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

A key measure of a productive tech ecosystem is the successful transition of new graduates from academia into industry. With academia focusing on building a broader knowledge base, industry-readiness of students for a successful transition necessitates dynamically evolving industry-academia collaborations. This 2-event series initiated by IEEE Women in Engineering Rochester focuses on working with local partners towards the common goal of creating awareness, addressing challenges, and promoting talent retention within the local tech ecosystem; a key focus is on DIVERSITY & INCLUSION. [] Co-sponsored by: Women@MKS Agenda: - WELCOME: - Deyasini Majumdar, PhD, SMIEEE, Sr. FPGA Design Engineer, MKS Instruments & Chair, IEEE WIE Rochester - Wendi Heinzelman, PhD, FIEEE, FACM, Prof. & Dean, Hajim School of Engg. & Applied Sciences, U. Rochester - GREATER ROCHESTER AREA INITIATIVES: - Andrea Tuttle, MA, Talent Strategy Program Manager Campus ROC, Rochester Chamber of Commerce - TECHNICAL PRESENTATION: - Cory Merkel, PhD, Associate Prof., Rochester Institute of Technology - PANEL DISCUSSION: Evolving Dynamics of Industry-Academia Interfaces - MODERATOR: - Gaurav Sharma, PhD, Fellow IEEE, SPIE, IS&T, Professor & Distinguished Researcher, U. Rochester - PANELISTS: - Santosh Kurinec, PhD, FIEEE, Professor, Rochester Institute of Technology - Greg Gdwoski, PhD, AAMI Fellow, Prof., Executive Director, CMTI, Univ. of Rochester & Past Director, IEEE R1 - Bijal Thakkar, MBA, Vice President & General Manager, TE Connectivity - Juniyali Nauriyal, PhD, CEO, Photonect Interconnect Solutions & Activate Fellow - Hannah Rickert, BS/MS Student Biomedical Eng. - Abhaya S Hegde, PhD Student, Physics and Astronomy - CLOSING REMARKS - NETWORKING & INDUSTRY EXHIBITS - Some companies will have their recruiters in attendance to collect resumes - Room: Feldman Ballroom, Bldg: Frederick Douglass Building, University of Rochester, River Campus, Frederick Douglass Building, Feldman Ballroom, Rochester, New York, United States, 14611, Virtual: https://events.vtools.ieee.org/m/431040

This presentation provides an introductory talk to the field of Artificial Intelligence (AI), tracing its evolution through key milestones and breakthroughs. We will explore the foundational requirements for AI, including the critical role of big data, and high-performance computing (HPC). The presentation will highlight AI's potentials, such as natural language processing (NLP), image processing, and diverse applications in scientific research. Additionally, we will address the inherent limitations of AI, focusing on security challenges, and the risks of data leakage. This introduction aims to equip participants with an understanding of AI's capabilities and constraints, fostering informed discussions about its future impact Co-sponsored by: Ali Daneshmand Speaker(s): Ifana, Agenda: Virtual: https://events.vtools.ieee.org/m/428481

Agenda: https://ieeemeetings.webex.com/ieeemeetings/j.php?MTID=m5725adc53fc8cb6477797c703456e752 Date: October 8, 2024 Location: Central Connecticut State University, AIH 3rd Floor Time: 6:30 PM – 9:30 PM Meeting (7:00pm) Approval of Agenda (7:05pm): Guest Reports Senior Member Applicants Section Reports Secretary’s Report : Treasurer’s Report : Webmaster’s Report : Affinity Groups Women in Engineering : · WIEFORUMEAST (Charlotte Blair) o Color laser printer for the forum o Helpers from Wednesday before Forum Young Professionals : PACE : LMAG : Committee Reports Audit Report : Entrepreneur Society : Membership : SAC (David Broderick): Society Reports AP/MTT/UFFC : Computer/SMC/SIT : CS/IAS/RA : PES : PELS : Old Business · AGM · Updated draft of revised Section Addendum · Senior Member Elevations (Oscar/Gary) · Social Hours (Oscar) · IEEE Milestones New Business · ? Next ExCom Meeting November 12th ?? Room: 315, Bldg: AIH, 1615 Stanley Street, New Britain, Connecticut, United States, Virtual: https://events.vtools.ieee.org/m/436276

Having been a technology consultant for over 40 years I have seen many shifts in the business climate. Hopefully you have all seen the first in this series of presentations on what it takes to get started in consulting. This session is a more advanced look at what you can and should do to grow your business and keep it healthy. I will show how I have made my business stronger over the years and how I modified my offerings to keep things moving forward, protect my cash flow during good times and bad. The 5 major topic categories covered will be: - General Business Practices including some Truths and Lies - Going it alone - The one person shop. - Partnerships and associations. How to do more while keeping control and not having to do it all yourself. - Working with Agencies. The Good, Bad, and Ugly. - Diversification of your business. Adding services to keep a steady cash flow. Speaker(s): , Larry Agenda: - General Business Practices including some Truths and Lies - Going it alone - The one person shop. - Partnerships and associations. How to do more while keeping control and not having to do it all yourself. - Working with Agencies. The Good, Bad, and Ugly. - Diversification of your business. Adding services to keep a steady cash flow. Virtual: https://events.vtools.ieee.org/m/437667

Careers in Technology and Standards in Action: IEEE 2933 Clinical IoT Data and Device Interoperability with TIPPSS - Trust, Identity, Privacy, Protection, Safety, Security a new Standard -- Selected for the 2024 Award Advanced technologies enable digital transformation … and can increase RISK. Connected healthcare leveraging advanced technologies and data can improve insights and outcomes. In the context of this important rapidly developing Clinical IoT industry, the IEEE 2933 Working Group has been selected as a recipient of the IEEE SA Emerging Technology Award “For the development of IEEE 2933-2024, IEEE Standard for Clinical Internet of Things (IoT) Data and Device Interoperability with TIPPSS - Trust, Identity, Privacy, Protection, Safety, Security.” The IEEE SA Emerging Technology Award is awarded for the initiation, advancement or progression of a new technology through the IEEE SA open consensus process. Leadership of this team Florence Hudson and William Harding, PhD will share their extensive knowledge and experience, and provide an excellent deep dive into careers in this field. Speaker(s): Florence Hudson, William C. Harding, PhD Virtual: https://events.vtools.ieee.org/m/434307