Venkatesh Vinayakarao

VENKATESH VINAYAKARAO

vvtesh@gmail.com

Research

My research interest is in building Search Engines. How does Google work? How to search trillions of documents within microseconds? How to evaluate if Google is better or Bing? Broadly, Information Retrieval is the field of study that investigates these questions. My current focus is on investigating the techniques to search for source code. You will see me discussing Programming Languages, Program Analysis and Software Engineering. More about my research is here.

If you are looking for an answer to an even more fundamental and important question: Why to study information retrieval?, enjoy the video from my students of the 2018 IR offering at IIITS - Mounika, Parkhi and Pragna.

Publications: DBLP Google Scholar

Teaching

Term@CMI: Jan - May 2023: Distributed Computing and Big Data
Term@CMI: Aug - Nov 2022: Information Retrieval
Term@CMI: Jan - May 2022: Distributed Computing and Big Data
Term@CMI: Nov - Dec 2021: RDBMS, SQL and Visualization
Term@CMI: Sep - Dec 2021: Information Retrieval
Term@CMI: Apr - Jul 2021: Distributed Computing and Big Data
Term@CMI: Feb - Mar 2021: RDBMS, SQL and Visualization
Term@CMI: Dec - Jan 2020: Advanced Information Retrieval
Term@CMI: Aug - Nov 2020: Information Retrieval
Term@CMI: Jan - Apr 2020: Big Data and Hadoop
Term@CMI: Jan - Apr 2020: Applied Program Analysis
Term@CMI: Oct - Nov 2019: RDBMS, SQL and Visualization
Term@CMI: Aug - Sep 2019: Information Retrieval
Term@CMI: Mar - Apr 2019: Program Analysis
Term@IIITS: Aug - Dec 2018: Information Retrieval
Term@IIITS: Aug - Dec 2018: Computer Programming

Talks

The Mathematics behind Search Engines   Mathematical models play a significant role in designing elegant products. Have you ever wondered how these search engines could index trillions of documents and yet respond to queries within seconds? How does the search engine understand queries? How does the indexing work? Similarly, we explore some ranking techniques too. In this talk, we discuss the vector space models and probabilistic retrieval models from scratch. I will cover the necessary preliminaries and explain the way various models lend elegance and efficiency. Towards the end, we shall discuss current trends in web search research. Tech Talk (delivered live online) for Qualcomm, 4th August, 2021. Slides

Knowledge Graphs - Going Beyond Data!   Digital enablement is the new mantra. Towards this purpose, we have come a long way leveraging the power of data. A key step in this direction is the mining and representation of knowledge. Various domains ranging from clinical healthcare to fintech, find a need to capture and use knowledge. In this talk, we discuss how knowledge graphs serve this purpose. Specifically, we focus on knowledge graph construction and discuss a case in entity retrieval. Tech Talk (delivered live online) for Qualcomm, 24th Jun, 2021. Slides

Source Code Search - An Overview   With the growing volume of information and information needs, technology support to retrieve information has become indispensable. We focus on Information Retrieval (IR) of a specific type of content, namely, source code. Source code retrieval has attracted the attention of several researchers in the last decade. This research has resulted in several useful applications such as code completion, example search, plagiarism detection, automated feedback for programming assignments, feature location, and bug localization. We discuss literature from the software engineering (SE) domain to understand the role of IR in SE, specifically where source code is involved, either as content or query. While this talk gives an overview of source code search, we hope it also inspires you to explore topics such as program analysis, software engineering and advanced information retrieval for future studies. Guest Lecture at CS317- Information Retrieval, National University of Computer & Emerging Sciences, Karachi Campus, 08th Apr, 2021. Slides

More talks are listed here.

Tweets by venkvinr

My Recommendations

Here are a list of books I really enjoyed reading:

How Life Imitates Chess: Although there is no game without a king, the most powerful piece on the board is the queen, and her job is to protect the king. In life too, you might be the most important person. But, unless the most powerful protects you, you might not exist. Moreover, if you are strong enough, protect the weak. This book comes with many such comparisons between life and chess. I found a purpose of living after reading this book. Am sure this book will remain in my top 10 list forever.
Deep Work: Rules for Focused Success in a Distracted World: Only when you are deep into some activity, do you really start seeing the true beauty. The importance of deep work is being explained by no other than an MIT PhD! A great read. The second half on social media is a little overstretched, I feel. Hence, this book misses the top spot.
The Elements of Style: This should be in the private library of every student. I have a detailed blog on why you should read this book.
What the Best College Students Do: This book was first introduced to me by Prof. Pankaj Jalote when I took his class at IIT Delhi in 2015. It was my dream to study at IIT Madras. However, when that did not happen, I started collecting years of notes on the qualities I missed. Surprisingly, this author lists every one of them! If only, I had read this during my school days.
What the Best College Teachers Do: I am a teacher, at last! But, am I a good one? This time around, I have the right book with me. Many teachers have given up on the belief that teaching is important. Another key to successful teaching is the conviction that students can learn! We are here to bring a difference.

Some great readings from the technical side:

Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan: Extremely well written! A very expensive book though. I was fortunate to get a used version of this book from US. I treasure it!
Probability and Computing: Randomized Algorithms and Probabilistic Analysis: I was first introduced to this book in a Randomized Algorithms course. Later, I found it to be the best text for probability, both introductory and advanced. If you are interested in probability, you should own this.
Pattern Recognition and Machine Learning: Another expensive, yet amazing book. I had the privilege of having lunch with Bishop, the author of this book. What a day!
For programmers and data scientists: Introducing Data Science (through Python), Design Patterns

I too co-authored one book! See HTML for Smart Kids.

Beautiful Computer Science
When I get some free time, I solve beautiful problems related to computer science. Computer science is probably a misnomer. Sometimes, the problems belong to areas such as mathematics as well. Here are some pieces of my work.

Chess

If I am not doing Information Retrieval, I am usually playing or studying chess. Here are some of my videos on my favorite "Colle System".




More videos are on my youtube channel.

Bio
Venkatesh Vinayakarao is a Principal Engineer at HERE Solutions (www.here.com). He was a lecturer at the Chennai Mathematical Institute till September 2021. Prior to this, he was employed as an Assistant Professor at the Department of Computer Science and Engineering, IIIT Sri City. He completed his Phd in 2018 at the Indraprastha Institute of Information Technology (IIIT) Delhi. Prior to his PhD, he gained practical experience in building search engines by working with the Microsoft's Search Technologies Group (Bing Team). He has also served technical roles at Yahoo! and Nokia. He received an MS degree in Information Technology with specialization in Software Engineering from Carnegie Mellon University in 2003. His research interests are in building search engines, especially in handling source code content. His research work is published in reputed venues such as the Web Search and Data Mining (WSDM) conference.

Treasured Moments

If you are not having fun, you are not the best teacher, researcher or an engineer, you can be!
(c) 2022.