September 21 through November 2, 2024. Six Saturdays 1:30-4:30pm (9/21, 9/28, 10/5, 10/19, 10/26, 11/2). The IEEE North Jersey Section Communications Society Chapter is offering a course entitled "DEEP LEARNING WITH APPLICATIONS". Deep learning is a transformative field within artificial intelligence and machine learning that has revolutionized our ability to solve complex problems in various domains, including computer vision, natural language processing, and reinforcement learning. This hands-on course on deep learning is designed to provide students with an understanding how these amazing successes are made possible by drawing inspiration from the way that brains, both human and otherwise, operate. Students will gain a comprehensive foundation in the principles, techniques, and applications of deep neural networks. Learning how to solve real data-set based applications will teach students how to really apply deep learning with Python programming software. Participants will be asked to design and train deep neural networks to perform tasks such as image classification using commonly available data sets. However, participants are encouraged to apply the techniques from this course to other data sets according to their interests. Discuss with the instructor in order to propose your own project. More importantly, this will set the foundations for understanding and developing Generative AI applications. The IEEE North Jersey Section's Communications Society Chapter can arrange for providing IEEE CEUs - Continuing Education Units (for a $5 charge) upon completion of the course. Course prices: $75 for Undergrad/Grad/Life/ComSoc members, $100 for IEEE members, $150 for non-IEEE members Co-sponsored by: Education Committee Speaker(s): Thomas Long, Agenda: 1. Introduction to Neural Networks: Explore the fundamental concepts of artificial neural networks, backpropagation, activation functions, and gradient descent, laying the groundwork for deep learning understanding. 2. Introduction to PyTorch: Learn how to implement and train neural networks using PyTorch one of the most popular deep learning frameworks. Understand tensors. 3. Computer Vision Applications: Apply deep learning to computer vision problems, including image classification and object detection using Convolutional Neural Networks (CNNs) 4. Training and Optimizing Deep Neural Networks: Study techniques for training deep neural networks effectively, including optimization algorithms, weight initialization, regularization, and dropout. 5. Sequential Data Analysis: Explore how deep learning is used to analyze sequential data using Recurrent Neural Networks (RNNs). In particular, explore how neural networks are used in Natural Language Processing (NLP) tasks such as sentiment analysis and machine translation. 6. Generative AI: Overview of generative ai techniques that leverage the patterns present in a dataset to generate new content. Applications of generative ai include large language models such as ChatGPT and image generation models such as Midjourney and Stable Diffusion. This course assumes a basic understanding of machine learning concepts and programming skills in Python. Familiarity with linear algebra and calculus will be beneficial, but not mandatory. Statistical software (Python, Scikit-learn) and Deep Learning Frameworks (Pytorch, TensorFlow) will be used throughout the course for the exploration of different learning algorithms and for the creation of appropriate graphics for analysis. Learning objectives: Subjects covered include these and other deep learning related materials: artificial neural networks, training deep neural networks, RNN, CNN, image recognition, natural language processing, GANs, data processing techniques, and NN architectures. The course is intended to be subdivided into 3-hour sessions. Each lecture is further subdivided into lecture, guided and independent project based exercises to build experience with hands-on techniques. This course will be held at FDU - Teaneck, NJ campus. Checks should NOT be mailed to this address. Can bring checks in person or use online payments at registration. Email the organizer for any questions about course, registration, or other issues. Technical Requirements: Students will need access to the Python programming language. In addition to a standard Python installation, most programming exercises will use the package Scikit-learn. Basic programming skills and some familiarity with the Python language are assummed. Students are expected to be able to bring a laptop onto which most of these libraries can be pre-installed using python's pip install. Most of the coding in this course will use the Python programming language. Coding examples and labs will be distributed in the form of Juypter notebooks. In addition to standard Python, most programming exercises will use either the PyTorch or TensorFlow libraries. Books and other resources will be referenced. Room: Room 306, Bldg: Becton Building , FDU Metropolitan Campus, 960 River Road, Teaneck, New Jersey, United States, 07666

Event is in Dubai. UAE and is being Live Streamed. The Live Stream is FREE. Follow link to Register and Attend. Co-sponsored by: IEEE Futtures Virtual: https://events.vtools.ieee.org/m/439443

In this webinar, we will discuss the latest developments at NY CREATES in the scalable fabrication of quantum devices. We will highlight our work with superconducting materials such as Ta, Nb, Al, and their oxides and nitrides, detailing the painstaking work required to reformulate CMOS processes to those designed for quantum technologies, which have a wide range of application including in communications, quantum computing, sensing, data security, solid state electronics, nanotechnology, photonics, quantum circuits, advanced fabrication, superconducting digital logic, and superconducting optoelectronics neuromorphic computing. With specific examples, we will illustrate how we leverage decades of learning from the CMOS industry, aiming to enable the fabrication of devices with tightly controlled performance characteristics. We will present the synergistic nature of our process development strategy, that advances a variety of quantum technologies at 300 mm wafer scale. These efforts are essential to establish a well-defined superconducting quantum process design kit (SQPDK) and facilitate the fabrication of quantum circuits that are faithful to designer intent, in a true ‘quantum foundry’ model. NY CREATES (New York Center for Research, Economic Advancement, Technology, Engineering, and Science) is a research and development entity in New York State that focuses on advancing innovation in semiconductor technology and other high-tech industries. It plays a significant role in fostering partnerships between academia, industry, and government to support technological advancements, economic growth, and workforce development. NY CREATES manages and operates several advanced research facilities, including the Albany NanoTech Complex, which is one of the most advanced semiconductor research facilities in the world. The organization works on a variety of projects related to microelectronics, nanotechnology, photonics, and other cutting-edge technologies, aiming to position New York as a global leader in these fields. Contact George Blasiak ([email protected]), Industry Liaison at Syracuse IEEE for more information on the event. Speaker(s): Ekta Bhatia, Ph.D Virtual: https://events.vtools.ieee.org/m/429789

ABOUT THE LECTURE “CHIPS: Execute for Success” Semiconductor innovation is a foundation to national security, economic security and job security in America. Since before the passage of CHIPS and Science Act in summer 2022, federal and state governments, companies and universities have stepped up the effort to revitalize the entire semiconductor supply chain in the U.S. We will review Purdue University’s initiatives in this area and draw some lessons on universities’ role in talent development, research moonshots, and public private partnership. ABOUT THE SPEAKER Professor Mung Chiang, President of Purdue University Mung Chiang is the 13th president of Purdue University and the Roscoe H. George Distinguished Professor of Electrical and Computer Engineering. He was previously the John A. Edwardson Dean of the College of Engineering and executive vice president for strategic initiatives at Purdue University, as well as the Arthur LeGrand Doty Professor of Electrical Engineering at Princeton University. Chiang founded the Princeton EDGE Lab in 2009 and then founded several startup companies and industry consortia in edge computing. As the Science and Technology Adviser to the U.S. Secretary of State in 2020, he initiated tech diplomacy programs for the U.S. government. Currently he serves on the inaugural board of the U.S. Foundation for Energy Security and Innovation and several corporate and nonprofit boards. Chiang received his BS (1999), MS (2000) and PhD (2003) from Stanford University and an honorary doctorate (2024) from Dartmouth College. For his research in communication networks, he received the NSF Alan T. Waterman Award (2013), as well as the IEEE Kiyo Tomiyasu Award (2012), the IEEE INFOCOM Achievement Award (2022) and a Guggenheim Fellowship (2014). He was elected to the American Academy of Arts and Sciences (Class of Mathematical and Physical Sciences 2024), the National Academy of Inventors (2020) and the Royal Swedish Academy of Engineering Sciences (2020). Co-sponsored by: Columbia University Department of Electrical Engineering Room: 400, 530 W120th Street, New York, New York, United States, 10027

Dear IEEE Connecticut Section Member, The IEEE Connecticut Section's Annual General Meeting features networking time, an engaging presentation on a relevant topic followed by an excellent dinner. This is a great opportunity to connect with other IEEE members in Connecticut and catch up with our activities. Member/ Senior Member $30+tax Life Member/ Fellow $15+tax Student Member $15+tax Nonmember $75+tax When registering partners please select your own member grade for them to get the correct cost and not the non-member cost. Dinner options: - Chicken Marsala - Grilled Salmon - Prime Rib - Vegetarian (Vegetable Ravioli with Cheese) - Gluten-Free - upon request Venue: Casa Mia at the Hawthorne 2421 Berlin Turnpike, Berlin, CT 06037 Hope to see you there, Speaker(s): Armen Pischdotchian, Agenda: 6:00pm - Social Hour, Hors d’oeuvres, cash bar 6:30pm - Dinner 7:00pm - Announcements 7:30pm – Speaker + Dessert 9:00pm - Conclusion Bldg: Casa Mia at the Hawthorne, 2421 Berlin Tpke, Berlin, Connecticut, United States, 06037

It’s time again to kick off our season of meetings with the annual computer graphics film show, featuring the latest and greatest computer animations direct from the ACM SIGGRAPH conference held this summer. (We have been running a graphics talk each year since 1980! This year is our 45th!) It will be an entertaining overview of recent advances in computer graphics. Room: 105, Bldg: Computer Science Building, 35 Olden St, Princeton, New Jersey, United States, 08544, Virtual: https://events.vtools.ieee.org/m/437505