Pramod Ganapathi
Pramod Ganapathi
Research Assistant Professor

Department of Computer Science
Room 105
Stony Brook, NY 11794-2424

pramod.ganapathi [at]
Mathematical and Algorithmic Puzzles, Algorithms to Discover Algorithms, Algorithm Design Techniques, Parallel Algorithms, Cache-Efficient Algorithms, Big Data, High Performance Computing

Pramod Ganapathi is a Research Assistant Professor in the Department of Computer Science at Stony Brook University (SBU) learning/teaching/researching mathematics/algorithms/puzzles. He has published a book, published 15+ papers in reputed international conferences/journals, been granted a US patent, won two Outstanding Paper Awards, taught 10+ courses in 25+ offerings, and has supervised 90+ master's/bachelor students. Prior to joining SBU, he was an Assistant Professor at the Indian Institute of Technology, Indore. Prior to joining IIT, he was the founder and CEO of an animation-based online higher education startup called "Learning is Beautiful", in India. Prior to founding his startup, he received his Ph.D. in computer science at SBU, specializing in parallel algorithms. His Ph.D. work is entitled "Automatic Discovery of Efficient Divide-and-Conquer Algorithms for Dynamic Programming Problems" and was supervised by Prof. Rezaul A. Chowdhury. Before pursuing Ph.D., he was a Software Engineer at IBM India Software Labs.


Pramod Ganapathi was previously involved in the following projects:

  1. [Autogen (TOPC 2017, PPoPP 2016).] This novel framework takes a serial iterative dynamic programming (DP) algorithm as input and automatically outputs parallel divide-and-conquer DP algorithms. These Autogen-discovered algorithms are theoretically and practically fast and have a lot of other advantages (e.g. they are energy-efficient, cache-oblivious, processor-oblivious, cache-adaptive, and processor-adaptive). 
  2. [Autogen-Wave (SPAA 2017).] This is the sequel to Autogen. This framework can be used to semiautomatically design divide-and-conquer DP algorithms that have more parallelism than Autogen-discovered algorithms using the novel concept of "timing functions".
  3. [Autogen-Fractile (ISC 2019)] This framework is used to design divide-and-conquer DP algorithms that have more parallelism than Autogen-discovered algorithms using multiway divide-and-conquer. These algorithms are architecture-independent in the sense that they can be used to run on GPUs and distributed machines with tiny changes.

Pramod Ganapathi is currently involved in the following project:

  • [Mathematical and Algorithmic Puzzles (Book).] This continuously updated students-contributed free online book presents serious mathematical and algorithmic puzzles that are mostly counterintuitive. The presented puzzles are simultaneously entertaining, challenging, intriguing, and haunting. This book introduces counterintuitive mathematical ideas and revolutionary algorithmic insights from a wide variety of topics.

    This book uses a puzzle-centric approach and multiple ways of attacking the same puzzle are presented which teach the application of elegant problem-solving strategies. Many of these counterintuitive solutions are intriguing to the degree that they shatter our preconceived notions, shake our long-held belief systems, debunk our fundamental intuitions, and finally rob us of sleep and haunt us for a lifetime. This book gives deep and generalized solutions to several puzzles, which you cannot find elsewhere.
Two Outstanding Paper Awards at SPAA 2021, Undergraduate Education Award 2022
Teaching Summary
CSE/ISE 102, CSE 214, CSE 215, CSE 303, CSE 350, CSE 582, CSE 595 (Algorithmic Problem-Solving)