CEMSE Weekly Updates - April 22, 2025 Tue, Apr 22 2025 Newsletter Upcoming Events Stay informed about the upcoming events and the latest news from CEMSE. Upcoming Events Metasurface Based Optical Metrology Systems: Design, Fabrication, and Implementations Arturo Burguete Lopez, Ph.D. Student, Electrical and Computer Engineering Apr 27, 11:00 - 13:00 B3 L5 R5209 Metasurfaces integrated optics This dissertation introduces a framework to advance optical metasurfaces from individual components to integrated optical instruments, it presents demonstrations of metrology techniques that combine machine learning and nanophotonic technologies for remote sensing that outperform methods based on conventional optics, thus advancing the next generation of optical instrumentation. Harnessing Multi-modal AI and Machine Learning for Next-Generation 6G Networks Asmaa Abdallah, Research Scientist, Electrical and Computer Engineering Apr 27, 12:00 - 13:00 B9 L2 R2325 LLM machine learning 6G Wireless communication Digital signal processing This seminar explores how multi-modal AI and large language models can optimize future 6G wireless networks by integrating diverse data sources to enhance reliability, efficiency, and overall performance. On Singular Equations Modeling Electrostatic MEMS Katerina Nik, Assistant Professor, Applied Mathematics and Computational Sciences Apr 28, 12:00 - 13:00 B9 L2 R2325 MEMS free boundary problems This talk introduces mathematical models for microelectromechanical systems (MEMS), focusing on the existence and behavior of solutions to equations describing the MEMS device's instability due to electrostatic forces that can lead to singularities in the mathematical equations. Design and Process Development of Graphene-Based Geometric Diodes for Enhanced Performance Heng Wang, Ph.D. Student, Electrical and Computer Engineering Apr 29, 14:00 - 16:00 B2 L5 R5220 Thz rectennas Graphene geometric diodes semiconductors nano devices artificial intelligence This thesis advances graphene geometric diodes (GGDs) by addressing fabrication, performance, and design challenges using innovative nanofabrication techniques and artificial intelligence-enhanced computational methodologies. Control and Estimation Designs Using Model-Based and Model-Free Approaches for Water Quality Monitoring in Process Systems Fahad Aljehani, Ph.D. Student, Electrical and Computer Engineering Apr 30, 10:00 - 12:00 B1 L4 R4214 machine learning algorithm optimal control Control Theory Reinforcement Learning This dissertation develops and evaluates advanced control and estimation strategies to address complex dynamics and measurement limitations in water-related applications, specifically optimizing fish growth in aquaculture and estimating bacterial concentration in wastewater treatment plants. Efficient Antenna-on-Chip with Optimized Artificial Magnetic Conductor Performance for 6G mm-Wave Applications Yiyang Yu, Ph.D. Student, Electrical and Computer Engineering Apr 30, 15:30 - 17:30 B3 L5 R5209 Electrically Small Antenna Design antenna design on-chip antennas 6g wireless systems This dissertation introduces innovative Artificial Magnetic Conductor structures and a reconfigurable superstrate to overcome profile thickness, illumination efficiency, and radiation pattern limitations in CMOS-integrated Antennas-on-Chip, thereby enhancing their performance and versatility for future 6G wireless communication systems. Retraction Maps, Feedback Linearization and Nonholonomic Integrators Ravi Banavar, Professor, Systems and Control Engineering, IIT Bombay May 1, 12:00 - 13:00 B9 L2 R2325 This talk will introduce the utility of retraction maps on Riemannian manifolds to two applications in applied mechanics and control. Towards Trustworthy News Recommendation Systems Manal A. Alshehri, Ph.D. Student, Computer Science May 1, 17:00 - 19:00 B3 L5 R5209 machine learning artificial intelligence personalized recommendations Generative Adversarial Networks This thesis enhances the trustworthiness of news recommendation systems by addressing the cold start problem for new users/items, enabling efficient user data removal for privacy, and mitigating multi-dimensional filter bubbles to improve diversity.
