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

    Bahen Centre, Room BA 1180 University of Toronto - St. George Campus 40 St George St, Toronto, ON M5S 2E4

    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.

  • Women in Engineering Winter 2020 Session #6

    In this session we are going to learn how to derive Flora-wearable electronic platform which we are going to use in dress. Day & Time: Tuesday, March 10, 2020 2:20 p.m. – 3:20 p.m. Organizers: IEEE Toronto WIE, Humber Student Branch Location: Humber College North Campus, Room F307 Contact: IEEE Humber

  • Webinar: Rotating Machine Stator Winding Insulation Failure Processes

    On Thursday, May 14, 2020 at 1:00 p.m., Dr. Greg Stone will be presenting  “Rotating Machine Stator Winding Insulation Failure Processes”. Day & Time: Thursday, May 14, 2020 1:00 p.m. ‐ 2:30 p.m. Speaker: Dr. Greg Stone of Qualitrol Organizers: IEEE DEI Ontario Chapter Location: Virtual – Webinar Contact: Ali Naderian, DEIS Toronto Chapter Abstract: The electrical insulation used in motors and generators rated 3.3 kV and above is made from mica tapes bonded together with epoxy. The stator winding insulation is the one of the most common reasons for machine failure, and the most common reason for motor and generator maintenance. The insulation normally fails due to gradual aging of the insulation by thermal, mechanical, and electrical stresses in combination with contamination. This lecture will discuss the main insulation aging and failure mechanism both of conventional 60 Hz machines, as well as motors and wind turbine generators connected to voltage source PWM inverters. Register: RSVP is required for this event. Please visit https://events.vtools.ieee.org/m/229820 for more details and to register. Biography: Dr. Stone took his degrees from the University of Waterloo, Canada in 1975 (BSEE) and in 1991 (PhD). He began his career as an engineer working at Ontario Hydro’s Research Division. In time, he was responsible for the testing of the 1200 large motors and generators in Ontario Hydro’s system. Later Dr. Stone became one of the developers of on-line partial discharge test methods to evaluate the condition of the high voltage insulation in stator windings, used on most large generators and many large motors in North America, and now widely used around the world. Since 1990, he has been employed at Iris Power LP in Toronto Canada, a company he helped to form as a co-founder. Dr. Stone has published over 150 technical papers and has been awarded three patents concerned with rotating machine maintenance and testing. He has published two books, the latest, Electrical Insulation for Rotating Machines – Design Evaluation, Aging, Testing and Repair. An IEEE Fellow, Dr. Stone has chaired several IEEE committees responsible for creating standards for evaluation and testing of rotating machines. He is past President of the IEEE Dielectrics and Electrical Insulation Society, and continues to be active on many other IEEE committees. Other awards include the IEEE Forster Distinguished Service Award and the IEEE Third Millennium Medal. Dr. Stone is also a Fellow of the Engineering Institute of Canada. He is a registered professional engineer in Ontario.

  • Programming Session Online

    Programming Sessions start for the Summer of 2020 via ZOOM. Day & Time: Friday, May 15, 2020 5:00 p.m. – 8:30 p.m. Speaker: Brandeen McDonald Organizers: IEEE Toronto WIE, Humber Student Branch Location: Virtual – Zoom Contact: Maryam Davoudpour

  • WIE Electronics session

    The workshop was to learn how to use virtual instruments in multisim, as a way of learning how to use lab equipment, followed by a discussion of an oscillator circuit, built and demonstrated in multisim. Day & Time: Friday, June 12, 2020 5:00 p.m. – 6:00 p.m. Speaker: Brandeen McDonald Professor, School of Applied Technology at Humber College Institution of Technology and Advance LearningOrganizers: IEEE Toronto WIE, Humber Student Branch  Location: Virtual – Zoom Contact: Ayda Naserialiabadi

  • Toronto ComSoc Summer Talks: A Career in Engineering, Past & Future Reflections

    On Thursday, June 18, 2020 at 6:00 p.m., Dr. Thamir (Tom) Murad will be presenting  “Toronto ComSoc Summer Talks: A Career in Engineering, Past & Future Reflections”. Day & Time: Thursday, June 18, 2020 6:00 p.m. ‐ 7:00 p.m. Speaker: Dr. Thamir (Tom) Murad, Ph.D., P.Eng. Organizers: IEEE Toronto ComSoc Chapter Location: Virtual – Zoom Contact: IEEE Toronto ComSoc Chapter Abstract: The IEEE Toronto ComSoc Chapter is thrilled to kick-off its Summer Talks Series hosting Dr. Tom Murad, the Vice Chair, Ontario Society of Professional Engineers “OSPE“ ‘s Board of Directors. Dr. Murad currently is the Country Lead for Engineering and Technology for Siemens Mobility. In this talk, we look forward to Dr. Murad as he shares his reflections on his career in engineering with insights into the future on how to remain relvant and combine passion with leadership. Register: Please visit https://events.vtools.ieee.org/m/232207 for more details and to register. Biography: Dr. Thamir (Tom) Murad, Ph.D., P.Eng. Vice Chair, Ontario Society of Professional Engineers “OSPE“ ‘s Board of Directors Tom has been a licensed engineer since 1998 and has extensive years of experience in the profession. He currently is the Country Lead for Engineering and Technology for Siemens Mobility, previously the founder and Head of Siemens Canada Engineering & Technology Academy (SCETA), as well as the Country Lead for Engineering, Technology and Academics for Siemens. Tom has been a great advocate for the Engineering profession by sharing his experience and expertise with many committees and organizations’ Boards. He is a member of the Ontario Government’s Post Secondary Education Quality Assessment board “ PEAQB “, the Ryerson University Faculty of Engineering Advisory Council, Humber College Applied Technologies Dean’s Board, PEO’s Experience Review Committee, Past chair of the IEEE -Toronto Section’s Executive Committee, and the Past Chair of Halton Champions of Innovation Round Table. Dr. Murad also has been a member of the Board of Directors for IEEE Canada, the German Canadian Centre for Innovation & Research, the Green Centre Canada, and Fielding Environmental. His contributions to the profession have been recognized by PEO, which gave him the Order of Honour, and he was also named a Fellow of Engineers Canada. Most Recently, He has been awarded the IEEE Canada J.M. Ham Outstanding Engineering Educator Award in 2019, OPEA (Joint PEO and OSPE) Best Engineering Achievement Award in 2017, and the Ontario Chamber of Commerce Golden Award for Best Skill Enhancement Project in 2016 . Tom has a Bachelor of Science in Electrical and Electronic Engineering, as well as a Ph.D. of Engineering, specializing in Power Electronics & Industrial Controls from Loughborough University of Technology in the U.K. Tom’s Passion has been always in Engineering Skills development , and he is Nationally recognised and awarded as a visionary and an Advocate for Innovative approach to work Integrated Learning and Education programs.

  • Introduction to NLP for Classification Task – Session 1

    Recorded Material: Video: https://drive.google.com/file/d/1gBUK_NtU3kSNblsGaYouLHyfDHlxr1tt/view?usp=sharing PowerPoint: 1-Intro to Python, Data Science Libraries, and Pytorch On Wednesday, July 8, 2020 at 6:00 p.m., IEEE Toronto WIE and Computational Intelligence Society will be hosting “Introduction to Natural Language Processing (NLP) for Classification Task – Session 1”. Day & Time: Wednesday, July 8, 2020 6:00 p.m. ‐ 7:30 p.m. Organizers: IEEE Toronto WIE, Computational Intelligence Society Location: Virtual – Zoom Contact: Ayda Naserialiabadi, Younes Sadat Nejad Abstract: Introduction to Natural Language Processing (NLP) for Classification Task is a series of workshops hosted by IEEE Toronto Section, WIE, Computational Intelligence Society, Instrumentation Measurement/Robotics Automation Chapter and Ryerson Advanced AI lab. Our main goal is to get started on NLP classification tasks for competition and explore duplicate question detection and sentiment analysis tasks. In session 1, we will be covering the introduction to Python, Data Science Libraries and Pytorch. Register: Please visit https://events.vtools.ieee.org/m/233944 or https://events.vtools.ieee.org/m/233942 for more details and to register.

  • TORONTO COMSOC SUMMER TALKS: Integrated Access and Backhaul for 5G and Beyond

    The IEEE Toronto ComSoc Chapter is thrilled to continue its Summer Talks Series hosting Dr. Behrooz Makki, a Senior Researcher in Ericsson Research, Gothenburg, Sweden. In his talk, Dr. Makki will discuss integrated access and backhaul for 5G and beyond. Day & Time: Thursday, July 9, 2020 12:00 p.m. ‐ 1:00 p.m. Speaker: Dr. Behrooz Makki Organizers: IEEE Communications Society Toronto Chapter Location: Virtual – Zoom Contact: IEEE ComSoc Toronto Chapter Abstract: The number of devices requesting for wireless communications is growing exponentially. Network densification via the deployment of many base stations (BSs) of different types is one of the mechanisms that can be employed to satisfy the ever-increasing demand for bandwidth/capacity in wireless networks. However, deploying fiber to the small cells may be expensive and impractical when the number of small cells increases. For this reason, as well as because of the traffic jams and infrastructure displacements caused by fiber optic installation, millimeter wave (mmw)-based wireless backhaul is currently considered as an alternative, providing (almost) the same rate as fiber optic with significantly less price and no digging. With this background, integrated access and backhaul (IAB) networks, where the operator can utilize part of the radio resources for wireless backhauling, has recently received considerable attention. The purpose of IAB is to replace existing backhaul systems with flexible wireless backhaul using the existing 3GPP bands providing not only backhaul but also existing cellular services in the same node. This creates more flexibility and reduces the implementation cost. For 5G NR, IAB is currently considered as a work item in 3GPP, and it is known as one of the main novelties of 5G. In this talk, we review the main backhauling techniques, and present the main motivations/standardization agreements on IAB. Moreover, We present comparisons between the IAB networks and the cases where all or part of the small access points are fiber-connected. Finally, we study the robustness of IAB networks to environmental effects and verify the effect of the blockage, the tree foliage, the rain as well as the antenna height/gain on the coverage rate of IAB setups, as the key differences between the fiber-connected and IAB networks. As we show, IAB is an attractive setup enabling 5G and beyond. Biography: Behrooz Makki received his PhD degree in Communication Engineering from Chalmers University of Technology, Gothenburg, Sweden. In 2013-2017, he was a Postdoc researcher at Chalmers University. Currently, he works as a senior researcher in Ericsson Research, Gothenburg, Sweden. Behrooz is the recipient of the VR Research Link grant, Sweden, 2014, the Ericsson’s Research grant, Sweden, 2013, 2014 and 2015, the ICT SEED grant, Sweden, 2017, as well as the Wallenbergs research grant, Sweden, 2018. He is a Senior Member of IEEE since Aug. 2019. Also, Behrooz is the recipient of the IEEE best reviewer award, IEEE Transactions on Wireless Communications, 2018. Currently, he works as an Editor in IEEE Wireless Communications Letters, IEEE Communications Letters, the journal of Communications and Information Networks as well as the associate editor of Frontiers in Communications and Networks. He was a member of European Commission projects “mm-Wave based Mobile Radio Access Network for 5G Integrated Communications” and “ARTIST4G” as well as various national and international research collaborations. His current research interests include integrated access and backhaul, hybrid automatic repeat request, Green communications, millimeter wave communications, and backhauling. He has co-authored 57 journal papers, 45 conference papers and 40 patent applications. Register: Please visit https://events.vtools.ieee.org/m/233754 for more details and to register.

  • Introduction to NLP for Classification Task – Session 2

    Online via Zoom

    Recorded Material: Video: https://drive.google.com/file/d/1gBUK_NtU3kSNblsGaYouLHyfDHlxr1tt/view PowerPoint: 2.IntroductiontoNLP,Kagle On Wednesday, July 15, 2020 at 6:00 p.m., IEEE Toronto WIE and Computational Intelligence Society will be hosting “Introduction to Natural Language Processing (NLP) for Classification Task – Session 2”. Day & Time: Wednesday, July 15, 2020 6:00 p.m. ‐ 8:00 p.m. Organizers: IEEE Toronto WIE, Computational Intelligence Society Location: Virtual – Zoom Contact: Ayda Naserialiabadi, Younes Sadat Nejad Abstract: Introduction to Natural Language Processing (NLP) for Classification Task is a series of workshops hosted by IEEE Toronto Section, WIE, Computational Intelligence Society, Instrumentation Measurement/Robotics Automation Chapter and Ryerson Advanced AI lab. Our main goal is to get started on NLP classification tasks for competition and explore duplicate question detection and sentiment analysis tasks. In the second session, we will introduce the concept of deep learning, and then specifically focus on Natural Language Process. We will also introduce Kaggle Account as an environment for python coding. Register: Please visit https://events.vtools.ieee.org/m/235444 or https://events.vtools.ieee.org/m/235447 for more details and to register.

  • Advanced Topics on Scalable Deployment of Machine Learning and Drone-Based Search and Rescue

    Online via Zoom Toronto, Ontario Canada

    On Thursday, July 23, 2020 at 1:00 p.m., Dalia Hanna and Mujahid Sultan will be presenting “Advanced Topics on Scalable Deployment of Machine Learning and Drone-Based Search and Rescue”. Day & Time: Thursday, July 23, 2020 1:00 p.m. – 4:00 p.m. Speakers: Dalia Hanna, Mujahid Sultan Organizers: IEEE Toronto WIE, IEEE IM/RA, Ryerson CS Graduate Student Council, IEEE Ryerson Computational Intelligence Chapter, Ryerson CSCU Location: Virtual – Zoom Contact: Ayda Naserialiabadi Title: Factors affecting the Automation of the Search and Rescue Operations: An Algorithm on Finding Missing Lost Persons Living with Dementia Abstract: Unmanned Aerial Vehicles (UAV) are now used in many applications. The focus in this presentation is on their use in public safety, specifically in search and rescue (SAR) operations involving lost persons living with dementia (LPLWD). When it comes to saving lives, there are many human factors associated with UAV operations that impact the performance of expert human SAR teams that could be improved through forms of automation. These include familiarity with the search location, tasks associated with piloting and search/flight management during SAR operations.  A LPLWD may not be interested in assisting in their own rescue as they may not know they are lost. As such, it has been observed that they tend to keep walking until they are faced with an obstacle that bars their further progress. The approach presented in this research work focuses on developing a people finding algorithm to identify higher probability locations where an LPLWD might be found, through informed, behavior-based analysis of the search location; then, developing an algorithm to fly a UAV to the vicinity of these higher probability locations.  The algorithm was tested and validated through field testing. The results from both the data collection process and the field tests indicated that there are efficiencies in using the drone, which enhances the probability of finding the lost person alive.  An informed cleaning process involving both manual and ‘R’-automated approaches to scrub and augment the data–adding any missing values in the dataset, helped in understanding the behaviour of the lost person and in determining what significant variables enhanced their survivability. Linear regression was utilized to acquire the correlation among the numeric values in the database. The analysis indicated that there was no significant correlation among the independent variables; however, the data indicated that the wanderer tended to be found closer to where they left or were last seen. Logistic regression was used to investigate the survivability using three classification models. Finally, a framework is presented considering all the factors form the field tests and data analysis. Title: How to build and deploy machine learning models in the scalable cloud  Abstract: Machine learning model development is a skill taught at schools and is a good skill to have but where most of the student’s lake is how to serve these models to the clients. How to scale. Make sure that the server does not die if it gets a million hits in a second. How to build security around it. Agenda: Interested students who want to build along with me, can bring their laptop with MobaXterm installed and we can do the following together. login to a cloud environment (I will provide the cloud login credentials during the presentation) create a virtual environment for development build a semantic search engineby pulling libraries from the net pick a visualization and presentation method from D3JS develop an application using MVC pattern like the flask wrap the application in a docker container install scalable web engine like NGINX host it to the cloud (azure) provide secure access with a username and password to anyone on the internet This presentation will expose the tools required to build scalable machine learning applications in the cloud. Registration: Please visit https://forms.gle/7ZoimYgVjjpC9mag8 to register. Biographies: Dalia Hanna Topic: Factors affecting the Automation of the Search and Rescue Operations: An Algorithm on Finding Missing Lost Persons Living with Dementia Dalia Hanna is a PhD Candidate in the Department of Computer Science, Ryerson University. She is a member of Ryerson’s Network-Centric Applied Research Lab, a multidisciplinary Computational Public Safety-focused research lab. She has a B.Sc. in Electronics and Communication Engineering and M.Sc. in Instructional Design and Technology with a specialization in Online Learning. Dalia is also a certified project management professional (PMP ® ) and a certified facilitator. Her research interest in utilizing technology tools for public safety, search and rescue, and emergency management operations. . Dalia authored several research papers and presented in national and international conferences. Mujahid Sultan Topic: Factors affecting the Automation of the Search and Rescue Operations: An Algorithm on Finding Missing Lost Persons Living with Dementia Mujahid Sultan is a senior computer scientist and enterprise architect with vast experience in machine learning, pattern recognition, deep learning, NLP, text synthesis, transcription, time-series forecasting and cloud-native developments (Python, microservices, APIs, Docker, Kubernetes). His current research focus: a) working to develop a robust clustering method with mathematical proofs b) improving learning from imbalanced data on graph-based deep learning backends (TensorFlow, Torch and CNTK), and c) building Machine Learning based dynamic SDN controllers. He has authored in high impact journals in fields of Machine Learning, Artificial Intelligence, Data Visualization, Genetics and Drug Discovery for Cancer, Requirements Engineering and Enterprise Architecture. His publications can be found at https://orcid.org/0000-0001-6721-4044 Areas of Expertise include: Regression, Clustering, Classification, Deep Learning, Convolutional and Recurrent Neural Networks (LSTMs), Natural Language Processing (NLP), Self-Organizing Maps (SOM), Topic Modeling and Parallel Processing. Expert in info visualization using matlab, matplotlib, D3js and plotly. Skills: Full-stack development: (Angular+Flask+Docker); Python: (Scikit-Learn, Keras, TensorFlow, NLTK, Spacy, NumPy, Matplotlib, SpaCy to name a few); MATLAB: (toolboxes: statistics, microeconomics, parallel processing, bioinformatics to name a few). Platform experience: Docker Containers and Kubernetes on AWS, Azure/Azure Stack and Google Cloud Platform. PaaS/IaaS: (AWS: (Elastic Beanstalk, Lambda, Poly, Sage-Maker), Azure ML, and Heroku).

  • 2D Game Development in Unity with C# – Session 1

    Online via Zoom

    On Monday, July 27, 2020 at 6:30 p.m., IEEE Ryerson Computational Intelligence Chapter will be hosting “2D Game Development in Unity with C# – Session 1”. Day & Time: Monday, July 27, 2020 6:30 p.m. ‐ 8:30 p.m. Speaker: Steven Medeot Organizers: IEEE Ryerson Computational Intelligence Chapter, IEEE Toronto WIE Location: Virtual – Zoom Contact: Ayda Naserialiabadi Abstract: Our interactive workshop welcomes new and experienced programmers who are interested in 2D game development. This event hosted by IEEE Ryerson Computational Intelligence Chapter is sponsored by IEEE WIE and will provide the building blocks and best practices in developing a 2D level game including, creating a player, creating enemies, game loops, animations, and more! All who attend all five sessions will get a certificate from IEEE WIE and can submit their 2D game into a friendly competition with small prizes at the end of the workshop series. In our first session, we will review basic programming concepts, object-oriented programming, and introduce best practices working with C# in the Unity environment. Register: https://forms.gle/VvZW3oeZ81UCtgnX7 Biography: Steven Medeot is a 3rd-year Computer Science Student at Ryerson University. He has a background in Game Development, who completed the Game Programming curriculum at George Brown College with a few years of experience working in this industry and enjoys developing his own games on the side. He strongly believes that creating a game that people can find joy in is a wonderful experience and wants to share some of the basic knowledge he has learned throughout the years.

  • Introduction to NLP for Classification Task – Session 4

    Online via Zoom Toronto, Ontario Canada

    On Wednesday, July 29, 2020 at 6:00 p.m., IEEE Toronto WIE, Computational Intelligence Society, and IM/RA will be hosting “Introduction to Natural Language Processing (NLP) for Classification Task – Session 4”. Day & Time: Wednesday, July 29, 2020 6:00 p.m. ‐ 8:00 p.m. Organizers: IEEE Toronto WIE, Computational Intelligence Society, IM/RA Society Location: Virtual – Zoom Contact: Ayda Naserialiabadi, Younes Sadat Nejad Abstract: Introduction to Natural Language Processing (NLP) for Classification Task is a series of workshops hosted by IEEE Toronto Section, WIE, Computational Intelligence Society, Instrumentation Measurement/Robotics Automation Chapter and Ryerson Advanced AI lab. Our main goal is to get started on NLP classification tasks for competition and explore duplicate question detection and sentiment analysis tasks. In this session, we will be focusing on RNN and LSTM. Register: Please visit https://events.vtools.ieee.org/m/236479 or https://events.vtools.ieee.org/m/236480 for more details and to register.