Talks §
Introduction to Quantum Computing
Edunatuic Workshop, IIT Delhi, 2025
The talk was jointly prepared (and presented) with Tharrmashastha SAPV. Our slides.
Modern Algorithmic Design Primitives in Quantum Computing
Symposium on Quantum Computing and Artificial Intelligence, 2025
This was an invited talk as part of the Young Scientists Session at the Symposium on Quantum Computing and Artificial Intelligence. My slides.
Block Encodings and LCUs
Quantum Computing Bootcamp, CMI, 2023
These lectures were given at the Chennai Mathematical Institute as part of the 2024 Quantum Computing Semester.
Youtube videos: Lecture 1, Lecture 2.
Generating Hard Instances for the Short Basis problem
IIITD Theory Reading Group, 2023
My notes and a short blog post on the Ajtai 1996 paper. For more details see the papers by Micciancio-Regev, and Alwen-Peikert.
Oracle Separation of BQP and PH
Complexity Theory Course Presentation, 2020
See the (original paper), and blog posts by Boaz Barak, Scott Aaronson, Lance Fortnow, and a project in Li Yang Tan's course.
My Slides.
The HHL algorithm
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Quantum Computing Bootcamp, CMI, 2023
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Gong Show Talk, IIAS Winter School, 2019
My HHL notes are part of the course we designed for the “Teach Me Quantum” category of the 2019-20 IBMQ awards (2019-2020), in which we won the second place prize. See the following papers for more details: HHL '09, Ambainis '10, WZP '17, and CKS '17.
Youtube Video: CMI lecture.
My Notes and
Slides.
Shallow Quantum Circuits
Evariste Invited Talk, 2020
This was a talk I gave for Evariste – IIITD’s Theory and Math club.
We discussed the motivations behind research on
Shallow Quantum Circuits and some
interesting
separation results (noisy as well as noiseless)
between SQC’s and various classical circuits.
My slides and video (internal to IIITD). See the following papers for more details: Bravyi-Gosset-Koenig'18, Watts-Kothari-Schaeffer-Tal'19 , Le Gall'19 , and Bravyi-Gosset-Koenig-Tomamichel'19.
Quantum Machine Learning
Faculty Development Program, 2020
This was an invited talk at the Faculty Development Program at the JNTU, Anantapuram, India. The talk focuses on giving an overview of Quantum Optimization and Quantum Machine Learning. My Slides.
§ See CV for full list.
Resources
Courses and Books (TCS)
Complexity Theory
- Circuit Complexity by William Hoza.
- Advanced Complexity Theory by Hamed Hatami.
- Computational Complexity by Manoj M. Prabhakaran.
- Communication Complexity by Mark Bun .
Boolean Functions
- Analysis of Boolean Functions by Ryan O'Donnell.
- Analysis of Boolean Functions by Ramprasad Saptarishi
- Playlist on Analysis of Boolean Functions at the Simons Institute.
Others
- Randomized Algorithms by James Aspnes.
- High Dimensional Expanders by Irit Dinur (Notes and Videos).
- High Dimensional Expanders by Gil Kalai and Alex Lubotzky (Notes and Videos).
- Computational Social Choice by Rohit Vaish .
- Analytical Toolkit in Computer Science by Hemanta K. Maji.
- A Theorist's toolkit by Ryan O'Donnell.
- Data Stream Algorithms by Amit Chakraborti.
- Theory of Metric Embeddings by Harald Räcke.
- Lecture notes on metric embeddings by Jiří Matoušek.
- Algorithms book by Jeff Erickson .
- Introduction to Theoretical Computer Science by Boaz Barak.
- Lecture Notes by Tim Roughgarden.
- Probabilistic Method in Combinatorics by Yufei Zhao .
Free Courses and Books (Quantum)
- Introduction to Quantum Computing by Sevag Gharibian.
- Introduction to Quantum Computing by Nathan Wiebe.
- Introduction to Quantum Information Theory by Mark M. Wilde.
- Quantum Complexity Theory by Scott Aaronson.
- Quantum Complexity Theory by Sevag Gharibian.
- Quantum Computing lecture notes by Ronald de Wolf.
- Quantum algorithms: A survey of applications and end-to-end complexities.
- Quantum Walks and Search Algorithms by Renato Portugal.
Free Courses and Books (Learning Theory and Optimization)
- Overview of Statistical Learning Theory: Part 1 and Part 2 by Nati Srebro.
- Sample Complexity Part 1 and Part 2: Eli Upfal.
- Machine Learning by Ronald Rivest and Mona Singh.
- Machine Learning Theory by Akshay Krishnamurthy.
- Foundations of Modern Machine Learning by Nika Haghtalab.
- Learning Theory by Ambuj Tewari.
- Machine Learning Theory by Maria Florina Balcan.
- Understanding ML by Shai Shalev-Shwartz and Shai Ben-David.
- Convex Optimization by Sébastien Bubeck.
- Optimization Algorithms by Constantine Caramanis. .
- Mathematics of Machine Learning 2019 Summer School .
- Distribution Testing by Clément Canonne.
- Applied Information Theory by Ziv Goldfeld.
Free Courses and Books (Maths)
- Introduction to Measure Theory by Claudio Landim.
- Concentration inequalities: A nonasymptotic theory of independence by Stephane Boucheron, Gabour Lugosi, and Pascal Massart.
- Concentration of Measure for the Analysis of Randomised Algorithms by Devdatt P. Dubhashi and Alessandro Panconesi.
- Introduction to Group Theory by Richard E Borcherds.
- Introduction to Ring Theory by Elliot Nicholson.
- Introduction to Field Theory by Elliot Nicholson.
- Martingale Theory by Artem Sapozhnikov.
Expository Resources (TCS)
- Computational Complexity (Blog) by Lance Fortnow and Bill Gasarch.
- Windows on Theory (Blog) by Boaz Barak.
- Combinatorics and more (Blog) by Gil Kalai.
- Thoughts by Manu (Blog) by Emanuel Viola.
- What's New? (Blog) by Terrence Tao.
- An introductory survey on expanders by Avi Wigderson. [Video]
- Taxonomy of Square Matrices.
- Metric Embeddings (FOCS22 workshop) .
- Five Proofs of Chernoff's Bound with Applications by Wolfgang Mulzer.
- Edmond's Blossom Algorithm by James S. Plank .
- Tossing a biased coin by Michael Mitzenmacher .
- Determining the direction of a coin's bias by William Hoza.
- Part 1 and Part 2 on Multivariate Gaussians by Chuong B. Do .
- Understanding Ladner's Theorem by Sanjoy Das.
- Reservoir Sampling: Florian Hartmann, Stephen N. Pallone .
- Morris' algorithm by Gregory Gundersen.
- The Unique Games Conjecture by Scott Aaronson.
- Hastad's switching lemma by Victor Lecomte.
- Plancherel's trick by Victor Lecomte.
Expository Resources (Quantum)
- Shtetl Optimized (Blog) by Scott Aaronson. (Note: In his blog, Scott talks about his politics and worldviews, along with technical content.)
- The General Adversary Bound: A Survey by Lily Li and Morgan Shirley.
- HSP - Review and Open Problems by Chris Lomont.
- A Survey on HSP by Frédéric Wang.
- Post Quantum Cryptography by Chris Peikert.
- Quantum algorithms: A survey of applications and end-to-end complexities by Dalzell et al.
- Quantum linear systems algorithms: a primer by Dervovic et al.
- Youtube playlist on Density Matrix and Mixed States by Diego Emilio .
- Maximally mixed vs Maximally Entangled on StackExchange.
- QAOA literature survey by Kunal Marwaha .
- A list of Open and Solved quantum problems by IQOQI Vienna .
Expository Resources (Learning Theory)
- Francis Bach's blog.
- Understanding Optimal Transport by Alex Williams.
- Website on Algorithms With Predictions .
- Diffusion Models : Calvin Luo, Lilian Weng, CVPR 2022 Tutorial .
- Generative Flows : Lilian Weng, Yoshua Bengio.
- Learning Theory Notes by Gene Li.
- Dijkstra's in Disguise by Eric Jang.
Expository Resources (others)
- Probability Cheatsheet by William Chen and Joe Blitzstein.
- Inequalities Cheatsheet by László Kozma.
- Notes and visualizations on Linear Algebra by Kenji Hiranabe.
- The We(a)ekly Quiz by Clement Cannone .
- Expository Papers on Algebra and Number Theory by Keith Conrad.
Curated Articles (On Research)
- Advice on giving talks by Anupam Gupta.
- The Value of Science by Richard Feynman .
- The Limits of Quantum Computers by Scott Aaronson.
- Advice to PhD students by Oded Goldreich.
- 3 qualities of successful PhD students by Matt Might.
- Writing a good introduction by Jim Kurose.
- How to write a ML paper by Jakob Foerster.
- Writing Technical Articles by Henning Schulzrinne .
- The importance of stupidity in scientific research by Martin A. Schwartz .
- Presenting a Technical Talk by Nick Feamster.
- Top 10 ways to Lose your Audience .
- Graduate Student Guide by Lance Fortnow and Bill Gasarch.
Curated Articles (Others)
- Andrei Nikolaevich Kolmogorov by K R Parthasarathy .
- Meeting a Gorilla by Douglas Adams and Mark Carwardine .