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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Simple illustration of permutation technique
Published:
This draft contains a detailed example illustrating a bit level permutation (or swapping, interchangeably used in this draft) of truth table.
Dont care cheatsheet for easy comprehension
Published:
Don’t care concept summarized in a short cheat sheet, this could help to comprehend different type of don’t care under logic synthesis context.
portfolio
Portfolio item number 1
Short description of portfolio item number 1
Portfolio item number 2
Short description of portfolio item number 2
publications
Paper Title Number 1
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1).
Download Paper | Download Slides
Paper Title Number 2
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2).
Download Paper | Download Slides
Paper Title Number 3
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).
Download Paper | Download Slides
Paper Title Number 4
Published in GitHub Journal of Bugs, 2024
This paper is about fixing template issue #693.
Recommended citation: Your Name, You. (2024). "Paper Title Number 3." GitHub Journal of Bugs. 1(3).
Download Paper
talks
Implementing System T in Haskell
Published:
Check the plug talk slides here.
Logic synthesis in a nutshell
Published:
Logic synthesis performs optimization on given network, in this talk, we are concentrating on technology independent, combinational logic synthesis, and illustrate the basic ideas on various intermediate representation and the features they have. Show why these basic concepts are more important than algorithms and what else can we do with them.
Check the talk slides here.
Logical Neural Networks
Published:
This talk is a presentation for MICS6001: Symbolic and Neurosymbolic Reasoning. You could fetch the related paper here.
Logical Neural Network(LNN) is developed by IBM, which is one of the core engine of their Neurosymblic Tookit. This presentation gives a high level overview of what LNN is and what’s happening under the hood. The key differences compared with classical Markov Neural Network. At the end, a quickstart live demo will help audience get familiar with how to use it in Python.
Check the talk slides here.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.