Latest Past Events

RAS Challenges and Silicon Lifecycle Management

Virtual: https://events.vtools.ieee.org/m/402589

This talk discusses resiliency challenges for emerging SOCs, and optimizing the SOC health using prognostics, test and analytic solutions, utilized for managing silicon lifecycle (SLM) for improving quality and yield; and also address aging and degradation challenges for improved RAS and functional safety. Speaker(s): Jyotika Athavale Virtual: https://events.vtools.ieee.org/m/402589

Designing salient, naturalistic “super-stimuli” with deep generative models

Virtual: https://events.vtools.ieee.org/m/403671

Attention can be deployed either voluntarily – based on task goals – or captured automatically – by salient sensory stimuli. Previous studies have controlled stimulus salience by altering low-level image features (e.g., luminance, or popout), or by inducing motion dynamics (e.g., flash, loom); such salient stimuli capture attention automatically by driving strong neural responses in multiple visual areas. Yet, precisely what combinations of naturalistic (high-level) stimulus features drive the strongest neural responses, and produce the highest behavioral salience, remains a topic of active research. As a first step toward this goal, I will describe the design of salient “super-stimuli” – high-resolution, naturalistic images tailor-made to evoke the strongest responses in specific brain areas. The high dimensionality of natural images renders this optimization prohibitively challenging at the pixel level. To tackle this challenge, we extend a recently developed framework called XDream . This framework employs a deep generative network in combination with a heuristic optimization (genetic) algorithm and was recently tested to generate “super-stimuli” for the monkey visual cortex. We extend this framework with a CNN-based encoder for human functional MRI (fMRI) brain responses and design novel classes of “super-stimuli” optimized for the human brain. Specifically, we advance the optimization algorithm to address the following questions: i) Given an object category (e.g., telephones or computers) can we design a class of super-stimuli that still respects category boundaries? ii) Can we design “chimeric” super-stimuli that can combinatorially activate (or suppress) multiple brain regions (e.g., primary visual cortex and face area), at once? I will conclude by describing ongoing work that seeks to validate the generated images by measuring human visual cortex responses directly with fMRI and quantifying the behavioral salience of the generated images with psychophysical experiments. Speaker(s): Prof. Sridhar Devarajan, Virtual: https://events.vtools.ieee.org/m/403671

Recent Advancements in Frequency Selective Surfaces.

Room: NKN, Bldg: Main Building, Department of Electronics & Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India, 721302

Since the last few decades, frequency selective surfaces (FSSs) have attracted significant research interest owing to their simple design, ease of fabrication, and wide adaptability. They have found a wide range of electromagnetic applications, such as absorbers, filters, polarizers, high-impedance surfaces, absorbers, antennas, and so forth, across various frequency ranges. This talk will center around several design aspects of microwave devices exploiting the FSS concepts. Speaker(s): Dr. Saptarshi Ghosh, Room: NKN, Bldg: Main Building, Department of Electronics & Electrical Communication Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal, India, 721302