Chair: Dr. Anupam Chattopadhyay, Nanyang Technological University, Singapore
Co-chair: Dr. Zheng Wang, Shenzhen Institutes of Advanced Technology, China

Dr. Anupam Chattopadhyay -- Anupam Chattopadhyay received his B.E. degree from Jadavpur University, India, MSc. from ALaRI, Switzerland and PhD from RWTH Aachen in 2000, 2002 and 2008 respectively. From 2008 to 2009, he worked as a Member of Consulting Staff in CoWare R&D, Noida, India. From 2010 to 2014, he led the MPSoC Architectures Research Group in RWTH Aachen, Germany as a Junior Professor. Since September 2014, he is appointed as an assistant Professor in SCSE, NTU and also holds an honorary adjunct appointment at SPMS, NTU.
During his doctoral studies, he worked on automatic RTL generation from the architecture description language LISA, which led to a spin-off, and subsequently was acquired by a leading EDA vendor. Anupam currently heads a team of 20+ researchers, overseeing projects in the area of computer architectures, security, design automation and emerging technologies. He is a member of ACM and a senior member of IEEE.
Dr. Zheng Wang -- Zheng Wang received his B.Sc. degree from Shanghai Jiao Tong University, M.Sc. in Electronic Engineering from Technische Universität München and PhD from RWTH-Aachen University. From 2008 till 2009, he worked in the mobile sector of Infineon Technologies AG in Munich. From 2015 till 2016, he worked in the Bio-inspired Reconfigurable Analog INtegrated (BRAIN) Systems Lab, Nanyang Technological University, Singapore in the field of neuromorphic ASIC and hardware security. In 2017 he joined the Center for Automotive Electronics, Shenzhen Institutes of Advanced Technology as an Assistant Professor.
He has published 30 papers in international journals and conferences including the best paper candidate in DATE'16 and best poster candidate in DATE'15. Currently he leads both teams of reconfigurable neuromorphic computing and perception/decision systems for autonomous vehicle in SIAT.

Autonomous vehicles (AVs) are emerging as the most important technological innovation that combines the recent growth in computing power, data processing and communication to deliver a fantastic system delegating more and more works to the machine from human. The possibilities enabled by AV are endless, ranging from self-driving taxi, automated logistics, last mile transportation, disaster management, and in general, empowering a much larger set of robotics application. The phases those turn the wheels of an autonomous vehicle, are perception, decision and actuation. Among these, the major highlight of recent research has been perception through diverse sensors, and rapid decision through an aggressive, in-vehicle fog computing setup or via cloud-based service providers, or through collaborative decision-making through multiple connected AVs.

A key challenge in the perception and decision-making of AV systems is to have low-overhead, smart and secure integrated on-board systems. As a result, there is a series of recent innovations that connected deep learning, lightweight security and high-performance computing with AV protocols. In this session, we will take a sneak peek into the security, safety and computing challenges for AV, as well as the corresponding solutions.

The contributing papers cover various novel perspectives of autonomous driving, including security IP, AI engine (reconfigurable and dedicate design for reinforcement learning), strategy (block-chain-based data aggregation, vector map assisted navigation) and simulation technique for ADAS. The scope of papers targets the bridge between circuits/system and perception/decision of AVs. Such synergy stimulates ideas, designs and implementations while will increase the attendees of APCCAS to explore the field of AV.