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DTSTART;TZID=America/Toronto:20210521T150000
DTEND;TZID=America/Toronto:20210521T160000
DTSTAMP:20260523T131654
CREATED:20210504T165404Z
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SUMMARY:The Analog Designer's Toolbox (ADT): Towards A New Paradigm for Analog IC Design
DESCRIPTION:The Circuits & Devices Chapter of IEEE Toronto is pleased to invite you to join us for a virtual talk by Dr. Hesham Omran of Ain Shams University. \nThis event will be a virtual talk held on Zoom. The invitation will be sent to registerants. \nTopic: The Analog Designer’s Toolbox (ADT): Towards A New Paradigm for Analog IC Design \nAbstract: \nThe integrated circuit (IC) technology has witnessed an exponential advancement in the last decades and has changed every aspect in our life. On the other hand\, the analog IC design flow did not experience any major change since the introduction of Berkeley SPICE in the 1970s\, posing significant challenges to the design of complex systems and to the transfer of analog design expertise and knowledge. The Analog Designer’s Toolbox (ADT) is an analog EDA tool that addresses this problem by defining a new paradigm in analog IC design. ADT provides a turnkey solution that enables everyone to reap the benefits of the gm/ID design methodology powered by precomputed lookup tables (LUTs). At the device level\, ADT Device Xplore gives an easy interface to plot arbitrary design charts involving complex expressions. The designer can explore devices from different technologies at different corners and temperatures\, and extract simulator-accurate design points while taking second-order effects into consideration. At the block level\, ADT Design Xplore gives the designer the power of design space exploration\, constraints management\, live tuning\, and optimization\, all in a single cockpit without invoking the simulator. Moreover\, with a single click\, ADT can build the testbenches in the background and report the results from your favorite simulator. The aim of ADT is to boost productivity\, restore designer’s intuition\, and make the design process systematic\, optimized\, and fun! \nSpeaker: Hesham Omran \nBiography: \nDr. Hesham Omran received the B.Sc. (with honors) and M.Sc. degrees from Ain Shams University\, Cairo\, Egypt\, in 2007 and 2010\, respectively\, and the Ph.D. degree from King Abdullah University of Science and Technology (KAUST)\, Saudi Arabia\, in 2015\, all in Electrical Engineering. From 2008 to 2011\, he was a Design Engineer with Si-Ware Systems (SWS)\, Cairo\, Egypt\, where he worked on the circuit and system design of the first miniaturized FT-IR MEMS spectrometer (NeoSpectra)\, and a Research and Teaching Assistant with the Integrated Circuits Lab (ICL)\, Ain Shams University. From 2011 to 2016 he was a Researcher with the Sensors Lab\, KAUST. He held internships with Bosch Research and Technology Center\, CA\, USA\, and with Mentor Graphics\, Cairo\, Egypt. In 2016\, he rejoined the ICL\, Ain Shams University\, as an Assistant Professor. He developed and taught several advanced courses on different topics in the field of IC Design. Most of these courses are available on the Mastering Microelectronics YouTube channel with 4k+ subscribers. He co-founded Master Micro in 2020 to develop the Analog Designer’s Toolbox (ADT)\, a winner of the Egyptian ITIDA-TIEC startup incubation program. \nDr. Hesham has received several awards including the Egyptian State Encouragement Award for Engineering Sciences in 2019\, best paper award from the IEEE International Design and Test Conference in 2009\, and Academic Excellence Awards from KAUST and Ain Shams University in 2011 and 2002\, respectively. He has published 40+ papers in international journals and conferences. He serves as a reviewer for several international journals and conferences including IEEE Transactions on Circuits and Systems (TCAS) I & II\, IEEE Transactions on Instrumentation and Measurement\, and IEEE Transactions on Very Large Scale Integration Systems (TVLSI). His research interests are in the design of analog and mixed-signal integrated circuits\, and especially in analog and mixed-signal CAD tools and design automation. \nEmail: hesham.omran@master-micro.com
URL:https://www.ieeetoronto.ca/event/the-analog-designers-toolbox-adt-towards-a-new-paradigm-for-analog-ic-design/
LOCATION:Virtual – Zoom
CATEGORIES:Circuits & Devices
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210514T110000
DTEND;TZID=America/Toronto:20210514T120000
DTSTAMP:20260523T131654
CREATED:20210504T165404Z
LAST-MODIFIED:20210809T204633Z
UID:10000279-1620990000-1620993600@www.ieeetoronto.ca
SUMMARY:ComSoc Distinguished Lecture: AI to Enable Digital Medicine and Detect COVID-19
DESCRIPTION:The IEEE Ottawa Joint Chapter of Communications Society\, Consumer Electronics Society\, and Broadcast Technology Society (ComSoc/CESoc/BTS)\, IEEE Toronto Chapter (ComSoc/BTS)\, IEEE ComSoc Montreal Chapter (ComSoc)\, IEEE Ottawa Educational Activities (EA)\, IEEE Ottawa Women In Engineering (WIE)\, IEEE Ottawa Young Professionals (YP)\, and Algonquin College Student Branch (ACSB) in conjunction with School of Advanced Technology\, Algonquin College are inviting all interested IEEE members and other engineers\, technologists\, and students to ComSoc Distinguished Lecture (webinar) on AI to Enable Digital Medicine and Detect COVID-19. \nFor any additional information please contact: Wahab Almuhtadi or Eman Hammad \nAbstract: \nDigitalize human beings using biosensors to track our complex physiologic system\, process the large amount of data generated with artificial intelligence (AI) and change clinical practice towards individualized medicine: these are the goals of digital medicine. In this talk\, we discuss how to design AI solutions in the clinical space and what are the key aspects to make a difference. We focus on two critical clinical topics that need AI: 1) atrial fibrillation (AF)\, and 2) viral illnesses (COVID-19). AF is the most common sustained cardiac arrhythmia\, associated with stroke\, heart failure and coronary artery disease. AF detection from single-lead electrocardiography (ECG) recordings is still an open problem\, as AF events may be episodic and the signal noisy. We conduct a thoughtful analysis of recent convolutional neural network architectures developed in the computer vision field\, redesigned to be suitable for a one-dimensional signal\, and we evaluate their performance in the detection of AF using 200 thousand seconds of ECG\, highlighting the potential and pitfall of this technology. We also discuss how to explain (global and local post hoc explanations) this AI model for AF detection using features that are commonly used by a cardiologist. \nTo tackle the problem of COVID-19\, we start with an overview of continuous\, passively monitored vital signs from 200\,000 individuals wearing a Fitbit wearable device for 2 years. This large study provides the baseline for DETECT\, our app-based\, nationwide clinical study enrolling individuals who routinely use a smartwatch or other wireless devices to determine if individualized tracking of changes in heart rate\, activity and sleep can provide early diagnosis and self-monitoring for COVID-19. We analyze data from more than 36\,000 individuals\, showing how we can discriminate (on an individual level) between COVID-19 and other types of infections. We discuss how this can impact both the individual and public health\, and how the use of AI can be a game changer in this fight against the virus. \nSpeaker: Giorgio Quer \nGiorgio Quer is the Director of Artificial Intelligence at the Scripps Research Translational Institute\, where he is leading the Data Science and Analytics team within the All of Us Research Program’s Participant Center (NIH). \nHis research focuses on artificial intelligence and probabilistic modeling applied to heterogeneous data signals\, in order to extract key information and make predictions on future occurrences based on past data. He is involved in several digital medicine initiatives within the Scripps Research Digital Trials Center. For the DETECT study\, he is developing algorithms to predict COVID-19 and other viral infections from wearable sensor data. He is responsible for collaborations with several industry partners\, studying changes in heart rate and sleep data monitored by commercial wearable devices. He is also interested in the detection and modeling of atrial fibrillation from single-lead ECG signals. He is leading the collaboration with the Halicioglu Data Science Institute at UC San Diego towards the development of new AI models for health data. \nHe received his Ph.D. degree in Information Engineering from the University of Padova\, Italy\, and he continued his studies as a Postdoctoral researcher with the Qualcomm Institute at the University of California San Diego. He is a Senior Member of the IEEE and a Distinguished Lecturer for the IEEE Communications society.
URL:https://www.ieeetoronto.ca/event/comsoc-distinguished-lecture-ai-to-enable-digital-medicine-and-detect-covid-19/
LOCATION:Virtual – Zoom
CATEGORIES:Communications
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BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210513T160000
DTEND;TZID=America/Toronto:20210513T180000
DTSTAMP:20260523T131654
CREATED:20210506T165445Z
LAST-MODIFIED:20210809T204621Z
UID:10000411-1620921600-1620928800@www.ieeetoronto.ca
SUMMARY:Electromagnetics Alumni Event
DESCRIPTION:We are inviting several alumni members from the electromagnetics group\, University of Toronto\, Canada who are working in industry at senior positions and in academia as Professors to provide an insight on career choices after graduation. We are planning it as a semi-formal event where the speakers would share their experiences and the attendees could ask them questions. \nZoom link will be provided to the registered participants. \nContact: IEEE UofT AP-S Student Chapter \nPanelists: \n\nDr. Michael Selvanayagam\, IBM T.J. Watson Research Center\, NY\nDr. Rubaiyat Islam\, AMD\, Canada\nDr. Marco Antoniades\, Ryerson University\, Canada\nDr. Loic Markley\, University of British Columbia\, Canada\nDr. Utkarsh Patel\, AMD Canada
URL:https://www.ieeetoronto.ca/event/electromagnetics-alumni-event/
LOCATION:Virtual – Zoom
CATEGORIES:Electromagnetics & Radiation
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210416T120000
DTEND;TZID=America/Toronto:20210416T130000
DTSTAMP:20260523T131654
CREATED:20210430T023730Z
LAST-MODIFIED:20210809T204407Z
UID:10000372-1618574400-1618578000@www.ieeetoronto.ca
SUMMARY:CAS Distinguished Lecture - Augmented Perception: Next Generation Wearables and Human-Machine Interfaces
DESCRIPTION:The Circuits & Devices Chapter of IEEE Toronto is pleased to invite you to join us for a virtual talk by Distinguished Lecturer Dr. Andrew Mason of the Michigan State University. \nTopic: Augmented Perception: Next Generation Wearables and Human-Machine Interfaces \nAbstract: \nProducts like Fitbit and the Apple Watch have brought to the public decades of foundational work on wearable technologies achieved by researchers in the IEEE CAS Society and related groups. Similarly\, research into brain- and human-machine interface is starting to enter the public domain in applications including deep brain stimulation\, prosthetic limb control\, and human assistive devices. While researchers continue to explore new wearable sensing and human-interface paradigms\, it is vital that we also explore what applications the next generation of wearable human-machine interfaces can and should enable. This talk will review key challenges and approaches within wearable assistive device and brain/human interface technologies. Aspects of physiological\, environmental\, and behavioral sensing within wearable platforms will be discussed\, and technical challenges will be highlighted. Finally\, the next generation concept of augmented human perception\, real time machine-enhanced awareness that expands natural human senses\, will be introduced. Utilizing wearable sensing and real-time feedback through visual\, audio and tactile mechanism\, augmented perception is poised to revolutionize the human experience\, enhance daily performance\, and enable new pathways to address mental and physical health concerns. \nSpeaker: Andrew Mason of Michigan State University \nBiography: \nAndrew J. Mason received the BS in Physics with highest distinction from Western Kentucky University in 1991\, the BSEE with honors from the Georgia Institute of Technology in 1992\, and the MS and Ph.D. in Electrical Engineering from The University of Michigan\, Ann Arbor in 1994 and 2000\, respectively. From 1999 to 2001 he was an Assistant Professor at the University of Kentucky.  In 2001 he joined the Department of Electrical and Computer Engineering at Michigan State University in East Lansing\, Michigan\, where he is currently a Professor.  His research explores mixed-signal circuits\, microfabricated structures and machine learning algorithms for integrated microsystems in biomedical\, environmental monitoring and sustainable lifestyle applications.  Current projects are focused on design of augmented human awareness systems including signal processing algorithms and hardware for brain-machine interface\, wearable/implantable biochemical and neural sensors\, and lab-on-CMOS integration of sensing\, instrumentation\, and microfluidics. \nDr. Mason is a Senior Member of the Institute of Electrical and Electronic Engineers (IEEE) and serves on the Sensory Systems and Biomedical Circuits and Systems Technical Committees of the IEEE Circuits and Systems Society. He is an Associate Editor for the IEEE Trans. Biomedical Circuits and Systems and regularly serves on the technical and review committees for several IEEE conferences. Dr. Mason was co-General Chair of the 2011 IEEE Biomedical Circuits and Systems Conference. He is a recipient of the 2006 Michigan State University Teacher-Scholar Award and the 2010 Withrow Award for Teaching Excellence. \nEmail: mason@msu.edu
URL:https://www.ieeetoronto.ca/event/cas-distinguished-lecture-augmented-perception-next-generation-wearables-and-human-machine-interfaces/
LOCATION:Virtual – Zoom
CATEGORIES:Circuits & Devices
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20210319T160000
DTEND;TZID=America/Toronto:20210319T170000
DTSTAMP:20260523T131654
CREATED:20210430T023726Z
LAST-MODIFIED:20210809T204212Z
UID:10000366-1616169600-1616173200@www.ieeetoronto.ca
SUMMARY:[AP-S Seminar Series] Natalia K. Nikolova\, McMaster University\, Mar. 19\, 4pm EDT
DESCRIPTION:The University of Toronto Student Chapter of the IEEE Antennas and Propagation Society (AP-S) invites you to the following talk in our 2020-2021 seminar series: \nMicrowave and Millimeter-Wave Near-Field Imaging: Applications\, Methods\, and Challenges\, presented by Natalia K. Nikolova from McMaster University\, on Friday\, March 19\, 2021\, 4-5 pm EDT. \nAbstract: In the last decade\, we have witnessed dramatic decrease in the price and size of on-chip transceivers and radars along with their increased functionality. This has spurred unprecedented growth in imaging\, sensing and detection applications\, defining the current and future growth of wireless technology. \nWe will introduce the methods of real-time microwave and millimeter-wave imaging\, which allow to “see” inside optically opaque objects. The electromagnetic models of wave propagation that link the object’s electrical properties to the microwave measurements are briefly introduced with an emphasis on the approximations\, which enable real-time image reconstruction. We will discuss the detrimental effects of these approximations on the reconstructed images and how these effects are mitigated through the careful design of the acquisition apparatus and through data processing. We will briefly dive into the inner workings of two reconstruction methods\, microwave holography and the scattered-power mapping\, along with examples of real-time quantitative image reconstruction of complex dielectric objects. \nSpeaker: Natalia K. Nikolova of McMaster University \nBiography: \nNatalia K. Nikolova (IEEE S’93–M’97–SM’05–F’11) received the Dipl. Eng. (Radioelectronics) degree from the Technical University of Varna\, Bulgaria\, in 1989\, and the Ph.D. degree from the University of Electro-Communications\, Tokyo\, Japan\, in 1997. From 1998 to 1999\, she held a Postdoctoral Fellowship of the Natural Sciences and Engineering Research Council of Canada (NSERC) at Dalhousie University and McMaster University. In 1999\, she joined the Department of Electrical and Computer Engineering at McMaster University\, where she is currently a Professor. Her research interests include inverse scattering\, microwave imaging\, as well as computer-aided analysis and design of high-frequency structures and antennas. Prof. Nikolova has authored more than 270 refereed manuscripts\, 6 book chapters\, and two books\, including the monograph “Introduction to Microwave Imaging” (Cambridge University Press\, 2017). She has delivered 48 invited lectures around the world on the subjects of microwave imaging and detection as well as computer-aided electromagnetic analysis and design. \nProf. Nikolova is a Fellow of the IEEE\, the Canadian Academy of Engineering and the Engineering Institute of Canada. She served as an IEEE Distinguished Microwave Lecturer from 2010 to 2013.
URL:https://www.ieeetoronto.ca/event/ap-s-seminar-series-natalia-k-nikolova-mcmaster-university-mar-19-4pm-edt/
LOCATION:Virtual – Zoom
CATEGORIES:Electromagnetics & Radiation
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20210319
DTEND;VALUE=DATE:20210327
DTSTAMP:20260523T131654
CREATED:20210430T023726Z
LAST-MODIFIED:20210809T204148Z
UID:10000365-1616112000-1616803199@www.ieeetoronto.ca
SUMMARY:PIC Microcontroller Workshop
DESCRIPTION:IEEE Seneca is offering PIC Microcontroller Workshop\, please check out the details below for more information. This session will be recorded and uploaded at our IEEE Seneca Website. \nKnowledge for the digital systems\, basic electronics and C programming helps to understand the workshop. \nWhy is PIC Microcontroller important? \n\nThey are low in power consumption\, high performance ability and easy to support hardware and software tools like compilers\, debuggers and simulators.\nHigh integration allows the costand size of the system are reduced\, which makes them easily accessible.\nIt is easy to interface additional RAM\, ROM and I/O ports.\n\nIntro to PIC Mictocontroller Workshop\nDate: Friday March 19\, 2021 \nTime: 11:00 a.m. – 12:00 p.m. \nThis workshop will be an introduction to the PIC Microcontroller featuring: \n\nMicrocontroller Setup\nRC Oscillator\nMPLab X Programming\n\nESP8266 Node MCU Microcontroller Workshop\nDate: Friday\, March 26\, 2021 \nTime: 11:00 a.m. – 12:00 p.m. \nNote: For this workshop\, we will be using Arduino IDE during the session. If you would like to try out or download before the workshop\, please visit https://www.arduino.cc/en/software. \nThis workshop will feature in-depth information about Amica NodeMCU: \n\nProgramming and debugging\nlibrary ESP8266WiFi
URL:https://www.ieeetoronto.ca/event/pic-microcontroller-workshop/
LOCATION:Virtual – Zoom
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Toronto:20200921T180000
DTEND;TZID=America/Toronto:20200924T210000
DTSTAMP:20260523T131654
CREATED:20210430T023715Z
LAST-MODIFIED:20210430T235933Z
UID:10000334-1600711200-1600981200@www.ieeetoronto.ca
SUMMARY:The Digital Utility - From AI\, AR\, MR to Blockchain platforms to support P2P
DESCRIPTION:This event has been cancelled. \nCertificate for Course THE DIGITAL UTILITY\, Signed by the Instructor. 15 PDUs per course for 5 day course. Discounts available for students and for companies who register more than 5 people for the event. Email dustin.dunwell@ieee.org for details. \nCourse Timetable:\nStart time: 6:00 pm ET\nEnd time: 9:00 pm ET \nOn each of the following dates: \n\nMonday\, September 21\, 2020\nWednesday\, September 23\, 2020\nThursday\, September 24\, 2020\nMonday\, September 28\, 2020\nThursday\, October 1\, 2020\n\nSpeakers: Puica Nitu\, Afiny Akdemir \nLocation: Virtual – Zoom\nFull meeting details\, including passwords to join the meetings\, will be sent out to registrants before the event. \nOrganizer: IEEE Toronto \nContact: Satish Saini\, Dustin Dunwell \nRegister: https://meetings.vtools.ieee.org/m/238130 \nCourse Fees: \n\nNon-IEEE Members: $250 CAD\nActive Members: $220 CAD\nStudent Members: $50 CAD\nDiscounts available for students and for companies who register more than 5 people for the event.\n\nCourse Content: The Digital utility encompasses technological end-to-end digitization with emphasis on the consumer\, on the flexibility and integration of renewable technologies while offering an increased portfolio of market services. This is the first course of 4 e-learning courses. Each course runs 5 evenings\, for 3 hours each. \nThe first course presents the integration of new technologies in light of regulatory changes. The course explores the penetration of renewable energy resources facilitated by the operating flexibility brought by power electronics. Interoperability aspects and industry standards are discussed\, with focus on the consumer centric paradigm of Transactive Energy. \nThis course defines AI followed by VR\, AR and MR as they apply to power systems. Practical examples illustrate each methodology. Special attention is given to advanced AI applications with Machine Learning for load and solar energy forecasts. The White House call-to-action of a decade ago allows utilities today to utilize energy platforms and APIs to standardize reporting\, optimize consumption and leverage the much needed open exchange of solar data. \nThe course introduces the Blockchain as a new line of defense against cyber threats and its increasing application to Peer-to-Peer transactions to stimulate green energy trading and also trading Renewable Certificates or Credits. \nThe course provides industry examples from utilities and agencies from Canada\, US\, EU and Southeast Asia. \nCourse Outline: \n\nIntroduction: Historical Evolution of the inverter-based technologies\nPerformance Requirements: Power System Controls Regulatory Agreements NERC\, EU ENTSO\nThe Role of the ISO\nDemonstration of Essential Reliability Services – Control algorithms\nPower System Stability in an Inverter dominated Grid\nTRANSACTIVE ENERGY – THE PROSUMER\nP2P Energy Trading\nCollaboration between Market Entities and Government Agencies Cloud Services for Utilities – NAESB Green Button\, Orange Button\nARTIFICIAL INTELLIGENCE -AI and Artificial Neural Networks- ANN\nAI and ANN Applications in Power Systems: Machine Learning\nTraining the algorithm for Short Term Load Forecast and Solar Energy Forecasts\nIOT – Internet of Things; A brief look into Interoperability INTERNET OF THINGS WORLD FORUM REFERENCE MODEL\nAR- AUGMENTED REALITY\nVR- VIRTUAL REALITY\nMR- MIXED REALITY and AR-Augmented Reality\nIEDs- Intelligent Electronic Devices and SENSORS IEDs – Examples and Functionality\nBLOCKCHAIN Security Certification ; Vulnerability Blockchain Applications in the Power Industry- P2P Trading\nTrading Renewable Certificates\nEmission Credits\nClass Test 45 min and Discussions for Course Certification\n\nThe target audience for this course includes practitioners at all levels in the organization in companies in the power industry\, LDCs\, regulatory agencies and students in engineering and economics. The course would benefit law firms supporting renewable investments\, and CleanTech groups. \nBiographies: \nPuica Nitu\, M.Sc. P.Eng.\, SM IEEE\, CIGRE \n\n\n\nPuica Nitu is a Utility Executive with extensive global experience in power system operation and planning\, energy markets\, enterprise risk and regulatory oversight. She consults on energy markets integrating renewable resources from planning to operation. She led complex utility projects in operations (EMS\, energy derivatives\, reliability studies and policy) and conducted long term planning studies to support planning and operational reliability standards. \nSpecializing in Smart Grids\, Renewable generation\, Reliability\, Financial Engineering\, Energy Markets and Power System Integration\, she was recently engaged by the Inter-American Development Bank/MHI in Guyana. Most recently\, Puica was the Operations Expert for a regulatory assessment of the Oman Control Centre. \nWith over 25 years with Ontario Hydro and its successor company Ontario Power Generation (Revenue $1.2 Billion CAD\, I/S 16 GW)\, she served as Canadian representative in CIGRE\, NSERC (Natural Sciences and Engineering Research Council of Canada)\, Senior Member IEEE and Elsevier since 1990. \nPuica Nitu chaired international conferences\, lectured on 4 continents\, published a book on Reliability and Security of Nuclear Power Plants\, papers in IEEE\, PICA\, CIGRE and PMAPS and published in the Ontario Journal for Public Policy\, Canada. She delivered seminars to OPG\, seminars organized by the Power Engineering Society\, IEEE and seminars to power companies worldwide\, including Thailand\, Saudi Arabia\, Oman\, Malaysia\, Indonesia\, Portugal\, South Africa\, Japan\, Romania\, and Guyana.\nPuica Nitu is a registered member of the Professional Engineers of Ontario\, Canada. \nAfiny Akdemir \nAfiny Akdemir is the co-founder and Director of Research at Xesto Inc.  Xesto is a spatial computing AI startup based in Toronto\, Canada and it has been voted as “Toronto’s Best Tech Startup 2019” and was named one of the top 10 “Canadian AI Startups to Watch” as well as one of 6th International finalists for the VW Siemens Startup Challenge\, resulting in a partnership. \nAfiny Akdemir specializes in both applied and theoretical machine learning and has extensive experience in both industrial and academic research. He is specialized in Artificial Intelligence with multiple industrial applications. \nAt Xesto\, Afiny leads projects that focus on applying cutting edge research at the intersection of spatial analysis\, differential geometry\, optimization of deep neural networks\, and statistics to build scalable rigorous and real time performing systems that will change the way humans interact with technology. \nIn addition\, Afiny is a Ph.D candidate in the Mathematics department at UofT\, focusing on applied mathematics. His academic research interests are in applying advanced mathematical methods to the computational and statistical sciences. His ongoing projects examine the results of the regularity of the equation that governs optimal matching between two arbitrary sets in different dimensions. He is developing algorithmic applications of these results\, as well as studying these applications in the context of big data and statistical estimation where the parameter space is much larger than the number of observations. Afiny earned a Bachelor’s and MSc in Mathematics\, both at the University of Toronto. \nHaving presented at research seminars as well as instructing engineers on various levels\, Afiny has the ability to distill advanced theoretical concept to diverse audiences on all levels. \nIn addition to research\, Afiny is also an avid traveller and plays the violin.
URL:https://www.ieeetoronto.ca/event/the-digital-utility-from-ai-ar-mr-to-blockchain-platforms-to-support-p2p/
LOCATION:Virtual – Zoom
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