Date-Driven Computing for Smart Vehicles

Dr. Yajun Ha, ShanghaiTech University, China

Organized by IEEE Circuits and Systems Singapore Chapter

Abstract

Smart vehicles have been considered as an effective solution to many challenges in road traffic systems, for example lower accident rate, lower energy consumption per hundred kilometer, lower pollution and so on. As a result, this field has become a hot competition area for all major IT and vehicle manufactures in the recent years. However, there are still substantial technical and non-technical challenges ahead before smart vehicles, especially highly autonomous vehicles can be widely deployed in the mass market. In this talk, we focus on the general smart vehicle introduction, and the technical challenges, and the data-driven computing for smart vehicles. For the data-driven computing part, we will discuss a learning based approach for smart vehicles. This includes the sensor system for data collection, dataset preparation, learning from dataset, acceleration for data-driven computing and some application demonstrations.

Speaker Biography

Dr. Yajun Ha is currently a Professor at ShanghaiTech University, China. Before this, he was a Scientist and Co-Director, I2R-BYD Joint Lab at Institute for Infocomm Research, A*Star, Singapore, and an Adjunct Associate Professor at the Department of Electrical & Computer Engineering, National University of Singapore. Before his work at A*Star, he was an Assistant Professor with National University of Singapore. He received his Ph.D. degree from Katholieke Universiteit Leuven (KULeuven), Leuven, Belgium, in 2004 and worked at the same period as a researcher with the Inter-University MicroElectronics Center (IMEC), Leuven, Belgium. His research interests include reconfigurable computing, ultra-low power digital circuits and systems, and embedded system architecture and design tools for applications in hardware security, smart vehicles and machine learning. He has published around 100 internationally peer-reviewed journal/conference papers on these topics.

He has served a number of positions in the professional communities. He serves as the Associate Editor for the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS-PART I: Regular Papers (2016-2017), the Associate Editor for the IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS-PART II: EXPRESS BRIEFS (2011-2013), the Associate Editor for the IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS (2013-2014), and the Journal of Low Power Electronics (since 2009). He has served as the General Co-Chair of ASP-DAC 2014; Program Co-Chair for FPT 2010 and FPT 2013; Chair of the Singapore Chapter of the IEEE Circuits and Systems (CAS) Society (2011 and 2012); Member of ASP-DAC Steering Committee; and Member of IEEE CAS VLSI and Applications Technical Committee. He has been the Program Committee Member for a number of well-known conferences in the fields of FPGAs and design tools, such as DAC, DATE, ASP-DAC, FPGA, FPL and FPT.

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Open 5G Platform

Dr. Yang Yang, Chinese Academy of Sciences & ShanghaiTech University, China

Organized by IEEE Circuits and Systems Singapore Chapter

Abstract

Facebook has recently announced its OpenCellular platform for promoting open-source wireless access technology developments and broader applications. In this talk, we will give an introduction of an open 5G platform, which applies SDN and NFV techniques to realize the key functions of a telecom operator according to the 3GPP standard on general CPU/GPU computing platform. It is very adaptive and flexible for supporting a variety of internet of things (IoT) applications in vertical industries. New technical challenges and potential applications of this open platform in delay-sensitive control areas will be fully discussed.

Speaker Biography

Dr. Yang Yang is currently a professor with Shanghai Institute of Microsystem and Information Technology (SIMIT), Chinese Academy of Sciences, serving as the Director of CAS Key Laboratory of Wireless Sensor Network and Communication, and the Director of Shanghai Research Center for Wireless Communications (WiCO). He is also a Distinguished Adjunct Professor with the School of Information Science and Technology, ShanghaiTech University. Prior to that, he has held faculty positions at University College London (UCL), Brunel University, and The Chinese University of Hong Kong.

Yang is a member of the Chief Technical Committee of the National Science and Technology Major Project “New Generation Mobile Wireless Broadband Communication Networks” (2008-2020), which is funded by the Ministry of Industry and Information Technology (MIIT) of China. In addition, he is on the Chief Technical Committee for the National 863 Hi-Tech R&D Program “5G System R&D Major Projects”, which is funded by the Ministry of Science and Technology (MOST) of China. Since January 2017, he has been serving the OpenFog Consortium as the Director for Greater China Region.

Yang’s current research interests include wireless sensor networks, Internet of Things, Fog computing, Open 5G, and advanced wireless testbeds. He has published more than 150 papers and filed over 80 technical patents in wireless communications.

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Medical Informatics: Data Analytics in Healthcare

Dr. Liu Nan, Singapore General Hospital & Duke-NUS Medical School, Singapore

Organized by IEEE Circuits and Systems Singapore Chapter & Centre for Bio Devices and Signal Analysis (VALENS)

Abstract

Data analytics have been applied to a wide spectrum of applications such as information retrieval, circuits and systems, bioinformatics, computational finance, robotics, computer vision, image processing, and medicine. With the advancement of computational power, sophisticated data analytics methods gained popularity in converting imagination into reality. Conventional statistical and mathematical methods continue to play important roles while new emerging technologies such as machine learning, data mining, and natural language processing have established their reputations in solving complex and challenging problems in medicine. Applying advanced computational techniques on medical applications provides numerous opportunities for better healthcare delivery. This talk aims to provide the audience a brief introduction to the latest development in healthcare data analytics with several real-world examples in Singapore General Hospital.

Speaker Biography

Dr Liu Nan is currently a Principal Research Scientist in Singapore General Hospital with a joint appointment at Duke-NUS Medical School as an Adjunct Assistant Professor. He received his PhD degree from School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. Before joining Singapore General Hospital, Liu Nan was a Data Scientist in a US start-up company working on design and implementation of data-driven algorithms for text data mining and video analytics. His research interests include biomedical and health informatics, machine learning, data mining, signal processing, and statistical analysis with applications in cardiovascular research and emergency medicine. He has published many articles in international peer-reviewed journals, and one US patent on a triage system for patients risk stratification. He is a regular reviewer for more than 30 journals.

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Chanllenges and Solutions for Automotive Security & Privacy

Dr. H. Gregor Molter

Head of Security & Privacy Research Embedded Systems

Security & Privacy Competence Center, SCC

Cross Divisional Systems & Technology - Corporate S&T

Continental Teves AG & Co. oHG, Germany

Organized by IEEE Circuits and Systems Singapore Chapter

Abstract

In this talk, a general introduction including current challenges for automotive security and privacy is given. It is highlighted how Continental is introducing a security life cycle in terms of a secure system engineering process and incident response management process to facilitate secure products. Our methodology for threat analysis, risk assessment, and risk treatment is detailed and discussed in relation of past research project like EVITA.On overview of our ongoing standardization efforts in ISO AWI 21434 "Road Vehicles - Cybersecurity Engineering" concludes the talk.

Speaker Biography

Dr. H. Gregor Molter works at Continental in the Security and Privacy Competence Center since 2012. He is responsible for the Security and Privacy Research Embedded Systems with a strong focus on Automotive Electronic Control Units. Before he started his professional career at Continental, he studied Computer Science at the Technische Universität Darmstadt in Germany. After his studies, he was working there as a research assistant in the group “Integrated Circuits and Systems Lab”. During his time in academia, he was part of the team hacking the DECT telephone system. Finally, he received his doctoral degree in the field of Hardware / Software Co-Design in 2012.

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An Anatomy of Social Media Popularity

Dr. Lexing Xie, Associate Professor, Australian National University, Australia

Organized by IEEE Circuits and Systems Singapore Chapter & Centre for Infocomm Technology (INFINITUS), School of EEE, NTU

"Sponsored by the IEEE Circuits and Systems Society under its Distinguished Lecturer Program"

Abstract

How did a video go viral? Or will it go viral, and when? These are some of the most intriguing yet difficult questions in social media analysis. This talk will first provide a broad overview of recent research in understanding the predicting popularity, driven by larger amounts of online data and more understanding of human perception and psychology.  I will then cover a few recent results from my group on understanding and predicting popularity, especially for YouTube videos. I will start by describing a unique longitudinal measurement study on video popularity history, and introduce popularity phases, a novel way to describe the evolution of popularity over time. I will then discuss a physics-inspired stochastic model that connects exogenous stimuli and endogenous responses to explain and forecast popularity. With such novel representation and new models, we can correlate video content type to popularity patterns, make better predictions, describe the endo-exo factors driving popularity, and forecast the effects of promotion campaigns.

Speaker Biography

Lexing Xie is Associate Professor in the Research School of Computer Science at the Australian National University, she leads the ANU Computational Media lab (https://cm.cecs.anu.edu.au), and is also affiliated with the machine learning research group at NICTA.  She was research staff member at IBM T.J. Watson Research Center in New York from 2005 to 2010, and adjunct assistant professor at Columbia University 2007-2009. She received B.S. from Tsinghua University, Beijing, China, and M.S. and Ph.D. degrees from Columbia University, all in Electrical Engineering. Her research interests are in machine learning, multimedia, social media. Of particular recent interest are stochastic time series models, neural network for sequences, and active learning, applied to diverse problems such as multimedia knowledge graphs, modeling popularity in social media, social recommendation. Lexing's research has received six best student paper and best paper awards between 2002 and 2015, and a Grand Challenge Multimodal Prize at ACM Multimedia 2012. She currently serves an associate editor of ACM Trans. MM, ACM TiiS and PeerJ Computer Science. Her service roles include the program and organizing committees of major multimedia, machine learning, web and social media conferences.

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Circuit Level Optimization of Fixed-coefficient Digital FIR Filters

Dr. Yajun Yu, Associate Professor, South University of Science and Technology, Shenzhen, China

Organized by IEEE Circuits and Systems Singapore Chapter & Centre for Infocomm Technology (INFINITUS), School of EEE, NTU

Abstract

Digital finite impulse response (FIR) filter is one of the most important building blocks in many digital signal processing (DSP) circuits and systems. For very large scale integration (VLSI) implementation of fixed-coefficient FIR filters, the resource-hungry multipliers can be realized by a multiple constant multiplication (MCM) block using shift and add/subtract operations. The products generated by the MCM block are then delayed and accumulated using the product accumulation block. In this talk, the circuit level optimization of FIR filters, in particular the MCM block and product accumulation block, and their efficient VLSI implementation are discussed.

Speaker Biography

Ya Jun Yu received the B.Sc. and M.Eng. degrees in biomedical engineering from Zhejiang University (ZJU), Hangzhou, China, in 1994 and 1997, respectively, and the Ph.D. degree in electrical and computer engineering from the National University of Singapore (NUS), Singapore, in 2004.

She was a Teaching Assistant, Research Engineer and Research fellow with ZJU, NUS and Nanyang Technological University (NTU), respectively, from 1997 to 2005. From 2005 to 2016, she was an Assistant Professor with the School of Electrical and Electronic Engineering, NTU, Singapore. Since 2016, she has been an Associate Professor with the Department of Electrical and Electronic Engineering, South University of Science and Technology, Shenzhen, China. Her research interests include digital signal processing and VLSI circuits and systems design.

Dr. Yu has served as an associate editor for Circuits Systems and Signal Processing for 2009 - 2017, for IEEE Transactions on circuits and systems II for 2010-2013, for Digital Signal Processing (Elsevier) since 2015, and for IEEE Transactions on circuits and systems I since 2016, respectively.

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Graph Signal Processing: Techniques for Processing of Numerical Data Defined over Irregular Domain

Dr. David Tay, Associate Professor, La Trobe University, Australia

Organized by IEEE Circuits and Systems Singapore Chapter & Centre for Infocomm Technology (INFINITUS), School of EEE, NTU

Abstract

Recently there has been increasing research activity in generalizing signal processing techniques for signals defined over regular domain to signals defined over irregular domain. Graph Signal Processing (GSP) is a merging of concepts from graph theory and traditional signal processing techniques such as FFT (Fast Fourier Transform) and FIR (Finite Impulse Response) filtering. In this talk some basic concepts and ideas in GSP are first reviewed and a summary of some my research in graph wavelets and filter banks is then presented.

Speaker Biography

David B. TAY received the BEng (Electrical & Electronic) and BSc (Mathematics) degrees from the University of Melbourne and the PhD (Signal Processing) degree from Cambridge University. He was a lecturer and then assistant professor in the School of Electrical and Electronic Engineering, Nanyang Technological University from 1995 till 1999.  From July 1999 till July 2017, he was with the Department of Engineering, LaTrobe University firstly as a lecturer and subsequently as an associate professor. He is currently an adjunct associate professor in the School of Engineering and Mathematical Sciences, LaTrobe University. Presently he is an Associate Editor for the Journal of the Franklin Institute. He also serves as a member of the DSP Technical Committee in the IEEE Circuits and Systems Society. His main research interest is in the area of graph signal processing, wavelets and filter banks and he also has interest in the area of biomedical engineering.

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Rate-Distortion Optimization for Sparse Coding in Image Compression

Prof. Nam Ling

IEEE Fellow, IET Fellow

Sanfilippo Family Chair Professor

Chair, Department of Computer Engineering

Santa Clara University, U.S.A.

Organized by IEEE Circuits and Systems Singapore Chapter & Centre for Infocomm Technology (INFINITUS), School of EEE, NTU

Abstract

Traditional video and image compression in main stream standards such as H.264/AVC and H.265/HEVC adopt a hybrid coding method incorporating orthogonal transforms, motion estimation, intra prediction, and entropy coding. Such methods seem to have approached saturation on coding efficiency, and major breakthrough is hard to achieve by traditional signal processing techniques. Recently, much research has been focusing on applying machine learning approaches aiming to improve coding efficiency to another level. In this talk, we will give an overview of image/video coding and its recent progress; we will then focus on one of our group’s research using sparse coding with over-complete representation to reduce the number of coefficients representing image information, as opposed to those by a traditional discrete cosine transform (DCT) method. Dictionary with over-complete representation can be learned from data and trained by a K-SVD (singular value decomposition) algorithm. Orthogonal matching pursuit (OMP) algorithm is then applied to select dictionary elements and their coefficients to represent the image. We propose a rate-distortion optimization (RDO) approach to select the number of non-zero coefficients given a sparsity constraint. Experimental results demonstrated a very good improvement of coding efficiency by our approach over the conventional DCT-based scheme. Finally, we will highlight some of our current research.

Speaker Biography

Nam Ling received the B.Eng. degree from the National University of Singapore and the M.S. and Ph.D. degrees from the University of Louisiana, Lafayette, U.S.A. He is currently the Sanfilippo Family Chair Professor (University Endowed Chair) of Santa Clara University (U.S.A) and the Chair of its Department of Computer Engineering. From 2002 to 2010, he was an Associate Dean for its School of Engineering. Currently, he is also a Chair Professor for Fuzhou University (China), a Cuiying Chair Professor for Lanzhou University (Chair), a Distinguished Professor for Xi’an University of Posts & Telecommunications (China), a Consulting Professor for the National University of Singapore, a Guest Professor for Tianjin University (China), and a Guest Professor for Shanghai Jiao Tong University (China). He has more than 190 publications (including books) in video/image coding and systolic arrays. He also has seven adopted standards contributions and has filed/granted more than 20 U.S./European/PCT patents. He is an IEEE Fellow due to his contributions to video coding algorithms and architectures. He is also an IET Fellow. He was named IEEE Distinguished Lecturer twice and was also an APSIPA Distinguished Lecturer. He received the IEEE ICCE Best Paper Award (First Place) and the IEEE Umedia Best Paper Award. He received six awards from the University, four at the University level (Outstanding Achievement, Recent Achievement in Scholarship, President’s Recognition, and Sustained Excellence in Scholarship) and two at the School/College level (Researcher of the Year and Teaching Excellence). He has served as Keynote Speakers for IEEE APCCAS, VCVP (twice), JCPC, IEEE ICAST, IEEE ICIEA, IET FC & U-Media, IEEE U-Media, and Workshop at XUPT (twice), as well as a Distinguished Speaker for IEEE ICIEA. He is/was General Chairs/Co-Chairs for IEEE Hot Chips, VCVP (twice), IEEE ICME, IEEE U-Media (thrice), and IEEE SiPS. He is an Honorary Co-Chair for IEEE Umedia. He has also served as Technical Program Co-Chairs for IEEE ISCAS, APSIPA ASC, IEEE APCCAS, IEEE SiPS (twice), DCV, and IEEE VCIP. He was Technical Committee Chairs for IEEE CASCOM TC and IEEE TCMM, and has served as Guest Editors/Associate Editors for IEEE TCAS-I, IEEE J-STSP, Springer JSPS, Springer MSSP, and other journals. He has delivered more than 120 invited colloquia worldwide and has served as Visiting Professors/Consultants/Scientists for many institutions/companies.

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Challenges and Opportunities of Circuits and Systems on Internet of Things

Dr. Yen-Kuang Chen

Intel Corporation, U.S.A.

IEEE Fellow

Editor-in-Chief of IEEE Journal on Emerging and Selected Topics in Circuits and Systems

Organized by IEEE Circuits and Systems Singapore Chapter & Centre for Infocomm Technology (INFINITUS), School of EEE, NTU

"Sponsored by the IEEE Circuits and Systems Society under its Distinguished Lecturer Program"

Abstract

This seminar aims to discuss the technical trends and challenges of circuits and systems on Internet of Things. Rapid advancement of networking technologies together with extreme miniaturization of computing and communication devices enable a host of new and exciting applications and services that connect the physical and the computational worlds. In the future, digital sensing, communication, and processing capabilities will be ubiquitously embedded into everyday objects, turning them into the Internet of Things (IoT). In this new paradigm, smart devices will collect data, relay the information or context to each another, and process the information collaboratively using cloud computing and similar technologies. This paradigm shift creates numerous challenges and opportunities for engineering. For example, in the future, enormous numbers of sensors will be deployed. The costs of servicing such sensors will be a major concern. It is often almost impossible to replace sensor batteries once they are in the field. Therefore, one major challenge is low power sensor design, or designs which do not require a battery change over the lifetime of the sensor. For example, if a sensor is deployed on an animal for tracking purposes, the battery of the sensor should outlive the animal. This creates a demand for energy-efficient designs. This seminar will discuss the challenges and opportunities of circuits and systems on Internet of Things.

Speaker Biography

Dr. Yen-Kuang Chen is a Principal Engineer at Intel Corporation. His research areas span from emerging applications that can utilize the true potential of internet of things to computer architecture that can embrace emerging applications. He has 50+ US patents, 20+ pending patent applications, and 85+ technical publications. He is one of the key contributors to Supplemental Streaming SIMD Extension 3 and Advanced Vector Extension in Intel microprocessors. He has served as a program committee member of 50+ international conferences on Internet of Things, multimedia, video communication, image processing, VLSI circuits and systems, parallel processing, and software optimization. He is a steering committee member of IEEE Internet of Things Journal, the past-chair of Internet of Things special interest group of IEEE Signal Processing Society, and the Editor-in-Chief of IEEE Journal on Emerging and Selected Topics in Circuits and Systems. He received his Ph.D. degree from Princeton University and is an IEEE Fellow.

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Design Automation of Cyberphysical Systems: System-Level Approaches for Energy-Aware Electric Vehicle Design and Management

Prof. Naehyuck Chang

ACM Fellow & IEEE Fellow

Full Professor, Korea Advanced Institude of Science and Technology, Korea

Organized by IEEE Circuits and Systems Singapore Chapter & Centre for Infocomm Technology (INFINITUS), School of EEE, NTU

Abstract

Why do we drive electric vehicles? It is not easy to say that electric vehicles are higher performance compared with similar price range of internal combustion engine vehicles. There are financial benefits including Government subsidies and tax deduction, which cannot be sustainable. A low maintenance cost is a good advantage, but vehicle depreciation is a big question. Therefore, environmental friendliness should be one clear motivation to drive electric vehicles.

However, electric vehicles are only “zero exhaust emission” because of tire and brake emissions, which occupy a large portion of the total vehicle emissions. Even putting aside the tire and brake emissions, electric vehicles still contribute to significant amount of pollution because of the source of electricity. Electric vehicles produce less than a half of equivalent exhaust emissions compared with gasoline vehicles and not much different from that of hybrid vehicles. Higher MPGe (mile per gallon gasoline equivalent) of electric vehicles can largely mislead the energy efficiency when it comes to “well to wheel” efficiency taking the entire energy ecosystem into account.

It is challenging to make electric vehicles more fuel-efficient because the key powertrain components are already highly efficient, and therefore, there is a very narrow headroom for further enhancement. Consequently, the challenges for extended range of electric vehicles end up with deployment of more lighter materials, which directly impacts on the manufacturing and repair costs, and it may make actual cost of ownership very high. Extended driving range of electric vehicles is one of the most demanding requirements of the current and potential electric vehicle owners, but use of a larger-capacity battery pack makes the vehicle curb weight heavier and thus the fuel efficiency worse.

In this talk, we introduce system-level solutions to enhance electric vehicle fuel efficiency with the current powertrain technologies. First, we develop an instantaneous power consumption modeling of electric vehicles by the curb weights, speed, acceleration, road slope, passenger and cargo weights, motor capacity, and so on, as a battery discharge model. We ensure the model fidelity as we fabricate a lightweight custom electric vehicle perform extensive measurement. The model fidelity enables us to achieve a more accurate range estimation.

We attempt both design and runtime energy optimization using the electric-vehicle-specific energy characteristics. We emphasize that electric vehicles show completely different fuel consumption behaviors from internal combustion engine vehicles due to the significant discrepancy in the drivetrain. We introduce minimum-energy driving methods for electric vehicles, which are largely different from eco-driving methods of internal combustion engine vehicles. We also propose a rapid energy-aware electric vehicle synthesis that allows users to quickly customize their own electric vehicle powertrain specification without understanding the technology.

Finally, we also give a heads up of an application-specific (extreme off-road driving) electric vehicle design challenges. We proved electric vehicles are capable, efficient and promising on extreme off-roads through real trail run tests.

Speaker Biography

Naehyuck Chang is a Full Professor at the Department of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST) from 2014. Before he joined KAIST, he was with the Department of Computer Science and Engineering, Seoul National University from 1997 to 2014. Dr. Chang also served as a Vice Dean of College of Engineering, Seoul National University from 2011 to 2013. His current research interests include low-power embedded systems and Design Automation of Things such as systematic design and optimization of Cyberphysical Systems.

Dr. Chang is an ACM Fellow and an IEEE Fellow for contribution to low-power systems. He was the Chair of the ACM SIGDA (Special Interest Group on Design Automation) and now the Past Chair of ACM SIGDA. Dr. Chang is the Editor-in-Chief of the ACM (Association for Computing Machinery) Transactions on Design Automation of Electronics Systems, and an Associate Editor of IEEE Transactions on Very Large Scale Integration Systems. He also served for IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, IEEE Embedded Systems Letters, ACM Transactions on Embedded Computing Systems, and so on, as an Associate Editor.

Dr. Chang is (was) the General Co-Chair of VLSI-SoC (Very Large Scale Integration) 2015, ICCD (International Conference on Computer Design) 2014 and 2015, ISLPED (International Symposium on Low-Power Electronics and Design) 2011, etc. Dr. Chang is the Technical Program Chair of DAC (Design Automation Conference) 2016. He was the Technical Program (Co-)Chair of ASP-DAC (Asia and South Pacific Design Automation Conference) 2015, ICCD 2014, CODES+ISSS (Hardware Software Codesign and System Synthesis) 2012, ISLPED 2009, etc.

Dr. Chang is the winner of the 2014 ISLPED Best Paper Award, 2011 SAE Vincent Bendix Automotive Electronics Engineering Award, 2011 Sinyang Academic Award, 2009 IEEE SSCS International SoC Design Conference Seoul Chapter Award, and several ISLPED Low-Power Design Contest Awards in 2002, 2003, 2004, 2007, 2012, 2014, and 2017.

Dr. Chang and his colleague introduced the world’s first extreme off-road electric Jeep Wrangler and recently finished the Rubicon Trail run for the first time in the history by an electric Jeep Wrangler with just a single recharging at the Rubicon Springs Basecamp.

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