Presentation, Virtual,
As a part of the end-semester (finals) for EE4140: Digital Communication Systems, I did an extensive review of existing blind algorithms (Godard, Sato, CMA, APA-CM, RCA, MMA, Stop-and-Go) and simulated them for a variety of channel models and samples generated from a QPSK/16-QAM constellation.
Talk, CSD159, IIT Madras, Chennai, India
Rushill and I gave an hour long critical talk on Price of Anarchy, as a part of our course project for EE6418: Game Theory for Engineering Applications.
Poster, ESB Foyer Area, IIT Madras, Chennai, India
Ruban and I got a chance to present a poster titled: ‘Signal Decomposition via Quadratic-Separable Optimization’.
Presentation, ESB 213B, IIT Madras, Chennai, India
Compressed sensing is a classical signal processing technique of reconstructing a sparse signal (’compressible’ signal) from as minimum number of measurements as possible. Let’s now consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear “incoherent” measurements, in real-time. The signals are sparse in some transform domain referred to as the sparsity basis. For a single spatial signal,we can apply Compressed sensing (CS) to solve the problem.
Presentation, Virtual,
I got a chance to present my work from summer at the IEEE HPEC 2023 conference, here are the slides.
Tutorial, ESB 350, IIT Madras, Chennai, India
My first time ever, conducting a tutorial session for a batch of 53 EE undergraduate students on Multirate Signal Processing. It was an amazing exprience, excited to do this more often.
EE Research Club, ESB 127, Chennai, India
Thank you for attending the session and for your overwhelming response! Here is the link to the presentation/slides used in the session.
Presentation, Michelson Hall, USC, Los Angeles, USA
This was an amazing opportunity for me to present my work from Summer 2023, under the guidance of Prof. Viktor Prasanna and my PhD guide Pengmiao Zhang on ML-based Memory Access Prediction.
Presentation, CRC 301, NPTEL Studio, Chennai, India
In many practical scenarios in communications and data processing, we work with large volumes of data. A single minute of an uncompressed HD video can be over 1 GB. How do we then fit a two-hour film on a 25 GB Blu-ray disc? So, there is a need for robust, lossless data compression techniques. Most compression techniques (like Huffman encoding) although optimal, need prior knowledge of the source distribution.
Contest, CRC101, IIT Madras, Chennai, India
Extremely glad to have hosted IITM’s first ever Integration Bee alongside Haricharan. You can find the contents from Integration Bee here.
EE Research Club, Inaugural Session, ESB 127, Chennai, India
The EE Research Club, a newly formed entity under the EEA, is excited to invite you to its inaugural session, featuring a talk by Prof. David Koilpillai on his reflections on research, and a brief overview of various research areas in our department.
EA, IITM, Chopra Farms, New Delhi, India
Selected from IITM to attend this 3-day workshop on AI Alignment Research from 28 August, 2022 to 30 August, 2022.
Seminar on History of Electrical Engineering, EE5004, Virtual
My talk on Bell Labs as a part of the final presentation for EE5004: Seminar on History of Electrical Engineering course. Bell Labs has been shaping the future with innovations over the past 90 years. Be it the first ever transistor, the first silicon solar cell, the first ever laser or the first communication satellite, involved in nearly every technological milestone in the last nine decades. A total of 9 Nobel Prizes and 5 Turing Prizes awarded to the work here. So how exactly did Bell Labs create the future that we live in today?
Shaastra Tutorial, Shaastra, IIT Madras, Chennai, India
Everything from the Introduction to AI and RL Workshop conducted during Shaastra 2022, on 15th and 16th January, 2022 at IIT Madras can be found here.
AI/ML Tutorial, Testing Institute of America 2014 Annual Conference, Chennai, India
Have you ever wondered how big businesses forecast their sales? Or maybe try to predict times when they need to stock up on their inventory? In order to help you build this reference code for most data science pipelines and develop your thought process we bring to you a session where we walk you through building this reference code for the Predict Future Sales contest on Kaggle. Here is an opportunity for you to explore the problem, learn the different ways to approach it and to get yourself your base reference code for building complete pipelines.
Talk, Amazon Academy, Virtual
Isn’t it your dream to land into an IIT? If it is, learn how to get there in this masterclass by Abhiram Rao, IIT Madras, JEE Advanced 2020, AIR 565.
Tutorial, Summer School, Centre of Innovation @ IITM, Chennai, India