Date: January 29, 2024 Time: 4:00 – 5:00 PM Location: CEI 1101, University of Windsor
Featuring: Dr. Mohammed A. S. Khalid, a distinguished professor from the University of Windsor. This is a golden opportunity for tech aficionados!
Topic: Immerse yourself in the dynamic realm of High-Level Synthesis (HLS) for FPGAs. Discover cutting-edge FPGA-based strategies for machine learning, deep learning, and automotive systems. A must-attend for anyone passionate about technology!
Introduction to MicroPython: Gain insights into MicroPython and its role in the future of engineering.
Practical Programming: Get hands-on experience with the Raspberry Pi Pico W.
Innovate with Technology: Learn to use SPI camera modules and integrate machine learning.
Competition: MicroPython Coding Competition with a chance to win a $50 Amazon Gift Card.
Registration: To secure your spot, please scan the QR code or visit the registration link.
We encourage students to come, learn, and be inspired to shape the future of engineering. Feel free to share this invitation with eligible students who may have a keen interest in technology and programming.
At this captivating event, we introduced participants to the fascinating world of IoT, its protocols, and cutting-edge technologies. Attendees were equipped with IoT kits and guided through the process of developing firmware for IoT integration, leveraging STM32 microcontrollers, WiFi-, and cellular-based IoT modules. We provided essential knowledge and hands-on training to empower participants for their upcoming IoT projects.
Instructor: Erfan Sadeghi, PhD Candidate, ECE Department, University of Windsor
Learn about the fundamentals of machine learning, Python basics and syntax, machine learning algorithms, and essential Python libraries and modules. July 17, 2023, starting at 10:00 AM.
Explore applications of machine learning in real-world scenarios, practical Python programming and project development, and other advanced concepts. Apply machine learning with Python in hands-on projects. July 18, 2023, starting at 10:00 AM.
Note: students must bring a Windows computer with them to participate in the activities.
LaTeX is a professional typesetting software system for document preparation. The author writes using plain text rather than the formatted text found in WYSIWYG (What You See Is What You Get). Word processors such as Microsoft Word, LibreOffice Writer, or Apple Pages need formatted text. This makes LaTeX extremely lightweight, fast, flexible, and accurate. For example, there are no chances of a document messing-up after adding a picture to it or crashing when creating a lengthy document.
LaTeXcan is used for a wide range of tasks, from the design of high-quality vector illustrations to the creation of eye-catching presentations. You can find memes comparing LaTeX and Microsoft Word by searching the Internet.
People who attend all four sessions will get the certificate. You will need to register for all 4 sessions separately.
Location: Hybrid event, in person (CEI 3000) , University of Windsor, and online (Microsoft Teams)
To lead the EV market, organizations must meet key engineering goals on performance safety and cost.
One of the concerns of a potential buyer is how far an electric vehicle can travel without a need for charging. The goal is to reduce the range of anxiety. The preferred range is over 400 miles while today it is 60-300 miles for EVs. Improve battery life and compare it to vehicle life(about 10 years). Today battery warranty is about 7-8 years. Increase battery and motor power density, and create differentiators in terms of comfort like reducing noise and vibration.
Safety is the most important criterion for EVs. Even a single battery fire could turn public opinion against electric mobility and set back Electric Vehicle development. Vehicles and components need to be tested against industry standards for compliance and reliability. The switching device in EV leads to ripple and overvoltage, which may lead to the failure of dielectrics. Also, the switching device results in emissions, which we need to ensure are below regulatory standards.
Affordability is one of the factors for mass adoption. The production cost of EVs should be equivalent to or lower than that of IC Engine vehicles. 30-40% cost of EVs is Battery, and it’s expected to reduce battery costs by <$100 / KW-hr. With the increase in electronics, software development costs and time have increased, and there is a need to improve development productivity and reduce manual error.
What will be discussed in this educational seminar:
How Simulation Solutions Applied in Four Critical Areas?
Machine learning (ML) and AI will play a key role in the development of 6G networks. Network virtualization and network softwarization solutions in 5G networks can support data-driven intelligent and automated networks to some extent and this trend will grow in 5G-advanced networks. Radio access network algorithms and radio resource management functions can exploit network intelligence to fine tune network parameters to reach close-to-optimal performance in 5G networks. In 6G networks, network intelligence is envisioned to be end-to-end, and air interface is envisioned to be AI-native. The user equipment (UE) devices need to be smarter, environment and context aware, and capable of running ML algorithms. This talk will focus on the main practical challenges in developing machine learning solutions in 5G use cases and emphasize with a case study how deployment of these solutions is much harder in a live network as compared to theoretical performance evaluation. Further, a vision for paradigm shift from AI-as-an-enabler to AI-Native air-interface will be provided for 6G networks.
Speaker: Dr. Majid of Nokia Bell Labs
M. Majid Butt received the M.Sc. degree in digital communications from Christian Albrechts University, Kiel, Germany, in 2005, and the Ph.D. degree in telecommunications from the Norwegian University of Science and Technology, Trondheim, Norway, in 2011. He is a senior research specialist at Nokia Bell Labs, France, and an adjunct Research Professor at Trinity College Dublin, Dublin, Ireland. Prior to that, he has held various positions at the University of Glasgow, U.K., Trinity College Dublin, Ireland, and Fraunhofer HHI, Germany. His current research interests include communication techniques for wireless networks with a focus on radio resource allocation, scheduling algorithms, energy efficiency, and machine learning for RAN. He has authored more than 75 peer-reviewed conference and journal articles, 4 book chapters and filed over 30 patents in these areas. He frequently gives invited and technical tutorial talks on various topics in IEEE conferences including, ICC, Globecom, VTC, etc.
Dr. Butt was a recipient of the Marie Curie Alain Bensoussan Post-Doctoral Fellowship from the European Research Consortium for Informatics and Mathematics. He has organized several technical workshops on various aspects of communication systems in conjunction with major IEEE conferences. He serves as an associate editor for IEEE Communication Magazine, IEEE Open Journal of the Communication Society and IEEE Open Journal of Vehicular Technology.
Austin ComSoc/SP/CtSoc and Computer/EMBS joint chapters would like to invite you to attend a special VDL talk on “AI Based Zero Energy Communication in 6G” on September 21st, 2022.
Prof. Sinem Coleri, Koc University (Turkey)
Supporting low- or zero-energy machine type devices through the incorporation of energy harvesting technologies in 6G is expected to reduce frequent battery replacements as well as sustaining the operation of battery-less devices. The nodes can harvest energy from natural sources, such as sun, vibration and pressure; inductive and magnetic coupling; and radio frequency (RF) based wireless energy transfer. The complexity of the integration of energy harvesting into communication system design is increasing with the wide variety of the requirements of massivemachine type communicationscenarios in terms of reliability, delay and throughput. This high complexity can only be handled by the usage of AI techniques to continuously monitor the system knowledge and update the optimal communication and energy harvesting parameters accordingly.In this talk,novel optimal resource allocation algorithmsare presentedfor low- or zero-energy machine type devicesbased on theusage of AI techniques. Thewireless communication network and energy harvesting parametersare mappedto the optimal resource allocation by using deep neural networks.
Sinem Coleri is Professor in the department of Electrical and Electronics Engineering at Koc University. She is also the founding director of Wireless Networks Laboratory (WNL). Her research interests are in wireless communications and networking with applications in machine-to-machine communication, sensor networks and intelligent transportation systems.
Sinem Coleri received the BS degree in electrical and electronics engineering from Bilkent University in 2000, the M.S. and Ph.D. degrees in electrical engineering and computer sciences from University of California Berkeley in 2002 and 2005. She worked as a research scientist in Wireless Sensor Networks Berkeley Lab under sponsorship of Pirelli and Telecom Italia from 2006 to 2009. Since September 2009, she has been a faculty member in the department of Electrical and Electronics Engineering at Koc University.
Dr. Coleri has more than 180 peer-reviewed publications with citations over 8900 (Google scholar profile). She has received numerous awards and recognitions, including TUBITAK (The Scientific and Technological Research Council of Turkey) Incentive Award and IEEE Vehicular Technology Society 2020 Neal Shepherd Memorial Best Propagation Paper Award in 2020, College of Engineering Outstanding Faculty Award at Koc University and IEEE Communications Letters Exemplary Editor Award as Area Editor in 2019, Turkish Academy of Sciences Distinguished Young Scientist (TUBA-GEBIP) in 2015.
Dr. Coleri has been Area Editor of IEEE Communications Letters and IEEE Open Journal of the Communications Society since 2019, Editor of IEEE Transactions on Vehicular Technology since 2016 and Senior Editor of IEEE Access since 2022. She is an IEEE Fellow.