Ghazi Sarwat Syed           

Short Biography

Ghazi Sarwat Syed works as a Research Staff Member at IBM Research located in Zurich, Switzerland. He completed his Bachelor of Engineering degree from PSG College of Technology in 2015, followed by a Ph.D. degree from the University of Oxford in 2019, specializing in Metallurgical Engineering and Materials Science.  Ghazi's current research focuses on exploring and implementing processing in-memory technologies for deep learning accelerators, which spans both electronics and optics domains. His work entails creating devices, utilizing new functional materials, and achieving algorithmic breakthroughs in this field. 

His work has been recognized with a Forbes 30 Under 30 award, the Innovator Award from the Indian National Academy of Engineering, the Felix Scholarship from Oxford University, the Foundation Award from the Society of Automotive Engineering, a World Steel Association award in the Asia Category, and a top science project award from the Indian Science Congress. Additionally, he has been awarded with a Brahm Prakash Medal, the Best Literature Review award from Taylor and Francis, the Best Thesis and Best Outgoing Student award. He has also contributed to 16 international patents and his research has been extensively featured in renowned journals and conferences such as Nature Nanotechnology, Nature Communications, Science Advances, Advanced Materials, Advanced Functional Materials, and Nano Letters, with a primary focus on materials science, nanoelectronics, and neuromorphic algorithms.

Employing an interdisciplinary and collaborative approach to science, Ghazi collaborates with IBM's global team to devise chipsets for practical artificial intelligence workload demonstrations. Furthermore, he partners with renowned European universities to design functional components and algorithms for in-memory computing based on silicon photonics. Additionally, he serves as a reviewer for distinguished journals and conferences, and is presently a member of the organizing committee for the MRS Spring 2023 Phase Change Materials Symposium. Dr. Ghazi Syed firmly advocates for the communication of scientific findings and STEM education, and is readily available to participate in discussions and initiatives aimed at supporting these objectives.

Invited Talks/Lectures

-"Tutorial: A Gentle Introduction to In-Memory Computing", Mauterndorf Winterschool (2023-Austria)

-“Chalcogenide Computational Memory” at European Phase Change and Ovonics Symposium, EPCOS (2022-Oxford)

-“Concepts of In-memory Computing” at ETH University (2022-Zurich)

-“Neuromorphic Computing and Neural Networks” at Club House (2022-Podcast)

-“Phase Change Computational Memory” at The Materials Research Society of India, MRSI (2022-India)

-“Biomimetic Phase Change Memtransistive Synapse” at European Phase Change and Ovonics Symposium, EPCOS (2021-UK)

-“Brain-Inspired Photonics Computing using Non-Volatile Memories” at The European Conference on Optical Communication, ECOC (2021-France)

-“In-memory Computing using Phase Change Materials” at Photonics North (2021-Canada)

-“Nanoelectronics with Low-dimensional Thin Films” at IBM Research (2019-Zurich)

-“Light-Matter Interaction in Phase Change Materials” at European Phase Change and Ovonics Symposium, EPCOS (2018-Catania)

-“Two Dimensional Materials for Nanoelectronics” at Public Engagement Lectures (2018-Oxford)

-“Phase Change Materials for Optical Applications” at Symposium on Amorphous Chalcogenides (2018-Lake District)

-“Truly Flexible Technologies” at Wearable and Flexible Technology Symposium, WAFT (2018 and 2017-Oxford)

-“Graphene Nanogaps: It's Performance Limits" at The International Union of Materials Research Societies, IUMRS (2018-Bangalore)

-“Nanogap Electrodes for Nanoelectronics" at The Micro and Nano Engineering, MNE (2017-Sweden)

-“Phase Change Memory using graphe Nanogaps" at The Micromechanics and Microsystems Europe Workshop, MME (2017-Portugal)

In the News

-Artificial Neurons Mimic Complex Brain Capabilities

-Forbes 30 Under 30 Honoree

-MRS Spring Meeting 2023 Phase Change Materials Symposium

-Designing and Writing a Review Paper

-IBM scientists give artificial neural networks a new look for neuromorphic computing

-An “Optomemristor” for Neural-Net Computing

-An Integrated Photonics Engine for Unsupervised Correlation Detection

-Lighting up artificial neural networks

-Photonics offers a solution to latency issues for AI

-What ultimately limits the scaling of graphene nanogap electrodes

-Studying strain effects in 2D materials using Kelvin Probe Microcopy

-Writing a scientific literature review

-Techian To Oxonian