S
Saibal Mukhopadhyay
Researcher at Georgia Institute of Technology
Publications - 432
Citations - 10232
Saibal Mukhopadhyay is an academic researcher from Georgia Institute of Technology. The author has contributed to research in topics: Computer science & CMOS. The author has an hindex of 40, co-authored 381 publications receiving 8814 citations. Previous affiliations of Saibal Mukhopadhyay include IBM & Purdue University.
Papers
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Journal ArticleDOI
Prevalence and predictors of left atrial appendage inactivity in patients of rheumatic mitral stenosis in sinus rhythm: An observational study.
TL;DR: In this article, the prevalence of LAA inactivity (LAAI) in severe RMS and assess its independent predictors were studied and found that LAAI was the only independent predictor of left atrium (LA)/LAA smoke with or without associated thrombus.
Journal Article
Triglycerides and Atherosclerotic Cardiovascular Disease.
Raman Puri,Vimal Mehta,S S Iyengar,S N Narasingan,P. Barton Duell,G B Sattur,Krishnaswami Vijayaraghavan,Jagdish C. Mohan,Subhash Kumar Wangnoo,Jamshed Dalal,D Prabhakar,Rajeev Agarwal,Manish Bansal,Jamal Yusuf,Saibal Mukhopadhyay,Sadanand Shetty,Prabhash Chand Manoria,Avishkar Sabharwal,Akshayaya Pradhan,Rahul Mehrotra,Sundeep Mishra,Sonika Puri,A Muruganathan,Abdul Hamid Zargar,Rashida Melinkari Patanwala,Soumitra Kumar,Neil Bardoloi,K K Pareek,Aditya Kapoor,Ashu Rastogi,Devaki Nair,Altamash Shaikh,Chandra Mani Adhikari,Muhammad Shoaib Momen Majumder,Dheeraj Kapoor,Madhur Yadav,M R Mubarak,A K Pancholia,Rakesh Sahay,Rashmi Nanda,Nathan D. Wong +40 more
Journal ArticleDOI
RADNet: A Deep Neural Network Model for Robust Perception in Moving Autonomous Systems
TL;DR: A novel ranking method to rank videos based on the degree of global camera motion and a novel input dependent weighted averaging strategy for fusing local and global features.
Posted Content
Characterization of Generalizability of Spike Time Dependent Plasticity trained Spiking Neural Networks
TL;DR: In this article, the generalizability properties of the Spike Time Dependent Plasticity (STDP) learning process were analyzed using the Hausdorff dimension of the trajectories of the learning algorithm.
Journal ArticleDOI
Electrothermal analysis of spin-transfer-torque random access memory arrays
TL;DR: The analysis shows that self-heating can results in considerable increase in both steady-state value and transient change in temperature of individual cells and negatively impacts electrical reliability metrics namely, read margin and detection accuracy; degrades cell performance; and modulates energy dissipation.