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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

[] Jersey Shore STEM Ecosystem K through Industry Pipeline - Industry Connections Teacher Workshop Event will introduce various topics to teachers during the Speed Dating Event: A Day at the Museum, Lunch with Leaders and Luminaries, Curriculum Guides, and more. Ocean, New Jersey, United States

This invited talk will delve into the intricate process of Chemical Mechanical Polishing (CMP) and its pivotal role in Hybrid Bonding (HB) within semiconductor manufacturing. CMP is a sophisticated technique that leverages both chemical and mechanical forces to achieve film planarization. The discussion will highlight the critical importance of CMP in HB, particularly in attaining precise control over dishing and surface roughness. The key challenges associated with CMP for HB will be addressed, such as defectivity, dishing, and loading, and present strategies for addressing them to ensure optimal outcomes. Furthermore, the session will highlight the necessity of co-optimizing CMP processes for HB, emphasizing its implications in in the ever-evolving field of semiconductor manufacturing and advanced packaging. Room: CESTM auditorium, Bldg: CESTM, 255 Fuller Rd, Albany, New York, United States, 12203

This is the initial (virtual) meeting of the newly-formed Life Member Affinity Group (LMAG) in the IEEE Connecticut Section. We will be planning activities for 2025 and discuss process for filling CT LMAG Officer positions. Any Connecticut Life Member is welcome to participate. Agenda: 1. Introductions 2. What is an LMAG? 3. Discussion of 2025 goals and activities 4. Organization (including process for filling officer positions) 5. Meeting schedule 6. Any other business Virtual: https://events.vtools.ieee.org/m/441065

Radar technology plays an important role in our daily lives with applications ranging from security screening for ensuring the safety of the public to structural health monitoring to name a few. In the field of subsurface sensing, Ground Penetrating Radar (GPR) is a key technology for detecting buried explosive threats, such as landmines and Improvised Explosive Devices (IEDs). The talk will be focused on GPR systems mounted on board Unmanned Aerial Vehicles (UAVs), leveraging the Synthetic Aperture Radar (SAR) paradigm to provide high-resolution radar images of the subsurface. This kind of systems brings together the advantages of UAVs (e.g., enabling the inspection of difficult-to-access areas without interacting with the soil) and the capability of radar systems to detect buried targets. In this talk, several prototypes of UAV-mounted GPR-SAR systems tested in realistic scenarios will be presented, showing their success to detect buried threats in realistic scenarios. The current challenges and future trends of this technology will be also discussed. Co-sponsored by: Sai Padmanabhan; Chair AP/MTT chapter of Long Island NY. [email protected] Speaker(s): MARIA, Agenda: 6:15PM Set up Webex online with speaker 6:25PM Introduce speaker and introduction to AP society's Ambassador program 6:30PM Talk begins 7:30PM Talk concludes 7:30-7:45PM Q & A session 8:00PM conclusion and vote of thanks Virtual: https://events.vtools.ieee.org/m/428577

Khandakar Nusrat Islam will conduct a deep dive on her experience as an RF/Microwave Solutions Engineer at Keysight Technologies, where she excels in both engineering and project management. Specializing in RF solutions architecture and project oversight, Nusrat is instrumental in developing custom global solution delivery next-generation solutions at Keysight Technologies. Dr. Islam's career in technology is crucial for driving innovation and addressing pressing global challenges. Her work in developing cutting-edge solutions at Keysight Technologies not only advances engineering practices but also enhances connectivity and improves quality of life. By driving technological progress, she contributes to transformative breakthroughs that benefit industries and communities worldwide. Co-sponsored by: Martha Dodge Speaker(s): Khandakar Nusrat Islam, PhD Virtual: https://events.vtools.ieee.org/m/434310

Khandakar Nusrat Islam will conduct a deep dive on her experience as an RF/Microwave Solutions Engineer at Keysight Technologies, where she excels in both engineering and project management. Specializing in RF solutions architecture and project oversight, Nusrat is instrumental in developing custom global solution delivery next-generation solutions at Keysight Technologies. Dr. Islam's career in technology is crucial for driving innovation and addressing pressing global challenges. Her work in developing cutting-edge solutions at Keysight Technologies not only advances engineering practices but also enhances connectivity and improves quality of life. By driving technological progress, she contributes to transformative breakthroughs that benefit industries and communities worldwide. Speaker(s): , , Agenda: Khandakar Nusrat Islam will conduct a deep dive on her experience as an RF/Microwave Solutions Engineer at Keysight Technologies, where she excels in both engineering and project management. Specializing in RF solutions architecture and project oversight, Nusrat is instrumental in developing custom global solution delivery next-generation solutions at Keysight Technologies. Dr. Islam's career in technology is crucial for driving innovation and addressing pressing global challenges. Her work in developing cutting-edge solutions at Keysight Technologies not only advances engineering practices but also enhances connectivity and improves quality of life. By driving technological progress, she contributes to transformative breakthroughs that benefit industries and communities worldwide. Virtual: https://events.vtools.ieee.org/m/442946