IMS2023 Teaser Videos

Artificial Intelligence and Machine Learning for RF and Microwave Design: Practical Technologies for Present and Future Applications

Speaker Bio: Dr. Jianjun Xu is recognized internationally as a leading innovator of advanced artificial neural network (ANN) technology and its practical applications to a wide range of microwave and RF engineering problems. He is presently Senior Machine Learning Engineer at Keysight Laboratories, Keysight Technology, Inc., in Santa Rosa CA. His ANN research has been integrated into leading commercial simulators and measurement-based design flows, including transistor characterization and nonlinear modeling of GaAs and GaN FETs, cryogenic CMOS devices, lithium-ion battery models, TCAD-to-circuit links, and more. Dr. Xu received the Ph.D. Degree in Electrical Engineering from Carleton University, Ottawa, Canada, in 2004, and is a frequent technical reviewer for the IEEE on topics of AI/ML and ANNs.

Introduction to Quantum Computing: Qubits, Gates, and Algorithms

Speaker Bio: Dr. William D. Oliver is appointed Henry Ellis Warren (1894) Professor of Electrical Engineering and Computer Science and Professor of Physics at the Massachusetts Institute of Technology. He serves as the inaugural Director of the MIT Center for Quantum Engineering and as Associate Director of the MIT Research Laboratory of Electronics. Will’s research interests and expertise include the materials, fabrication, design, and implementation of superconducting qubit processors, as well as the development of cryogenic packaging and control electronics for extensible quantum computing applications.
Will is a Fellow of the American Physical Society, Senior Member of the IEEE, serves on the National Quantum Initiative Advisory Committee and the US Committee for Superconducting Electronics, and was a coauthor of the 2019 National Academies consensus study report entitled, “Quantum Computing: Progress and Prospects”. He received his B.S. in EE and B.A. in Japanese from the University of Rochester in 1995, S.M in EECS from MIT in 1997, and Ph.D. in Electrical Engineering from the Stanford University in 2003. 

Emerging Trends in 2.5D and 3D Heterogeneous Integration Technologies

Speaker Bio: Muhannad S. Bakir is the Dan Fielder Professor in the School of Electrical and Computer Engineering and the Interim Director of the 3D Systems Packaging Research Center at Georgia Tech. His areas of interest include 2.5D and 3D heterogeneous integration technologies, photonic interconnect networks and co-packaging, embedded cooling and power delivery for emerging heterogeneous integration architectures, and flexible electronics for healthcare. Dr. Bakir and his research group have received more than thirty paper and presentation awards including six from the IEEE Electronic Components and Technology Conference (ECTC), four from the IEEE International Interconnect Technology Conference (IITC), and one (best invited paper) from the IEEE Custom Integrated Circuits Conference (CICC). Dr. Bakir’s group was awarded Best Paper Awards from the 2014 and 2017 IEEE Transactions on Components Packaging and Manufacturing Technology (TCPMT). Dr. Bakir is the recipient of the 2013 Intel Early Career Faculty Honor Award, 2012 DARPA Young Faculty Award, 2011 IEEE CPMT Society Outstanding Young Engineer Award, and was an Invited Participant in the 2012 National Academy of Engineering Frontiers of Engineering Symposium. Dr. Bakir is also the recipient of the 2018 IEEE Electronics Packaging Society (EPS) Exceptional Technical Achievement Award “for contributions to 2.5D and 3D IC heterogeneous integration, with focus on interconnect technologies.” He is also the co-recipient of the 2018 McKnight Foundation Technological Innovations in Neuroscience Awards. In 2020, Dr. Bakir was the recipient of the Georgia Tech Outstanding Doctoral Thesis Advisor Award. He is also the recipient of several teaching awards, including the 2014 and 2015 Georgia Institute of Technology Class of 1940 Course Survey Teaching Effectiveness Award, and the 2020 Student Recognition of Excellence in Teaching: Class of 1934 Award.