IEEE North Jersey Section

The 2024 IEEE Metropolitan AI Applications Symposium (IEEE MAIAS-2024) will be held online (Zoom) on Saturday, December 14, 2024, from 10 am until 12:30 pm. The symposium consists of one keynote presentation and several invited presentations, covering various topics in AI methods, systems, and applications. This symposium is organized in collaboration with Canadian-American Research Forum on AI Technologies. Organizers: IEEE North Jersey Engineering in Medicine and Biology Chapter (EMB) IEEE North Jersey Section Canadian-American Research Forum on AI Technologies Registration Required: https://events.vtools.ieee.org/m/447282 Conference Room: Join Zoom Meeting Meeting ID: 506 875 4099 https://zoom.us/j/5068754099 2024 IEEE Metropolitan AI Applications Symposium Symposium Program 10:00AM: Welcome Messages Prof. Yu-Dong Yao (IEEE North Jersey Section) 10:05AM: Keynote Speaker: Prof. Zhifeng Kou, NJIT AI in Medical Imaging: An Initial Investigation 10:40AM: Syon Doshi, Stevens Institute of Technology Autonomous Driving and Machine Learning 10:50AM: Cleopatra Mozolewski, Stevens Institute of Technology Bond Pricing Using Deep Learning 11:00AM: Aditi Dam, Stevens Institute of Technology Reading Comprehension Using Deep Learning 11:10AM: Colm Murrer, Stevens Institute of Technology Visual Arts Classified by Deep Learning 11:20AM: Rose Friedman, Stevens Institute of Technology AI and Gardening 11:30AM: Pratik Jain, NJIT Enhancing Functional Connectivity with Dictionary Learning for Brain Fingerprints 11:40AM: Marco Marena, NJIT Generative AI for Solar Physics 12:15PM: Conclusion Remark Prof. Yu-Dong Yao (IEEE North Jersey Section) Registration IEEE member $ 0.00 Non-member $ 0.00 IEEE Student/Graduate Student/Life Member $ 0.00 Non-IEEE Student/Graduate Student $ 0.00 Organizing Committee Prof. Yu-Dong Yao, IEEE North Jersey Section Prof. Elisa Kallioniemi, NJIT, Newark Prof. Wei-Ping Zhu, Concordia University, Montreal Virtual: https://events.vtools.ieee.org/m/447282

Special Presentation by Dr. Ayush Dwivedi (Tampere U., Finland) Hosted by the Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group Date/Time: Thursday, December 19th, 2024 @ 12:00 UTC Topic: Machine Learning Ideas for Sensor Networks Abstract: This talk explores the application of machine learning (ML) techniques to address the challenges in scaling sensor networks while maintaining accuracy and energy efficiency. First, we discuss ML-based approaches to optimize data transmission, significantly reducing communication overhead and extending battery lifetimes. Second, we examine the impact of such optimizations on enhancing overall network capacity. Finally, the role of ML in sensor calibration is analyzed, highlighting its potential to improve accuracy and scalability. Speaker: Dr. Ayush Dwivedi a postdoctoral research scholar at Tampere University, Finland, with a PhD from the International Institute of Information Technology, Hyderabad, India. His research focuses on next-generation wireless communication, including non-terrestrial networks, stochastic geometry, satellite-based IoT, and sensor networks for smart cities. He has been an active member of the IEEE INGR Satellite Working Group for several years, contributing to ideas on satellite-based sensor networks. Co-sponsored by: Machine Learning Ideas for Sensor Networks Virtual: https://events.vtools.ieee.org/m/448221