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  • Assessment of Egocentric Spatial Orientation using Virtual Reality for Diagnosis and Monitoring Alzheimer’s Disease

    TRI-UC, Basement Lecture theatre 550 University Ave., Toronto, M5G 2A2

    Friday May 24th, 2019 at 12:15 p.m. Prof. Zahra Moussavi, Director of the Biomedical Engineering Program at University of Manitoba and Canada Research Chair, will be presenting “Assessment of Egocentric Spatial Orientation using Virtual Reality for Diagnosis and Monitoring Alzheimer’s Disease”. Day & Time: Friday May 24th, 2019 12:15 p.m. ‐ 1:15 p.m. Speaker: Zahra Moussavi Director of the Biomedical Engineering Program Professor & Canada Research Chair Department of Electrical & Computer Engineering University of Manitoba Organizers: IEEE Toronto WIE, IEEE Toronto, IEEE Toronto Engineering in Medicine and Biology Chapter, UHN Location: TRI-UC, Basement Lecture Theatre 550 University Ave., Toronto, M5G 2A2 GoToMeeting: https://global.gotomeeting.com/join/543203653 Contact: Dr. Maryam Davoudpour Abstract: Memory and cognitive declines are associated with normal brain aging but are also precursors to dementia, in particular the so called the pandemic of the century, Alzheimer’s disease. While currently there is no cure or “vaccine” against dementia, based on brain’s plasticity, there are hopes to delay the onset or to slow the progression of disease. Alzheimer’s disease is multi-facet condition; thus, the key to its management is in multi- disciplinary approaches. The clinical diagnosis of neurodegenerative disorders, in general, is based on an extensive evaluation of cognition and behavioral performance along with functional status, which provides a variable grade of accuracy especially at early stages of the disease. In this talk, I will review diagnostic objective methods that can assist Alzheimer’s diagnosis. In particular, I will elaborate on the application and research outcomes of virtual reality egocentric spatial assessment for and its potentials for a differential diagnosis of Alzheimer’s versus other types of dementia. Biography: Zahra Moussavi is a professor, a Canada Research Chair, and the founder and director of Biomedical Engineering Graduate Program at University of Manitoba. Her current research focuses are on medical devices instrumentation and signal analysis for sleep apnea management and Alzheimer’s diagnosis and treatment using virtual reality, rTMS and EVestG technologies. She is the recipient of several awards including the “Canada’s Most Powerful Women (Top 100)” and “Manitoba Distinguished Women” in 2014 and IEEE EMBS Distinguished Lecturer, 2014 and 2019. She has published more than 259 peer-reviewed papers in journals and conferences, and has given 94 invited talks/seminars including 2 Tedx Talks and 9 keynote speaker seminars at national and international conferences. Aside from academic work, on her spare time, she writes science articles for public; also has developed and offered memory fitness programs for aging population. Poster Link: Click here

  • MIMO Signalling: Knowing the Classics Can Make a Difference

    Room BA-2135, University of Toronto

    Thursday June 6th, 2019 at 10:00 a.m. Prof. Wing-Kin (Ken) Ma, Chinese University of Hong Kong, will be presenting an IEEE Signal Processing Society Distinguished Lecture “MIMO Signalling: Knowing the Classics Can Make a Difference”. Day & Time: Thursday June 6th, 2019 10:00 a.m. ‐ 11:00 a.m. Speaker: Prof. Wing-Kin (Ken) Ma Chinese University of Hong Kong Organizers: IEEE Signal Processing Chapter Toronto Section IEEE Communications Chapter Toronto Section Location: Room BA-2135, University of Toronto http://map.utoronto.ca/building/080 Contact: Mehrnaz Shokrollahi, Yashodhan Athavale, Michael Zara, Abstract: In this talk the speaker will share two stories of how his research was benefitted by learning from the basics. The first story concerns physical-layer multicasting, a topic that has been dominated bybeamforming and optimization techniques. We will see how the classical concept of using channel coding to fight fast fading effects gives spark to rethink multicasting, and how that leads to a stochastic beamforming approach that goes beyond what beamforming achieves. The second story considers one-bit massive MIMO precoding, an emerging and challengingtopic. Current research on this topic mostly focuses on optimization, often in a sophisticated, if not complicated, manner. We will see how the traditional idea of Sigma-Delta modulation for DAC of temporal signals can be transferred to the spatial case, leading to one-bit massive MIMO precoding solutions that are simple and have quantization error well under control. Biography: Wing-Kin (Ken) Ma is a Professor with the Department of Electronic Engineering, The Chinese University of Hong Kong. His research interests lie in signal processing, optimization and communications. His mostrecent research focuses on two distinct topics, namely, structured matrix factorization for data science and remote sensing, and MIMO transceiver design and optimization. Dr. Ma is active in the Signal Processing Society. He served as editors of several journals, e.g.,Senior Area Editor of IEEE Transactions on Signal Processing, Lead Guest Editor of a special issue in IEEE Signal Processing Magazine, to name a few. He is currently a member of the Signal Processing for Communications and Networking (SPCOM) Technical Committee. He received Research Excellence Award 2013– 2014 by CUHK, the 2015 IEEE Signal Processing Magazine Best Paper Award, the 2016 IEEE Signal Processing Letters Best Paper Award, and the 2018 IEEE Signal Processing Best Paper Award. He is an IEEE Fellow and is currently an IEEE SPS Distinguished Lecturer.

  • Data Mining and Machine Learning with Application to Medical Data

    TRI-UC, Basement Lecture theatre 550 University Ave., Toronto, M5G 2A2

    Wednesday July 17th, 2019 at 12:15 p.m. Prof. Steven Wang, Professor in Statistics at York University, will be presenting “Data Mining and Machine Learning with Application to Medical Data”. Day & Time: Wednesday July 17th, 2019 12:15 p.m. ‐ 1:15 p.m. Speaker: Prof. Steven Wang Professor in Statistics Department of Mathematics and Statistics York University Organizers: IEEE Toronto Robotics, IEEE Toronto WIE, EMB, UHN Location: TRI-UC, Basement Lecture theatre 550 University Ave., Toronto, M5G 2A2 GoToMeeting: https://global.gotomeeting.com/join/435099981 Contact: Prof. Azadeh Yadollahi Abstract: In this talk, we will discuss some applications of data mining and machine learning to medical data. We will discuss a variety of topics: genetic analysis, signal processing method for ECG and EEG, personalized medicine, autoimmune disease and human microbiome analysis. We will also share our experience on data including issues related to data cleaning and missing values. Biography: Dr. Steven Wang is a professor in Statistics at the Department of Mathematics and Statistics. He received his Ph.D. in Statistics from the University of British Columbia in 2001 and did one year Postdoc on Data Mining at the Pacific Institute of Mathematical Sciences. He joined York University in 2002 and currently a full professor in Statistics. His research included statistical theory, data mining, optimization and machine learning. With his co-inventors, he has applied a Canadian and US patent for deep learning method. In the past 10 years, his research is focused on machine learning and medical data. Poster: See Poster

  • IEEE Toronto Centennial Workshop: Distributed Machine Learning, Basic Concepts

    Room B3-09 Centennial College, Progress Campus 941 Progress Ave., Toronto, Ontario, M1G 3T8

    Tuesday July 23rd, 2019 at 2:30 p.m. Reza Dibaj, Chair of Magnetics Chapter in the IEEE Toronto Section, will be presenting “IEEE Toronto Centennial Workshop: Distributed Machine Learning, Basic Concepts”. Day & Time: Tuesday July 23rd, 2019 2:30 p.m. ‐ 3:30 p.m. Speaker: Reza Dibaj Chair of Magnetics Chapter, IEEE Toronto Section Organizers: Magnetics Chapter, IEEE Toronto Centennial College Chapter, WIE IEEE Toronto Location: Room B3-09 Centennial College, Progress Campus 941 Progress Ave., Toronto, Ontario, M1G 3T8 Contact: Reza Dibaj Abstract: Machine Learning is an indispensable part of data science and there is no need to have a thorough programming background to benefit from it. Machine Learning (ML) and statistical techniques have provided a new era that enables us to convert the data to information, and transform the information into actionable knowledge. SciKit and TensorFlow are two states of the art libraries that can be used in Python and this seminar will open the gate to know their bases. The first seminar is about “Hello World!” Machine Learning program, using python language and SciKit learn library.

  • IEEE Toronto Centennial Workshop: Distributed Machine Learning, The Second Step

    Room B3-09 Centennial College, Progress Campus 941 Progress Ave., Toronto, Ontario, M1G 3T8

    Tuesday July 30th, 2019 at 2:30 p.m. Reza Dibaj, Chair of Magnetics Chapter in the IEEE Toronto Section, will be presenting “IEEE Toronto Centennial Workshop: Distributed Machine Learning, The Second Step”. Day & Time: Tuesday July 30th, 2019 2:30 p.m. ‐ 3:30 p.m. Speaker: Reza Dibaj Chair of Magnetics Chapter, IEEE Toronto Section Organizers: Magnetics Chapter, IEEE Toronto Centennial College Chapter, WIE IEEE Toronto Location: Room B3-09 Centennial College, Progress Campus 941 Progress Ave., Toronto, Ontario, M1G 3T8 Contact: Reza Dibaj Abstract: At the beginning of the workshop, we quickly recap what we did in the previous session and knowing more about the definition of good features in our datasets. To continue our journey that we have started in the previous workshop, we will dive deeper into ML by applying our Decision Tree algorithm on a classical iris dataset. We will thoroughly practice training and testing data, using a step-by-step hands-on. Finally, we will use visualization tools to show what is happening under the hood in a decision tree and how it works as one of the most interpretable algorithms in ML.

  • Opportunities, Challenges and Implementations of Silicon Integration and Packaging in mmWave Radar and Communication Applications

    Room BA 1200, Bahen Centre for Information Technology 40 St George St Toronto, Ontario M5S 2E4

    Friday August 9th, 2019 at 10:00 a.m. Dr. Xiaoxiong Gu, Distinguished Lecturer of the IEEE EMC Society, will be presenting “Opportunities, Challenges and Implementations of Silicon Integration and Packaging in mmWave Radar and Communication Applications”. Day & Time: Friday August 9th, 2019 10:00 a.m. ‐ 11:00 a.m. Speaker: Dr. Xiaoxiong Gu (IBM) Distinguished Lecturer of the IEEE EMC Society Organizers: IEEE Toronto Electromagnetics & Radiation Chapter, IEEE EMC Society Location: Room BA 1200 Bahen Centre for Information Technology 40 St George St, Toronto, ON M5S 2E4 Contact: Prof. Piero Triverio Abstract: Co-design and integration of RFIC, package, and antennas are critical to enable multiple aspects of 5G communications (backhaul, last mile, mobile access) and are particularly challenging at mmWave frequencies. This talk will cover various important aspects of mmWave antenna module packaging and integration for base station, backhaul, and user equipment applications, respectively. We will first present a historical perspective on Si-based mmWave modules and approaches for antenna and IC integration including trade-offs. We will focus on the challenges, implementation, and characterization of a 28-GHz phased-array module with 64 dual polarized antennas for 5G base station applications. We will then introduce a software-defined phased array radio based on the 28-GHz hardware. The highly re-configurable phased array radio features beam shaping/steering control as well as data TX/RX function control from a single Python-based software interface. Second, we will present a W-band phased-array module with 64-element dual-polarization antennas for radar imaging and backhaul application. The module consists of a multilayer organic chip-carrier package and a 16-element phased-array TX IC or a 32-element RX IC chipset. Third, we will describe a compact, low-power, 60-GHz switched-beam transceiver module suitable for handset integration incorporating 4 antennas that supports both normal and end-fire directions for a wide link spatial coverage. Biography: Xiaoxiong Gu received the Ph.D. in electrical engineering from the University of Washington, Seattle, USA, in 2006. He joined IBM Research as a Research Staff Member in January 2007. His research activities are focused on 5G radio access technologies, optoelectronic and mm-wave packaging, electrical designs, modeling and characterization of communication, imaging radar and computation systems. He has recently worked on antenna-in-package design and integration for mm-wave imaging and communication systems including Ka-band, V-band and W-band phased-array modules. He has also worked on 3D electrical packaging and signal/power integrity analysis for high-speed I/O subsystems including on-chip and off-chip interconnects. He has been involved in developing novel TSV and interposer technologies for heterogeneous system integration. Dr. Gu has co-authored over 80 peer-reviewed publications and holds 9 issued patents. He was a co-recipient of IEEE ISSCC 2017 Lewis Winner Award for Outstanding Paper and IEEE JSSC 2017 Best Paper Award (the world’s first reported silicon-based 5G mmWave phased array antenna module operating at 28GHz). He was a co-recipient of the 2017 Pat Goldberg Memorial Award to the best paper in computer science, electrical engineering, and mathematics published by IBM Research. He received an IBM Outstanding Technical Achievement Award in 2016, four IBM Plateau Invention Awards in 2012 ~ 2016, the IEEE EMC Symposium Best Paper Award in 2013, two SRC Mahboob Khan Outstanding Industry Liaison Awards in 2012 and 2014, the Best Conference Paper Award at IEEE EPEPS in 2011, IEC DesignCon Paper Awards in 2008 and 2010, the Best Interactive Session Paper Award at IEEE DATE in 2008, and the Best Session Paper Award at IEEE ECTC in 2007. Dr. Gu is the co-chair of Professional Interest Community (PIC) on Computer System Designs at IBM. He is a Senior Member of IEEE and has been serving on different program committees for MTT-S, EPEPS, ECTC, EDAPS and DesignCon. Dr. Gu was the General Chair of IEEE EPEPS 2018 in San Jose, CA. He is also a Distinguished Lecturer for IEEE EMC Society in 2019-2020.

  • Setting in with Programming – Python – Workshop 1

    Lassonde Building, Ottawa Rd, Toronto, ON M3J 1P3, Canada

    Monday September 16th, 2019 at 1:30 p.m. Enas Tarawneh will be presenting a Python workshop, “Setting in with Programming”. Day & Time: Monday September 16th, 2019 1:30 p.m. – 3:30 p.m. Speaker: Enas Tarawneh Organizers: IEEE WIE, WICSE Location: Lassonde Building (LAS-3033) Contact: Hina Tabassum Registration Link: http://bit.ly/2y9bKaY Snacks will be served. Workshop Description: Beginner lesson (assumes no knowledge in programming). This workshop will cover (1) input/output, (2) variables (3) numbers (4) string (5) lists /arrays (6) if-else (7) loops Note: Bring your own laptop with a python installation (2.7, 3.3-3.6) and Speech Recognition Package installation. Installation guidelines will be sent to registered attendees. Biography: Enas Tarawneh is a PhD student at York University in the department of Computer Science and Electrical Engineering. She works in the Vision, Graphics and Robotics (VGR) Laboratory as a research assistant. Her most recent research involves the development and evaluation of a cloud-based avatar (intelligent agent) for human-robot interaction that is part of a project funded by VISTA. She holds an OGS and VISTA doctoral scholarship. Prior to this, Enas worked as an academic Lead, instructor and e-learning coordinator in the Institute of Applied Technology in UAE in which she received an award for “Distinguished Curriculum Support” and another for “Excellence in E-learning coordination”. Most importantly Enas, is a wife and mother of three, that believes that open-mindedness and positivism is the best accomplishment and the source of true happiness.

  • Professional Development Conference for Immigrants (PDCI)

    Humber College North Campus Residence 203 Humber College Boulevard Toronto, ON M9W 6V3

    After four successful years of holding sold-out seminars for immigrants, North Star Success Inc. has partnered up with Humber College to host an amazing one-day conference, PDCI: An opportunity for networking with and learning from successful immigrants. Day & Time: Sunday, October 6, 2019 9:00 a.m. ‐ 5:00 p.m. Speakers: Dr. Abuelaish (5-time Nobel Peace Prize nominee), Mohamad Fakih (Founder of Paramoun Fine Foods), Kundan Joshi (Entrepreneur of the Year), Sathish Bala (Founder of DesiFest) and Bobby Umar (5-time TEDx speaker), and more! Organizers: North Star Success Inc., Humber College, IEEE Toronto Location: Humber College North Campus Residence 203 Humber College Boulevard Toronto, ON M9W 6V3 Register: www.northstarsuccess.com/pdci Contact: Dr. Maryam Davoudpour Description: PDCI (Professional Development Conference for Immigrants) aims for three major initiatives: 1) NETWORKING and OPEN EXCHANGE of INFORMATION: Stop struggling for success in Canada! PDCI means open exchange of information and resources. Network with and get direct advice from the most successful immigrants, whether in corporate jobs or in business. 2) PRIZES for PREPARED MINDS: Looking for excitement? During the panel discussions, the moderator of the panel will pose a question to the audience and whoever gives the best answer (judged by the panelists) will win big cash prizes! 3) RECOGNITION of CHAMPIONS: Let’s acknowledge the Champions! A handful of successful immigrants who have chosen to support our cause will be recognized and given awards for their achievements and contribution.

  • Setting in with Programming – Python – Workshop 2

    Lassonde Building, Ottawa Rd, Toronto, ON M3J 1P3, Canada

    Monday October 7th, 2019 at 1:30 p.m. Enas Tarawneh will be presenting a Python workshop, “Setting in with Programming – Workshop 2”. Day & Time: Monday October 7th, 2019 1:30 p.m. – 3:30 p.m. Speaker: Enas Tarawneh Organizers: IEEE WIE, WICSE Location: Lassonde Building (LAS-3033) Contact: Hina Tabassum Pre-requisites: Workshop 1 Registration Link: http://bit.ly/2Y171HP Snacks will be served. Workshop Description: This workshop will cover the (1) use and application of existing packages (2) file manipulation (3) GUI input/output (4) speech recognition package (5) use microphone or file for input (6) output audio capture result through play or file (7) output text result through terminal and GUI. Note: Bring your own laptop with a python installation (2.7, 3.3-3.6) and Speech Recognition Package installation. Installation guidelines will be sent to registered attendees. Biography: Enas Tarawneh is a PhD student at York University in the department of Computer Science and Electrical Engineering. She works in the Vision, Graphics and Robotics (VGR) Laboratory as a research assistant. Her most recent research involves the development and evaluation of a cloud-based avatar (intelligent agent) for human-robot interaction that is part of a project funded by VISTA. She holds an OGS and VISTA doctoral scholarship. Prior to this, Enas worked as an academic Lead, instructor and e-learning coordinator in the Institute of Applied Technology in UAE in which she received an award for “Distinguished Curriculum Support” and another for “Excellence in E-learning coordination”. Most importantly Enas, is a wife and mother of three, that believes that open-mindedness and positivism is the best accomplishment and the source of true happiness.

  • Analog Photonic Systems: Features & Techniques to Optimize Performance

    Sidney Smith Hall – Room SS 2108

    Monday October 7th, 2019 at 4:30 p.m. Dr. Edward Ackerman, Vice President of R&D for Photonic Systems and IEEE Fellow, will be presenting “Analog Photonic Systems: Features & Techniques to Optimize Performance”. Day & Time: Monday October 7th, 2019 4:30 p.m. ‐ 5:30 p.m. Speaker: Dr. Edward Ackerman Vice President of R&D for Photonic Systems, Inc. of Billerica, Massachusetts IEEE Fellow Organizers: IEEE Toronto Electromagnetics & Radiation Chapter Location: Sidney Smith Hall – Room SS 2108 University of Toronto – St. George Campus 100 St George St, Toronto, ON M5S 3G3 Contact: George V. Eleftheriades, FRSC, FIEEE Abstract: Both the scientific and the defense communities wish to receive and process information occupying ever-wider portions of the electromagnetic spectrum. This can often create an analog-to-digital conversion “bottleneck”. Analog photonic channelization, linearization, and frequency conversion systems can be designed to alleviate this bottleneck. Moreover, the low loss and dispersion of optical fiber and integrated optical waveguides enable most of the components in a broadband sensing or communication system, including all of the analog-to-digital and digital processing hardware, to be situated many feet or even miles from the antennas or other sensors with almost no performance penalty. The anticipated presentation will highlight the advantages and other features of analog photonic systems (including some specific systems that the author has constructed and tested for the US Department of Defense), and will review and explain multiple techniques for optimizing their performance. Biography: Edward Ackerman received Ph.D. degree in electrical engineering from Drexel University in 1994. From 1989 through 1994 he was employed as a microwave photonics engineer at Martin Marietta’s Electronics Laboratory in Syracuse, New York. From 1995 to July 1999 he was a member of the Technical Staff at MIT Lincoln Laboratory. Since 1999 he has been Vice President of R&D for Photonic Systems, Inc. of Billerica, Massachusetts. Dr. Ackerman is a Fellow of the IEEE.

  • Wireless Positioning and Sensing Network (WPSN™) for Hyper-Accurate Indoor & Outdoor Location Tracking System with Applications in the Critical and Massive IoT

    Progress Campus 941 Progress Ave, Scarborough, ON M1G 3T8 Room L1-12

    Tuesday October 8th, 2019 at 3:00 p.m. Peyman Moeini, B. Eng., MASc, PMP, P.Eng., will be presenting “Wireless Positioning and Sensing Network (WPSN™) for Hyper-Accurate Indoor & Outdoor Location Tracking System with Applications in the Critical and Massive IoT”. Day & Time: Tuesday, October 8, 2019 3:00 p.m. ‐ 4:00 p.m. Speaker: Peyman Moeini, B. Eng., MASc, PMP, P.Eng. Founder and CEO of Peytec Organizers: IEEE Toronto Instrumentation & Measurement Chapter, Women in Engineering Location: Progress Campus 941 Progress Ave, Scarborough, ON M1G 3T8 Room L1-12 Contact: Dr. Maryam Davoudpour Abstract: Wireless Sensor Networks (WSN’s) are the building blocks of Internet-of-Things (IoT) and Industrial IoT in the physical layer; however, they lack a fundamental aspect; WSN’s are not designed to be located. There has been several research papers published that addresses the addition of localization capability in various Wireless Sensor Networks such as Zigbee, BLE’s, LoRa modules, and NB-IoT. In virtually all of the mentioned networks, by adding the localization capability other network and tags advantages such as latency, battery life, scalability, and reliability will be negatively affected; in addition, the localization accuracy obtained would vary significantly depending on the sample rate and method of localization. Most localization methodologies used to locate the position of a moving tag with the mentioned WSN’s utilize Received Signal Strength (RSSI) which is a range free methodology which often has poor localization accuracy and it is not repeatable nor reliable. To address this problem a groundbreaking Wireless Positioning and Sensing Network (WPSN™) is designed developed where not only a localization accuracy of 10 cm is maintained but also latency, reliability, scalability, and battery life of the tags are not sacrificed to maintain and sustain the 10 cm localization accuracy. Biography: Peyman Moeini, B. Eng., MASc, PMP, P.Eng., is an entrepreneur engineer who has launched several successful Internet of Things (IoT) & Artificial Intelligence (AI) products in various fields such as agriculture, manufacturing, logistics, freight, retail, and mining. He has won more than 30 innovation and entrepreneurship awards in the IoT&AI fields. Peyman has extensive knowledge and experience in the IoT&AI spaces. Through his career, Peyman has developed an AI algorithm that made the time efficiency of software 500 times faster for the exact same results! He holds several patents in this space and is the founder and CEO of Peytec, a Smart Industrial IoT&AI company that builds and sells hyper-accurate “Indoor GPS” and Sensing Systems. Through his initiatives, Peyman is on a mission to help make Canada be the global leader in IoT&AI space.

  • Automotive Radar – A Signal Processing Perspective on Current Technology and Future Systems

    Bahen Centre, Room BA 2175

    Thursday March 5th, 2020 at 4:00 p.m. Dr. Markus Gardill, IEEE Distinguished Microwave Lecturer, will be presenting an IEEE Distinguished Lecture “Automotive Radar – A Signal Processing Perspective on Current Technology and Future Systems”. Day & Time: Thursday March 5th, 2020 4:00 p.m. ‐ 5:00 p.m. Speaker: Dr. Markus Gardill IEEE Distinguished Microwave Lecturer Organizers: IEEE Toronto Electromagnetics & Radiation Chapter Location: Bahen Centre, Room BA 1180 University of Toronto – St. George Campus 40 St George St, Toronto, ON M5S 2E4 Contact: George V. Eleftheriades, FRSC, FIEEE Abstract: Radar systems are a key technology of modern vehicle safety & comfort systems. Without doubt it will only be the symbiosis of Radar, Lidar and camera-based sensor systems which can enable advanced autonomous driving functions soon. Several next generation car models are such announced to have up to 10 radar sensors per vehicle, allowing for the generation of a radar-based 360° surround view necessary for advanced driver assistance as well as semi-autonomous operation. Hence the demand from the automotive industry for high-precision, multi-functional radar systems is higher than ever before, and the increased requirements on functionality and sensor capabilities lead to research and development activities in the field of automotive radar systems in both industry and academic worlds. Current automotive radar technology is almost exclusively based on the principle of frequency-modulated continuous-wave (FMCW) radar, which has been well known for several decades. However, together with an increase of hardware capabilities such as higher carrier frequencies, modulation bandwidths and ramp slopes, as well as a scaling up of simultaneously utilized transmit and receive channels with independent modulation features, new degrees of freedom have been added to traditional FMCW radar system design and signal processing. The anticipated presentation will accordingly introduce the topic with a review on the fundamentals of radar and FMCW radar. After introducing the system architecture of traditional and modern automotive FMCW radar sensors, with e.g. insights into the concepts of distributed or centralized processing and sensor data fusion, the presentation will dive into the details of fast-chirp FMCW processing – the modulation mode which is used by the vast majority of current automotive FMCW radar systems. Starting with the fundamentals of target range and velocity estimation based on the radar data matrix, the spatial dimension available using modern single-input multiple-output (SIMO) and multiple-input multiple-output (MIMO) radar systems will be introduced and radar processing based on the radar data cube is discussed. Of interest is the topic of angular resolution – one of the key drawbacks which e.g. render Lidar systems superior to radar in some situations. Consequently, traditional and modern methods for direction of arrival estimation in FMCW radar systems are presented, starting from traditional monopulse-like algorithms to modern frameworks for superresolution DoA estimation. The presentation will then introduce the great challenge of FMCW radar system interference. While FMCW radar interference is a challenge which can be handled using adaptive signal processing in today’s systems, it will become a severe problem with the increasing number of radar-sensors equipped vehicles in dense traffic situations in the near future and a solution to the expected increase in interference is still an open question. It is this problem of interference, together with some added functionality, which motivated the proposal of alternative radar waveforms such as pseudo-random or orthogonal-frequency division multiplexing (OFDM) radar for automotive radar systems. Although not yet of great interest from an industrial perspective, the fundamentals and capabilities of both technologies will be introduced in the remainder of the anticipated presentation. Biography: Markus Gardill (S’11-M’15) was born in Bamberg, Germany in 1985. He received the Dipl.-Ing. and Dr.-Ing. degree in systems of information and multimedia technology/electrical engineering from the Friedrich-Alexander-University Erlangen-Nürnberg, Germany, in 2010 and 2015, respectively. In 2010, he joined the Institute for Electronics Engineering at the Friedrich-Alexander-University Erlangen-Nürnberg as a research assistant and teaching fellow. From 2014 to 2015 he was head of the team Radio Communication Technology. In late 2015 he joined the Robert Bosch GmbH as an R&D engineer for optical and imaging metrology systems and leading the cluster of non-destructive testing for the international production network. In 2016 he joined the automotive radar business segment of InnoSenT GmbH, where he is currently head of the group radar signal processing & tracking. His main research interest include radar and communication systems, antenna (array) design, and signal processing algorithms. His particular interest is spatio-temporal processing such as e.g. beamforming and direction-of-arrival estimation with a focus on combining the worlds of signal processing and microwave/electromagnetics. Dr. Gardill is an IEEE Young Professional. He is member of the IEEE Microwave Theory and Techniques Society (IEEE MTT-S) and currently serves as co-chair of the IEEE MTT-S Technical Committee Digital Signal Processing (MTT-9). He regularly acts as reviewer and TPRC member for several journals and conferences, will act as associate editor of the Transactions on Microwave Theory and Techniques beginning with 2020 and serves as Distinguished Microwave Lecturer (DML) for the DML term 2018-2020 with a presentation focussing automotive radar systems.