde)

Carbon memory (EE Times)

Sub-threshold transport in PCM (EE Times)

Threshold switching in PCM (EE Times)

Crystal growth in PCM (EE Times)

Crystal growth in PCM (IBM Blog)

Profile of a scientist (IBM Blog)