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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.
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Posts
Poems
Published:
Want a similar webpage for yourself?
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During my “first” friendly yet long encounter with html scripts, I often asked myself: “Why endure this long fight?”. Every time, I shyly answered: To make someone’s long fight short
. For not fooling myself, or along the first principle of Ricahrd Feynman that you must not fool yourself – and you are the easiest person to fool.
, a blog post is born – to help you with your website. For those who are going ahead, wish you a Happy Website building
! All are welcome.
portfolio
John Bardeen - Two-time Nobel Laureate (23 May 1908 – 30 Jan 1991)
Always right there in the trenches until death do us part! 
Von Braun - Rocket Scientist (23 Mar 1912 – 16 Jun 1977)
Build a Rock Castle rather than miles of Rock Wall! 
Ludwig Van Beethoven (17 Dec 1770 – 26 March 1827)
From the ashes we shall rise! 
Alexander Grothendieck (28 March 1928 – 13 Nov 2014)
Starting from scratch is always an option! 
A P J Abdul Kalam - Rocket Man of India (15 Oct 1931 – 27 Jul 2015)
If you want to shine like a sun, first burn like a sun! 
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). http://academicpages.github.io/files/paper1.pdf
Paper Title Number 4
Published in Journal 2, 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). http://academicpages.github.io/files/paper2.pdf
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). http://academicpages.github.io/files/paper2.pdf
Paper Title Number 11
Published in Journal 1, 2015
Paper Supplementary BibtexLorem ipsum dolor sit amet. [button url=”http://www.google.com”]
Recommended citation: Your4 Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
talks
Photometric Stereo for Scanning Electron Microscopy
Published:
This is an industry collaboration talk given to a Research Team from KLA-Tencor. Here, we presented the concepts of photometric stereo, to think of and discuss ways to extend these ideas for their Scanning Electron Microscopes. [Slides]
Special session on Rolling Shutter Camera
Published:
This talk in NCVPRIPG 2017, headed by Prof. A. N. Rajagopalan, covers multiples works from our lab involving RS Camera. Here, I presented our ICCV 2017 work Going Unconstrained with RS Deblurring! [Slides]
Divide and Conquer for Full-resolution Light Field Deblurring
Published:
Here, we presented our light field
work from CVPR 2018! The objective of this session (i.e., Vision India
@ ICVGIP 2018) is to motivate Indian researchers (especially disadvantaged) to publish in top-tier venues. [Slides] [Poster]
Unconstrained Motion Deblurring for Dual-lens Cameras
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This is the presentation of our work Unconstrained Motion Deblurring for Dual-lens Cameras
in ICCV-2019. [Slides]
Motion Deblurring Methodologies: Going Beyond Conventional Cameras
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This is the presentation of my Ph.D. work done under the guidance of Prof. A. N. Rajagopalan, for which I am awarded a Doctorate from IIT Madras. [Slides]
Complex-Valued AI in Agriculture
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This section contains a series of SPAI Group's expositions (or resources) that focus on Complex-valued AI in Agriculture.
Complex-Valued AI in Chemistry
Published:
This section contains a series of SPAI Group's expositions (or resources) that focus on Complex-valued AI in Chemistry, under the joint guidance of Profs. Anjali Devi J S and Mahesh Mohan M R.
Complex-Valued AI in Finance
Published:
This section contains a series of SPAI Group's expositions (or resources) that focus on Complex-valued AI in Finance.
Understanding Complex-Valued AI
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This section contains a series of SPAI Group's expositions (or resources) that focus on Understanding Complex-valued AI.
Complex-Valued AI in LLMs
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This section contains a series of SPAI Group's expositions (or resources) that focus on Complex-valued AI in LLMs.
Complex-Valued AI in Quantum Computing
Published:
This section contains a series of SPAI Group's expositions (or resources) that focus on Complex-valued AI in Quantum Computing.
Complex-Valued AI in Structural Analysis
Published:
This section contains a series of SPAI Group's expositions (or resources) that focus on Complex-valued AI for Structural Analysis, under the joint guidance of Drs. Sumith Sreedhar and Mahesh Mohan M R.
teaching
Lectured on various topics in Deep Learning
Lab Talk, IIT Madras, EE Dept., 2015
This Lecture Series started at a time when Deep Learning
was taking off, and it aims to explain the (then) emerging field of Deep Learning for the (then) members of Image Processing and Computer Vision Lab and Computational Imaging Lab, headed by Prof. A. N. Rajagopalan and Prof. Kaushik Mitra, respectively.
Here, the first lecture introduces Deep Learning (L1), later, followed by a doubt-clearing session (L1.1). Lecture 2 covers Convolutional Neural Network (L2), and Lecture 3 provides a mathematical interpretation of Deep Learning; O Lost! This series is concluded with Lecture 4, which discusses several Deep Learning approaches for Image Processing. [Slides-L1] [Slides-L1.1] [Slides-L2] [Slides-L3] [Slides-L4]
Prepared Course Contents for a module in Deep Learning Course
Graduate Course, IIT Madras, EE Dept., 2017
When Deep Learning course
was first introduced in IITM, EE Dept. by Prof. A. N. Rajagopalan and Prof. Kaushik Mitra, I (along with Prof. A. N. Rajagopalan) prepared course contents and presentations for Convolutional Neural Network
. [Slides]
Mentored two undergrad students towards the best
Deep Learning course-project
Graduate Course (Deep Learning), IITM, EE Dept., 2017
Here, I proposed a problem statement Efficient Sketch Classification for Resource-constrained platforms
, and designed a research plan for the same. Undergrads Akshit Kumar and Sachin Agrawal joined with me and finally got recognition for the best Deep Learning course-project. Presently, both the students are continuing research in Deep Learning; the former is a Master's student at the University of Michigan, US, and the latter is a Data Scientist at Daimler, Germany. [Slides]
Mentored (with Prof. A. N. Rajagopalan) a project associate towards a funded project.
Funded Project, IITM, EE Dept., 2018
Lots of accidents happen while exiting a vehicle from its side doors, for it is difficult to ensure whether another vehicle(s) are coming from behind and how fast it is. This project attempts to solve this issue; project associate Madumithra Krishnamoorthy was incharge. Together, we employ a side view camera and propose a deployable algorithm using image processing techniques to address this. Later, she joined as a graduate research student in image processing. [Demo]
Lectured on Traditional Image Processing
and Deep Learning based Motion Deblurring
Graduate Course, IIT Madras, EE Dept., 2019
As a part of the Deep Learning Course
offered by Prof. A. N. Rajagopalan and Prof. Kaushik Mitra, the first lecture (L1) aims to equip students from different branches to understand the basics of Image Processing, and the second lecture (L2) provides an overview of the Deep Learning solutions for the problem of Motion Deblurring. [Slides-L1] [Slides-L2]
Lectured on Image Mosaicing
for Image Signal Processing Course
Graduate Course, IIT Madras, EE Dept., 2019
As a part of the Image Signal Processing Course offered by Prof. A. N. Rajagopalan, this lecture aims to make students understand the fundamentals of Image Mosaicing (i.e., the task of stitching images to create a panorama), and equip them to implement the same as an assignment. [Slides]
Mentored (with Prof. A. N. Rajagolalan) a B. Tech project, which led to an ICCV-19 Oral
Undergrad Thesis, IIT Madras, EE Dept., 2019
Here, we identified a problem statement Motion Deblurring for Dual-lens Camera
, and designed a research plan for the same. Undergrad Sharath Girish joined with me for implementation, which finally led to an ICCV-19 Oral paper (4.3% acceptance rate). Later, Sharath Girish joined for Ph.D. under Prof. Rama Chellappa, University of Maryland, US.
Mentored (with Prof. ANR) a B. Tech project, which led to an IEEE Transactions on Image Processing
Undergrad Thesis, IIT Madras, EE Dept., 2020
Here, we identified a problem statement Deep Learning based models for Dual-lens Camera
, and designed a research plan for the same. Undergrad Nithin G K joined with me for implementation, which finally led to a TIP paper. Later, Nithin G. K. joined for Ph.D. under Prof. Vishal Patel, John Hopkins University, US.
Deep Learning Foundations and Applications AI61002
, 2024 Spring, IIT Kharagpur
Teaching, IIT Kharagpur, Centre of Excellence in AI, 2024
Course Overview: Moodle Snapshot
Teaching Distribution: Taught after Mid-semester, Convolutional Neural Network (preceeded by Prof. Somdyuti Paul, followed up with Prof. Jiaul Hoque Paik).
Logistics: In-person Mode, Weekly 3 hrs lecture + 1 hr Tutorial; Credits: 4
Students: 137 (Senior UG/PG students from all departments, selected based on CGPAs)
Student Feedback: IIT-KGP ERP Snapshot
Machine Learning Foundations and Applications AI42001
, 2024 Spring, IIT Kharagpur
Teaching, IIT Kharagpur, Centre of Excellence in AI, 2024
Course Overview: Moodle Snapshot
Teaching Distribution: Taught till Mid-semester, i.e., till Support Vector Machine (followed up with Prof. Somdyuti Paul and Prof. Sudheshna Sarkar).
Logistics: In-person Mode, Weekly 3 hrs lecture + 3 hrs Lab; Credits: 5
Students: 108 (UG/PG students from all departments, selected based on CGPAs)
Student Feedback: IIT-KGP ERP Snapshot
Foundations of Machine Learning AI60203
, 2024 Autumn, IIT Kharagpur
Teaching, IIT Kharagpur, Centre of Excellence in AI, 2024
Course Overview: Moodle Snapshot
Logistics: In-person Mode, Weekly 3 hrs lecture; Four sessions of Lab; Credits: 3
Students: 125 (Core subject for M-Tech in AI + UG/PG students from all departments, selected based on CGPAs)