Tutorials, Workshops, And Demonstrations
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With the rapid proliferation of 4G and 5G networks, mobile operators have now started the trial deployment of network function virtualization (NFV), and software defined networking (SDN) especially with the introduction of various virtualized network elements in the access and core networks. 5G and 6G networks promise to support emerging applications such as enhanced mobile broadband, ultra-low latency, massive sensing type applications while providing the resilience in the network. While NFV and SDN open up the door for flexible networks and rapid service creation, these also offer both security opportunities while also introducing additional challenges and complexities, in some cases. This talk addresses evolution of cellular technologies towards 5G/6G and discusses various market verticals and new applications that can be supported using the new technologies. The talk also focuses on various security challenges and opportunities introduced by SDN/NFV and 5G networks and enablers such as Hypervisor, Virtual Network Functions (VNFs), SDN controller, orchestrator, network slicing, cloud RAN, edge cloud, and virtual security function. Additionally, this talk introduces a threat taxonomy for 5G security from an end-to-end system perspective, potential threats introduced by these enablers, and associated mitigation techniques. At the same time, some of the opportunities introduced by these pillars are also discussed. This talk also highlights some of the ongoing activities within various standards communities including open source consortiums, large scale NSF testbeds, and illustrates a few deployment use case scenarios.
The attendees will get to know the benefits of 5G technologies for various emerging applications, namely augmented reality, Meta verse, digital twins, current standards and deployment status, and various security threats and mitigation techniques associated with 5G. The attendees can learn about the 5G and 6G technologies and various enablers that can help alleviate some of the pain points of previous generation of networks. They will learn about various use cases (e.g., Entertainment, eHealth, First Responder, Tactical Networks, Agriculture) where 5G technologies can be applied.
Dr. Ashutosh currently works as Chief 5G Strategist and Fellow at Johns Hopkins University Applied Physics Labs and Chair of Electrical and Computer Engineering for Engineering Professional Program at JHU. Earlier I worked as Director of Technology Security at AT&T, CTO for NIKSUN, Senior Scientist in Telcordia Research, Director of Central Research Facility at Columbia University and Computer Engineer at TATA Motors. Ashutosh is author of more than 100 technical papers and 31 issued patents. Ashutosh is co-author of the book, titled, “Mobility Protocols and Handover Optimization: Design, Evaluation and Application” published by IEEE and John & Wiley. As a Technical Leader in 5G and security, Ashutosh has been serving as the founding Co-Chair for the IEEE Future Networks Initiative that focuses on 5G standardization, education, publications, testbed, and roadmap activities. Ashutosh is IEEE Communications Society’s Distinguished Lecturer for 2017-2020 and as an ACM Distinguished Speaker (2020-2022). Ashutosh currently serves as the founding co-chair for IEEE Future Networks Initiative and Member-At-Large for IEEE Communications Society. He co-founded the IEEE STEM conference (ISEC) and helped to implement EPICS (Engineering Projects in Community Service) projects in several high schools. Ashutosh has served as the general Co-Chair for the IEEE STEM conference for the last 10 years. Ashutosh served as the Director of Industry Outreach for IEEE Communications Society from 2014-2019. He was recipient of 2009 IEEE MGA Leadership award and 2010 IEEE-USA professional leadership award. Ashutosh currently serves as Member-At-Large for IEEE Communications Society for 2020-2022. Ashutosh has served as the general Co-Chair for the premier IEEE 5G World Forums and has organized 80 5G World Summits around the world. Ashutosh currently serves as the Chair for IEEE Industry Connection’s O-RAN activities. Ashutosh is recipient of IEEE-USA’s 2010 Professional Leadership Award, IEEE-USA, 2022 IEEE USA George F. McClure Citation of Honor and 2022 IEEE North American Region Exceptional Service Award. Ashutosh is a Distinguished Alumnus of NIT Rourkela with BS in Electrical Engineering, MS in Computer Science from NJIT, and Ph.D. in Electrical Engineering from Columbia University under the supervision of Prof. Henning Schulzrinne. Ashutosh is a Fellow of IEEE and Distinguished member ACM.
The development of string algorithms is an important research focus among the core study areas in the field of computer science, which leverages complicated data structures to solve problems optimally. Suffix tree, a concept put forward by Weiner is one of these fundamental data structures for processing any type of sequential data. Motivated by the fact that suffix trees can provide fast implementations of several essential string operations, this talk will provide an introduction to this important data structure and covers some of its application. However, the space consumption of this important data structure is a problem and the second part of the talk will focus on algorithms to resolve the issue. In many cases the problem is not the size of the data, but it is the size of the data structure that is required to be built on the data to efficiently perform the required queries. A promising direction is to develop indexes that use the compressibility feature of the text, so that the index size is a function of the compressed text length. This concept has eventually grown into self-indexes, that hold sufficient information to remake any part of the text. So, self-indexes replace the text itself.
Sahar Hooshmand is an Assistant Professor in the Department of Computer Science at the California State University Dominguez Hills, since Fall 2021. She also serves as the chair of the IEEE Women in Engineering (WIE) affinity group in Southern California. Sahar completed her Ph.D. in the Department of Computer Science at the University of Central Florida in December 2020. Her research focuses on String Algorithms, Text Compression, and Bioinformatics.
The brain communicates through electrical signals. The modern medical technologies have enabled acquisition of high-resolution data from brain while it performs multiple tasks in real world. The types of data collected include EEG, intracranial EEG, MEG and MRI data, which gives a window to peek into the functioning of the brain. On one side it will enable improvement in the understanding of brain functioning at multiple levels.
On the other hand, it will also help in designing better strategy for control of neurological disorders. In addition to these two benefits understanding of the brain function will further enable us in designing better algorithms in computer vision, data processing etc.
Analyzing the huge amount of data that comes from any of the above mentioned data acquisition methods and making reliable sense out of it, is a major engineering challenge. Modern signal processing techniques and deep learning tools have been extremely helpful in this direction but need to be further improvised and tailored to meet the demands of this field.
The proposed workshop will focus on intracranial EEG data processing using deep learning tools. As an introduction, the different types of data acquisition scenarios, technologies involved and limitations will be discussed. Availability of different open data sources, application of different types of data preprocessing strategies to maximize the feature extraction etc., will be reviewed. Focusing on deep learning methodologies, application into the classification of signals to pathological and physiological states will be reviewed.
Adaptation of deep learning technologies in medical field, will depend on the ability to explain the relevant signal features that the deep neural networks (DNN) are using to arrive at decisions. This would be important, at least initially in incorporating the outputs from deep learning tools in the clinical decision making. From this standpoint, it would be important to unravel the relevant features utilized by the neural networks in arriving at the specific conclusions, with the heatmapping strategies. The workshop will review the heatmapping tools and specifically discuss the grad-CAM approach in calculating heatmap. Additional heatmapping tools available for DNN will be evaluated.
The time series signal contains various features in frequency and time domains. The various signal processing strategies including Hilbert transform for establishing the correlation with the findings of deep learning will be discussed.
Another aspect that is important from a medical decision making standpoint is the reliability of predictions made through DNN. Strategies to evaluate the certainty of predictions made by DNN will be reviewed.
As conclusion the most challenging questions in the field, both from medical, neuroscience and information science standpoint will be discussed. The workshop will enable the young scientists in getting a firm footing in understanding the field and taking up challenging tasks.
Dr. Gireesh is a medical doctor trained in medical technologies from IIT Kharagpur, currently pursuing doctoral degree in Computer Engineering. He has worked in the field of Neural signal processing while doing post- doctoral fellowship at National Institutres of Health, Bethesda. Research interests include heatmapping strategies in deep neural networks, use of entropy in Neural signals for estimating reliability of predictions.
This tutorial serves as an engineering-oriented introduction to important Web3 technologies such as Decentralized Autonomous Organizations (DAOs), blockchains, cryptocurrencies, smart contracts, blockchain-based virtual machines for Decentralized Finance (DeFi) applications, and an introduction to the regulation and governance challenges resulting from these advances.
The main focus will be on public permissionless blockchains, crypto mechanics, smart contracts, and blockchain governance. Consensus algorithms, random number generators, public-key cryptology, and use of cryptographic hash functions will be presented – as well as a deeper analysis of the “proof-of-work” and “proof-of-stake” consensus techniques employed by most cryptocurrencies.
The Environmental, Social, and Governance (ESG) impact of mining/minting crypto will be addressed as well as the differences between solo vs. pooled mining/minting. Crypto creation/destruction policies (aka “the money supply”) of major cryptocurrencies will be addressed as well as self-custody vs. exchange-custody of crypto.
The primary objective of this talk is to provide a deeper level of understanding of these technologies than the media provides. Crypto journalists often espouse blockchain explanations that are overly simplistic and often factually inaccurate. Attendees of this tutorial will understand how Bitcoin works better than those journalists!
Michael A. Ramalho, Ph.D. is an IEEE Senior Member and a recipient of the 2021 IEEE Florida Council Outstanding Engineer Award. Dr. Ramalho has extensive experience as a director, lead/chief architect, and principal investigator in networking, media signal processing, unified communications, packet-based error correction, and acoustic spread-spectrum communication technologies.
Dr. Ramalho was especially active in Internet Telephony in the Web1 era during which time he ran an Internet Telephony research program at Telcordia Technologies, was co-chair of the Voice Over IP Forum, and was Chief Telephony Technologist at Voxware, Inc. during its IPO. While employed in the Collaboration CTO Office at Cisco Systems, he was the first to introduce lossless codec technology to Internet Telephony, resulting in ITU-T Standard G.711.0.
Dr. Ramalho has also worked for Bell Telephone Laboratories. He holds a Ph.D. from Rutgers University and a M.Eng.E.E. from Cornell University. He holds over 56 patents. He has authored many standards in the ITU-T, IETF, and IMTC, and many foundational input documents to ETSI, 3GPP, and ANSI Committee T1 standards.