Speakers

Dr. Jaume Anguera

IEEE Fellow, Founder and CTO at Ignion;
Associate Professor (Profesor Titular),
Electronics and Telecommunication Engineering, Universitat Ramon LLull

https://users.salle.url.edu/~jaume.anguera/

Jaume Anguera is the founder of and CTO at Ignion. Prior to this he was the Partner and R&D Manager at Fractus, Barcelona, Spain. He is also serving as Associate Professor at Universitat Ramon LLull, Barcelona, Spain. He is an IEEE Antennas and Propagation Distinguished Lecturer. He holds more than 150 patents. His biography is listed in Who´sWho in the World, Who´sWho in Engineering.

Author of more than 250 scientific widely cited papers and international conferences with citations above 7500, h-index 50, and i10 index of 150. Author of 6 books. He has participated in more than 21 competitive research projects financed by the Spanish Ministry . He is the author of  6 books, directed more than 100 bachelor and master thesis and 3 Ph.Ds. He is inventor of Virtual Antenna™ technology, which enables full functional multi-band wireless connectivity to wireless devices through miniature and off-the-shelf antenna boosters. He has taught more than 20 antenna courses around the world (USA, China, Korea, India, UK, France, Poland, Czech Republic, Tunisia, Spain). With over 21 years of R&D experience, he has developed part of his professional experience with Fractus in South Korea in the design of miniature antennas for large Korean companies such as Samsung and LG. He has received several national and international awards. He is associate editor of the IEEE Open Journal on Antennas and Propagation, Electronics Letters, International Journal of Electronics and Communications, and reviewer in several IEEE and other scientific journals. He is vice-chair of the working group “Software and Modeling” at EurAAP.

“Antenna Booster Technology: From Fundamentals to Applications”

Abstract

Addressed to Antenna, Microwave, RF, Wireless, Electronics, Engineers to learn about Antenna Booster Technology and how to design wireless devices with antenna boosters. Antenna boosters are off-the-shelf electrically small components that can be integrated inside any wireless device for operation at any frequency band (0.4GHz-10.6GHz) through the proper design of a matching network. The antenna booster frequency bands of operation are easily adjusted—not by modifying its geometry but through the proper matching-network design. This is a simpler, faster, and more familiar method for RF/microwave and wireless engineers, who are acquainted with the design of matching networks at every single stage of a telecommunication system for example, filters, and amplifiers. Attendants will learn the physical insights of antenna boosters and how to design wireless devices (ex. IoT) embedding antenna boosters covering from single band to multi-band applications either using passive and active matching network-based architectures. The presentation will give a general overview of the fundamentals of antenna booster till recent applications of antenna booster embedded in IoT devices.

Dr. Kiran Gunnam

Distinguished Engineer – Machine Learning & Computer Vision, Western Digital, USA.

https://www.linkedin.com/in/kirangunnam

Dr. Gunnam is an innovative technology leader with vision and passion who effectively connects with individuals and groups. Dr. Gunnam’s breakthrough contributions are in the areas of advanced error correction systems, storage-class memory systems, and computer vision-based localization & navigation systems. He has helped drive organizations to become industry leaders through ground-breaking technologies. Dr. Gunnam has 86 issued patents and 100+ patent applications/invention disclosures on algorithms, architectures, and real-time low-cost implementations for computing, storage, and computer vision systems. He is the lead inventor/sole inventor for 90% of them.

Dr. Gunnam’s patented work has been already incorporated in more than 3 billion data storage, WiFi and 5G chips as of 2020 and is set to continue to be incorporated in more than 500 million chips per year. Dr. Gunnam is also a key contributor to the precise localization and navigation technology commercialized for autonomous aerial refueling and space docking applications. His recent patent-pending inventions on low-complexity simultaneous localization and mapping (SLAM) and 3D convolutional neural network (CNN) for object detection, tracking, and classification are commercialized for LiDAR + camera-based perception for autonomous driving and robotic systems. His more recent inventions on machine learning accelerators have ~2x savings vs the state of the art.

Dr. Gunnam received his MSEE and PhD in Computer Engineering from Texas A&M University, College Station. He is world-renowned for balance between strong analytical ability and pragmatic insight into implementation of advanced technology. He served as IEEE Distinguished Speaker and Plenary Speaker for 25+ events and international conferences and more than 3000 attendees in the USA, Canada and Asia benefited from his talks.

Dr. Kiran Gunnam is a member of the Board of Governors of the IEEE Circuits and Systems Society (CASS). He is also the Chair of IEEE CASS Standard Activities Subdivision (SASD). Dr. Gunnam has been involved with the IEEE standards association (SA) since 2013.

Dr Kiran Gunnam is a recipient of the ValleyML Distinguished Technical Achievement Award for long-lasting contributions to architectures and algorithms of real-time signal processing, communication, and machine learning systems that enabled ubiquitous computing.

“Overview of IEEE Standards and IEEE Circuits and Systems Society Standards Activities Subdivision”

Abstract
The IEEE Circuits and Systems Society (CASS) recently approved establishing the Standards Activities Sub Division (SASD) under its Technical Activities (TA) Division. IEEE CASS SASD will be starting efforts to provide core standards for the benefit of industry including integrated circuit design and test systems, arithmetic, microprocessors, domain-specific accelerators such as error correction coding, video, and AI. These standards help enable industry to move technology forward at a rapid pace to deliver amazing products to consumers. By working with the IEEE Standards Association (IEEE SA), IEEE CASS would be able to provide a globally open, inclusive, and transparent environment for market-relevant, voluntary consensus standardization, and other industry consensus activities in the Circuits and Systems area.

The mission of this new initiative by IEEE Circuits and Systems Society (CASS) Standards Activities Board (SASD) is to encourage all the relevant stakeholders to participate in standardization activities, to promote the use of IEEE standards, and to develop useful products that leverage IEEE standards within the scope of the CASS. This new initiative also promotes and fosters academic and industry participation by engaging a broader community by drawing members from various IEEE CASS Technical Committees (TC). Also, professionals or ad-hoc industry groups who are actively working on standardization activities related to CASS are invited to bring their activities under the umbrella of IEEE CASS SASD to utilize the broader impact of IEEE Standards.

Dr. Satyasai Jagannath Nanda

Senior Member IEEE, Assistant Professor, Dept. of Electronics and Communication Engineering,
Malaviya National Institute of Technology Jaipur

Dr. S. J. Nanda is an assistant professor in the Department of Electronics and Communication Engineering, Malaviya National Institute of Technology Jaipur. Prior to joining MNIT Jaipur he has received the PhD degree from School of Electrical Sciences, IIT Bhubaneswar and M. Tech. degree from Dept. of Electronics and Communication Engg., NIT Rourkela. He was the recipient of Canadian Research Fellowship- GSEP, from Dept. of Foreign Affairs and Intern. Trade (DFAIT), Govt. of Canada for the year 2009-10. He was awarded Best PhD thesis award at SocPros 2015 by IIT Roorkee. He received the best research paper awards at SocPros-2020 at IIT Indore, IC3-2018 at SMIT Sikkim, SocPros-2017 at IIT Bhubaneswar, IEEE UPCON-2016 at IIT BHU and Springer OWT-2017 at MNIT. He is the recipient of prestigious IEI Young Engineers Award by Institution of Engineers, Govt. of India in the field of Electronics and Telecommunication Engineering for the year 2018-19.

Dr. Nanda is a Senior Member of IEEE and IEEE Computational Intelligence Society. He has received travel and research grants from SERB, UGC, CCSTDS (INSA), INAE. Till date he has published 40 SCI/SCOUPUS Journal articles and 40 international conference proceedings which received almost twelve hundred citations. He is the in-charge of Digital Signal and Image Processing (DSIP) Lab. at MNIT Jaipur. Under his supervision at MNIT Jaipur six researchers have awarded PhD and four researchers are continuing their research work. Along with it he has supervised 20 M. Tech thesis. Dr. Nanda is co-coordinator of Electronics and ICT Academy at MNIT Jaipur which is a set up of Ministry of Electronics and IT, Govt. of India of Grant 10 Crore.

“Nature Inspired Meta-heuristics for Effective Clustering”

Abstract

Unsupervised machine learning techniques have become very popular among the data mining researchers  in the last two decades due to their wide potential for online segregation and handing big data analytics. The objective here is to design effective clustering techniques (otherwords unsupervised machine learning techniques) using Nature Inspired Meta-heuristic algorithms. These algorithms are derived from the natural behavior of ants, birds, fishes, elephants, spiders, gray wolfs, whales . They provide effective solutions where derivative based optimization algorithms fail. The discussion will be carried out on various principles involve in development of these nature inspired meta-heuristics and their logical modeling.  Key issues involve in formulation of various meta-heuristics as a clustering problem and their application on benchmark datasets will also be discussed. Application of these algorithms in solving a real life multi-spectral image segmentation problem will also be highlighted.