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  • Integrated Terrestrial-Aerial-Satellite Networks: Key Enabler for the Super Smart Cities of the Future

    Virtual - Zoom

    There have been rapid and exciting developments in recent years in satellite networks, in particular, in LEO mega-constellations such as SpaceX's Starlink. Although less visible, exciting developments have also been taking place in a certain type of aerial networks known as the high-altitude platform station (HAPS) systems, such as the formation of HAPS Alliance which brings together the connectivity and aerospace industries. It is worth noting that the satellite and aerial networks discussions have been occurring exclusively in the context of remote and rural connectivity. A major concern in this context is the rather questionable business case; there is limited revenue in rural and remote regions. In this talk, a novel vision will be presented for an integrated terrestrial-aerial-satellite networks architecture as a key enabler for the super smart cities of 2030s and beyond Speaker: Dr. Halim Yanikomeroglu Biography: Dr. Halim Yanikomeroglu is a Professor at Carleton University, Canada. He received his Ph.D. from the University of Toronto in 1998. He contributed to 4G/5G technologies and standards; his research focus in recent years has been on 6G and non-terrestrial networks (NTN). His extensive collaboration with industry resulted in 37 granted patents. He supervised or hosted in his lab around 140 postgraduate researchers. He co-authored IEEE papers with faculty members in 80+ universities in 25 countries. He is a Fellow of IEEE, Engineering Institute of Canada, and Canadian Academy of Engineering, and an IEEE Distinguished Speaker for Communications Society (ComSoc) and Vehicular Technology Society (VTS). He is currently chairing the IEEE WCNC (Wireless Communications and Networking Conference) Steering Committee; he is also a member of PIMRC Steering Committee and ComSoc Emerging Technologies Committee. He served as the General Chair of two VTCs and Technical Program Chair/Co-Chair of three WCNCs. He chaired ComSoc Technical Committee on Personal Communications. He received several awards for his research, teaching, and service including IEEE ComSoc Fred W. Ellersick Prize (2021), IEEE VTS Stuart Meyer Memorial Award (2020), and IEEE ComSoc Wireless Communications Technical Committee Recognition Award (2018).

  • AI against COVID-19: Screening X-ray Images for COVID-19 Infections

    Virtual

    Join the virtual competition on AI for COVID diagnosis, thanks to Microsoft Canada, the exclusive technology and cloud platform sponsor! The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, has generated an unprecedented global health crisis, with more than 2.7 million deaths worldwide. Do you want to contribute to the fight against this pandemic? IEEE SIGHT (Special Interest Group on Humanitarian Technology) of Montreal Section, Vision and Image Processing Research Group of the University of Waterloo and DarwinAI Corp. invite data scientists, students and professionals working on Artificial Intelligence (AI) to participate in a virtual competition to help medical researchers diagnose COVID-19 with chest X-ray (CXR) images. The ultimate goal is to contribute to the development of highly accurate yet practical AI solutions for detecting COVID-19 cases and, hopefully, accelerating the treatment of those who need it the most. Moreover, this AI for Good initiative will also allow us to take action on at least one of the United Nations Sustainable Development Goals (SDGs), Good Health and Well-being. In the First Phase of the competition, the challenge consists of designing robust machine learning algorithms to predict if the subjects of study are either COVID-19 positive or COVID-19 negative. The dataset for this competition is the dataset curated by COVID-Net, a global open-source initiative launched by DarwinAI Corp., Canada, and Vision and Image Processing Research Group, University of Waterloo, Canada, for accelerating advancements in machine learning to aid healthcare workers around the world in the fight against the COVID-19 pandemic. More about the COVID-Net initiative and available open-source resources are available here. In the Second Phase, the 10 top teams of the first phase will have the opportunity to refine their solution and submit a proposal for a follow-up project to positively impact society or the academic community. This competition is organized in collaboration with the National Research Council Canada and is co-hosted by the IEEE Young Professionals Affinity Groups of Montreal, Ottawa, Toronto and Vancouver Sections, Vancouver Circuit and Systems (CAS) Technical Chapter, the Student Branches of INRS (Institut National de la Recherche Scientifique), University of Toronto and Vancouver Simon Fraser University, WIE (Women In Engineering) Ottawa. It is largely sponsored by Microsoft, and partially by the IEEE Canada Humanitarian Initiatives Committee and the IEEE Montreal Section. How to participate Note: This competition only accepts participants living in Canada, due to restrictions on funds transfer. NO PURCHASE NECESSARY TO ENTER OR WIN. The competition is hosted on the Eval.ai online platform. To participate, you or your team will need to perform the following steps: Register individually at the link provided below in the current webpage (vTools). Register yourself or your team at the link on Eval.ai: https://eval.ai/web/challenges/challenge-page/925/participate. Follow the instructions here: https://evalai.readthedocs.io/en/latest/participate.html#. Download the dataset from https://www.kaggle.com/andyczhao/covidx-cxr2. Design an AI algorithm that gets CXR images as inputs and predicts the labels of the images in the output (COVID or non-COVID). Train your AI algorithm using the training dataset. Submit your AI algorithm through Eval.ai for evaluation against the test dataset for the competition. Prizes For the First Phase, the first five best solutions will be awarded monetary prizes and Azure credits: First place: 1,000 CAD + 500 CAD in Azure. Second place: 800 CAD + 300 CAD in Azure. Third place: 600 CAD + 300 CAD in Azure. Fourth place: 400 CAD + 300 CAD in Azure. Fifth place: 300 CAD + 300 CAD in Azure. The top 10 teams on the leaderboard will also have the following opportunities: Participate in the 2nd phase to refine their solution and receive funding for a project. Write a scientific paper with the Vision and Image Processing Research Group, from the University of Waterloo, to explain their approach. For the Second Phase, the best three projects can receive funds up to the following amounts: Project 1: 5,000 CAD. Project 2: 5,000 CAD. Project 3: 4,000 CAD. Term of funding: Up to 4 months following the announcement of the selected teams. The deadline is December 31st, 2021. For more information, visit IEEE SIGHT Montreal website.  

  • Ubiquitous Machines Learning for Design and Implementation of Energy-Efficient Electrical Systems: A Wide Range of Uses and Applications

    Virtual

    IEEE Industry Relations Committee (on behalf of IEEE Canada) would like to invite you to attend the Webinar "Ubiquitous Machines Learning for Design and Implementation of Energy-Efficient Electrical Systems: A Wide Range of Uses and Applications" The objective of this webinar is to discuss how Artificial Intelligence (AI) can play a significant role in several applications in electrical engineering. The webinar intends to provide an update/overview of the recent trends and advances of AI research and to open a dialog on how to address the challenges faced in the design of energy-efficient electrical systems. Several pathways to innovate through electronic systems design will be discussed through a series of ongoing projects. Speakers: Prof. Yvon Savaria Yvon Savaria FIEEE (S' 77, M' 86, SM' 97, F’08) received the B.Ing. and M.Sc.A in electrical engineering from Polytechnique Montreal in 1980 and 1982 respectively. He also received the Ph.D. in electrical engineering in 1985 from McGill University. Since 1985, he has been with Polytechnique Montreal, where he is currently professor in the department of electrical engineering. He is also affiliated with Hangzhou Innovation Institute of Beihang University. He has carried work in several areas related to microelectronic circuits and microsystems such as testing, verification, validation, clocking methods, defect and fault tolerance, effects of radiation on electronics, high-speed interconnects and circuit design techniques, CAD methods, reconfigurable computing and applications of microelectronics to telecommunications, networking, aerospace, image processing, video processing, radar signal processing, and digital signal processing acceleration. He is currently involved in several projects that relate to aircraft embedded systems, asynchronous circuits design and test, virtual networks, software defined networks, machine learning, computational efficiency and application specific architecture design. He holds 16 patents, has published 180 journal papers and 470 conference papers, and he was the thesis advisor of 175 graduate students who completed their studies. Dr. Ahmed Ragab Ahmed Ragab is an AI research scientist working for CanmetENERGY, an energy innovation center of Natural Resources Canada (NRCan). He received a Ph.D. degree in Industrial Engineering from Polytechnique Montréal in 2014. His research interests include AI, Image Processing, Data Fusion, Causality Analysis, Operations Research, Discrete Event Systems, and Process Mining. He has a bunch of experience in developing advanced algorithms and tools in the manufacturing industry, aiming at reducing energy consumption, Greenhouse gas (GHG) emissions, and operational and maintenance costs while improving operations’ performance. His main thematic activities focus on the practical challenges of Big Data and AI in a number of applications including Abnormal Events Diagnosis & Prognosis, Predictive Maintenance, Supervisory Control, Real-Time Optimization and Systems Design.

  • [AP-S Seminar Series] Low Profile Antennas for Chip-to-Chip Data Communications: A Research Story, Prof. Kathleen Melde

    Virtual - Zoom

    Abstract: In this talk, we present our recent research involving the development of low profile antennas that are used to replace wired interconnects in multi-chip modules in electronic packaging. This presentation will discuss the evolution of chip-compatible pattern adaptable mm-wave antenna modules to be used in massively multicore computers. The result is an enabling technology that overcomes technology bottlenecks that are prevalent when wired lines are used in interconnect busses. While device technologies have scaled, the interconnection layers have not. The limits are in the pitch of the input and output (I/O) for chip-to-chip communications and losses due to physical transmission lines. This is a unique type of pattern adaptable antenna array in that the antenna patterns are in the same plane as the antenna elements. This is quite a departure from many other types of reconfigurable antennas where the patterns are broadside (90 degree angle) to the antennas. The approach is new in that it leverages mm-wave technology (60GHz) so that the antenna size is small. 60GHz allows the work to leverage the already-developed transceiver work done for WPAN technologies. 60GHz also has a natural attenuation at large transmission distances, which means sufficient isolation and elimination of interference outside of the MCMC system. The research impacts antenna technology, packaging technology (circuit stacking and advanced packaging), and wireless systems testing on an experimental testbed. The talk will focus on the story behind how the technology progresses and how the research unfolded along the way. Contact: UofT AP-S Student Chapter

  • Basic OrCad Workshop

    Virtual - Zoom

    IEEE Seneca is offering a basic OrCad Workshop. We will be reinforcing ETY155 concepts and learn about following topics: - Simple resistor circuits - Voltage divider - Current divider concepts - Parallel circuits vs series circuits To amplify the experience, please have OrCad installed or use virual commons by Seneca to follow through the instruction. Contact: IEEE Seneca Speakers: Gabriel Chen, Adi Malihi

  • Introduction to Python Programming

    Virtual

    This is an introduction to Python programming for students without any prior programming knowledge or experience. The proposed 5-day course covers the fundamental aspects of programming, which include data types, various operators, input/output, conditions, control flow, functions, and algorithms. The learning experience is enhanced by a number of examples and problem sets (data, strings, file processing and simple graphics) that will be solved interactively during the lecture with the participation of the students. The course format includes 3 hours of daily lectures. Course Objective: Attendees will gain a solid understanding of principles of programing using Python; they can progress to more advanced programming topics and explores algorithms that are integral parts of more sophisticated methodologies, e.g., Artificial Intelligence. Attendees will have the knowledge to write various Python programs, and to design algorithms manipulating files and different types of data including numbers, and text. Note: This course is designed to be offered online, and it requires the attendees to use their personal computers/laptops. Details to Join in will be forwarded to Registered Attendees Who should attend: Students, second career trainees, engineers, scientists, clinicians, and in general specialists in variety of non-STEM fields. What will you receive after completion: A certificate of completion will be given to the students who successfully complete the course and pass a short exam. Electronic copies of the course materials. Attendees will also be provided with career, and skills development advice. Speaker Dr. Alireza Sadeghian Dr. Alireza Sadeghian has been with the Department of Computer Science at Ryerson University since 1999, where he holds the position of the Professor. He is also an Affiliate Scientist at the Li Ka Shing Knowledge Institute, St. Michael's Hospital, and serves as the AI research Theme Lead in Healthcare and Analytics at the Institute for Biomedical Engineering, Science, and Technology. Dr. Sadeghian was the Chair of the Department of Computer Science from 2005 to 2015. He is the founding Director of the Advanced Artificial Intelligence Initiative (AI2) Laboratory and has extensive expertise in the areas of AI, machine learning, and Deep Learning particularly related to industrial and medical applications. He has supervised 9 postdoctoral fellows, 8 PhD, and 24 Master’s students, as well as 60 research assistants. He has published over 150 journal manuscripts, refereed conference papers, and book chapters, as well as two edited books. He has 2 invention disclosures and 2 patents. Dr. Sadeghian has been actively involved with a number of international professional and academic boards including IEEE Education Activity Board. Presently, he is the Chair of IEEE Computational Intelligence Technical Society Chapter, Toronto Section. Dr. Sadeghian is also on the Editorial Board of Applied Soft Computing Journal and serves as an Associate Editor of IEEE Access, Information Sciences, and Expert Systems Journal. Email: dr.alireza.sadeghian@ieee.org Agenda Day 1 – June 7, 2021, 6:00-9:00 pm: Introduction to computer systems, hardware architecture, CPU, memory, compilation, high level vs. low-level programming language, data representation, Python and PyCharm interactive IDE installation, writing/editing/saving/retrieving and running a simple program, basic data types, variables, assignments, comments, and expressions. The material learned will be reinforced through examples provided during the lecture. Day 2 – June 8, 2021, 6:00-9:00 pm: The following topics will be discussed: conditions, operators (arithmetic, logic, and comparison), control statements (if and if-else), and loops (for and while). The material learned will be reinforced through examples provided during the lecture. Day 3 – June 9, 2021, 6:00-9:00 pm: Students will be introduced to Strings and text files in Python. They will learn how to work with files, reading/writing text and numbers from/to a file, string manipulation, indexing, and string slicing. The material learned will be reinforced through examples provided during the lecture. Day 4 – June 10, 2021, 6:00-9:00 pm: Functions, arguments, and return values will be discussed. The material learned will be reinforced through examples provided during the lecture. Day 5 – June 11, 2021, 6:00-9:00 pm: The topics of lists and dictionaries will be discussed. Students will learn about the basic operators, creating, accessing, slicing, adding, removing, replacing, and iteration methods for lists and dictionaries. The material learned will be reinforced through examples provided during the lecture.

  • Advanced OrCad Workshop

    Virtual - Zoom

    IEEE Seneca is offering an advanced OrCad Workshop. We will be reinforcing ETD555 concepts and learn about following topics: Transistor circuits (PNP, NPN, Darlington and MOSFETS) Components such as IRF840, IRF9510, TIP122, TIP127, 2N3904, and 2N3906 To amplify the experience, please have OrCad installed or using virual commons to follow through the instructions. Contact: IEEE Seneca Speakers: Gabriel Chen, Adi Malihi

  • Rate-Splitting Multiple Access for 6G

    Virtual

    Virtual platform will be delivered to registrants a couple of hours before starting the event.  Contact: IEEE Montreal Young Professionals Abstract: Rate Splitting Multiple Access (RSMA), based on (linearly or nonlinearly) precoded Rate-Splitting (RS) at the transmitter and Successive Interference Cancellation (SIC) at the receivers, has emerged as a novel, general and powerful framework for the design and optimization of non-orthogonal transmission, multiple access, and interference management strategies in future MIMO wireless networks. RSMA relies on the split of messages and the non-orthogonal transmission of common messages decoded by multiple users, and private messages decoded by their corresponding users. This enables RSMA to softly bridge and therefore reconcile the two extreme strategies of fully decode interference and treat interference as noise. RSMA has been shown to generalize, and subsume as special cases, four seemingly different strategies, namely Space Division Multiple Access (SDMA) based on linear precoding (currently used in 5G), Orthogonal Multiple Access (OMA), Non-Orthogonal Multiple Access (NOMA) based on linearly precoded superposition coding with SIC, and physical-layer multicasting. RSMA boils down to those strategies in some specific conditions, but outperforms them all in general. Through information and communication theoretic analysis, RSMA is shown to be optimal (from a Degrees-of-Freedom region perspective) in a number of scenarios and provides significant room for spectral efficiency, energy efficiency, fairness, reliability, QoS enhancements in a wide range of network loads and user deployments, robustness against imperfect Channel State Information at the Transmitter (CSIT), as well as feedback overhead and complexity reduction over conventional strategies used in 5G. The benefits of RSMA have been demonstrated in a wide range of scenarios (MU-MIMO, massive MIMO, multi-cell MIMO/CoMP, overloaded systems, NOMA, multigroup multicasting, mmwave communications, communications in the presence of RF impairments and superimposed unicast and multicast transmission, relay,…) and systems (terrestrial, cellular, satellite, …). Thanks to its versatility, RSMA has the potential to tackle challenges of modern communication systems and is a gold mine of research problems for academia and industry, spanning fundamental limits, optimization, PHY and MAC layers, and standardization. This lecture will share key principles of RSMA, recent developments, emerging applications and opportunities of RSMA for 6G networks and will cover many of the topics currently investigated as part of the new IEEE special interest group on RSMA https://sites.google.com/view/ieee-comsoc-wtc-sig-rsma/home. Speaker(s): Bruno Clerckx Biography: Bruno Clerckx is a (Full) Professor, the Head of the Wireless Communications and Signal Processing Lab, and the Deputy Head of the Communications and Signal Processing Group, within the Electrical and Electronic Engineering Department, Imperial College London, London, U.K. He received the M.S. and Ph.D. degrees in applied science from the Université Catholique de Louvain, Louvain-la-Neuve, Belgium, in 2000 and 2005, respectively. From 2006 to 2011, he was with Samsung Electronics, Suwon, South Korea, where he actively contributed to 4G (3GPP LTE/LTE-A and IEEE 802.16m) and acted as the Rapporteur for the 3GPP Coordinated Multi-Point (CoMP) Study Item. Since 2011, he has been with Imperial College London, first as a Lecturer from 2011 to 2015, Senior Lecturer from 2015 to 2017, Reader from 2017 to 2020, and now as a Full Professor. From 2014 to 2016, he also was an Associate Professor with Korea University, Seoul, South Korea. He also held various long or short-term visiting research appointments at Stanford University, EURECOM, National University of Singapore, The University of Hong Kong, Princeton University, The University of Edinburgh, The University of New South Wales, and Tsinghua University.

  • Protect the Privacy, Security, and Integrity of APIs

    Virtual - Zoom

    TeejLab’s mission: Protect the privacy, security, and integrity of APIs at a global scale by building Data Science and Artificial Intelligence driven API management solutions to help enterprises with API Governance.  Learn more about TeejLab: https://apidiscovery.teejlab.com. Contact: Mehrdad Tirandazian Abstract: Software development is becoming increasingly reliant on using third-party services accessed through APIs. These APIs connect various IT systems and processes with people to offer useful services that help us run our businesses and personal lives.  API integration may be simple, but APIs may directly or indirectly expose your IT assets and Databases to unofficial or illegitimate use. This talk aims to help students understand the overall implications of API, including information security, data management, legal risk management, and licensing costs. Speaker(s): Dr. Baljeet Baljeet of TeejLab Biography: Dr. Malhotra is an award-winning researcher known for his work in Open Source and API data management. He conceptualized the world's first "API Composition Analysis" based on source code static analysis. He founded TeejLab in 2017 and steered the team to build, API Discovery™, world's first comprehensive end-to-end API Management platform. He also established R&D unit of Black Duck Software in 2016 (acquired for US $565M by Synopsys). Previously, he was Research Director at SAP (2011-2016), Computational Scientist at the EOS Lab (2009) and Software Engineer at Satyam Computers (1999). He received a PhD in Computing Science from the University of Alberta. He was awarded NSERC (Canada) scholar in 2005, and Global Young Scientist (Singapore) in 2011. He concurrently holds Adjunct Professor positions at the University of British Columbia, University of Victoria and University of Northern BC.

  • IEEE VDL: Localization in Drone Assisted and Vehicular Networks

    Virtual - Zoom

    Join the IEEE Kingston Communications Society Chapter for the Virtual Distinguished Lecture: Localization in Drone Assisted and Vehicular Networks, presented by Shahrokh Valaee. Contact: IEEE Kingston ComSoc Abstract: The next generation of wireless systems will employ networking equipment mounted on mobile platforms, unmanned air vehicles (UAV), and low orbit satellites. As a result, the topology of 6G wireless technology will extend to 3D vertical networking. With its extended service, 6G will also give rise to new challenges which include, the introduction of intelligent reflective surfaces (IRS), the mmWave spectrum, the employment of massive MIMO systems, and the agility of networks. Along with the advancement in networking technology, user devices are also evolving rapidly, with the emergence of highly capable cellphones, smart IoT equipment, and wearable devices. One of the key elements of 6G technology is the need for accurate positioning information. The accuracy of today’s positioning systems is not acceptable for many applications of future, especially in smart environments. In this talk, we will discuss how positioning can be a key enabler of 6G, and what challenges the next generation of localization technology will face when integrated within the new wireless networks. Speaker(s): Shahrokh Valaee Biography: Shahrokh Valaee is a Professor with the Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, and the holder of Nortel Chair of Network Architectures and Services. He is the Founder and the Director of the Wireless and Internet Research Laboratory (WIRLab) at the University of Toronto. Professor Valaee was the TPC Co-Chair and the Local Organization Chair of the IEEE Personal Mobile Indoor Radio Communication (PIMRC) Symposium 2011. He was the TCP Chair of PIMRC2017, the Track Co-Chair of WCNC 2014, the TPC Co-Chair of ICT 2015. He has been the guest editor for various journals. He was a Track Co-chair for PIMRC 2020 and VTC Fall 2020. From December 2010 to December 2012, he was the Associate Editor of the IEEE Signal Processing Letters. From 2010 to 2015, he served as an Editor of IEEE Transactions on Wireless Communications. Currently, he is an Editor of Journal of Computer and System Science. Professor Valaee is a Fellow of the Engineering Institute of Canada, and a Fellow of IEEE.

  • AI against COVID-19 Competition: Closing Ceremony

    Virtual

    IEEE SIGHT (Special Interest Group on Humanitarian Technology) of Montreal Section, Vision and Image Processing Research Group of the University of Waterloo and DarwinAI Corp. invite you to the closing ceremony of the virtual competition on AI for COVID-19 diagnosis with chest X-ray images. In the First Phase, the challenge consisted of designing robust machine learning algorithms to predict if the subjects of study are either COVID-19 positive or COVID-19 negative. Join us to celebrate the amazing work done by all the teams and know who will be participating in the Second Phase. Then, you are also invited to a networking session with everybody! All the information will be sent to the registrants.

  • IEEE VDL: Intelligent Reflected Surfaces for Future Wireless Systems

    Virtual - Zoom

    Join the IEEE Kingston ComSoc and IEEE Toronto ComSoc for the Virtual Distinguished Lecture "Intelligent Reflected Surfaces for Future Wireless Systems", presented by Dr. Shahid Mumtaz. Contact: IEEE Kingston ComSoc Abstract: As we have finalized the research for 5G, now there is a race for technologies that will conquer 6G. The 6G  technologies will achieve much better latency and computation efficiency as compared to 5G. From 1G to 5G, almost all research and standardization randomly model the wireless channel between transmitter and receiver. There is no control of humans over a wireless medium, as it is given by nature. In 6G, we will break this assumption and go from random wireless channels to controllable wireless. Thanks to Intelligent Reflected Surfaces for Future Wireless System(IRS). This talk will explain in detail the physics of metasurface and the progress of IRS till today. This talk will also present different use case, study cases, signal processing and communication techniques for IRS, standardization, Prototype and testbed, and the open research challenges. Speaker(s): Dr. Shahid Mumtaz Biography: Shahid Mumtaz is an IET Fellow, IEEE ComSoc and ACM Distinguished speaker, recipient of IEEE ComSoC Young Researcher Award (2020), IEEE Senior member, founder and EiC of IET “Journal of Quantum communication”, Vice-Chair: Europe/Africa Region- IEEE ComSoc: Green Communications & Computing society and Vice-chair for IEEE standard on P1932.1: Standard for Licensed/Unlicensed Spectrum Interoperability in Wireless Mobile Networks. He has more than 15 years of wireless industry/academic experience. He has received his Master's and Ph.D. degrees in Electrical & Electronic Engineering from Blekinge Institute of Technology, Sweden, and University of Aveiro, Portugal in 2006 and 2011, respectively. From 2002 to 2003, he worked for Pak Telecom as System Engineer and from 2005 to 2006 for Ericsson and Huawei at Research Labs in Sweden. He has been with Instituto de Telecomunicações since 2011 where he currently holds the position of Auxiliary Researcher and adjunct positions with several universities across the Europe-Asian Region. He is the author of 4 technical books, 12 book chapters, 250+ technical papers (170+ Journal/transaction, 90+ conference, 2 IEEE best paper award- in the area of mobile communications. He had/has supervised/co-supervising several Ph.D. and Master Students. He uses mathematical and system-level tools to model and analyze emerging wireless communication architectures, leading to innovative theoretically optimal new communication techniques. He is working closely with leading R&D groups in the industry to transition these ideas to practice. He secures the funding of around 2M Euro.