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Dr Karthik Inbasekar

Dr Karthik Inbasekar is a Principal Researcher at Ingonyama. His primary research interests are in the protocol level of Zero Knowledge proofs, Elliptic curve cryptography and Homomorphic encryption. Karthik comes with a background in Physics, holding a PhD in theoretical Physics with 8 years of post doctoral research experience and has published in journals such as Journal of High Energy Physics, Physical Review D and Physical Review Letters.

Blogs by 

Dr Karthik Inbasekar

Marlin & Me: A Deep Dive into the Heart of the Marlin ZK Protocol

In this article, we dive deep into the heart of the Marlin protocol introduced in [1]. The goal of the document is to provide intuition in the various technical steps involved in the protocol with necessary explanation wherever possible. We will assume some familiarity with protocols such as Groth16

Bridging the Multichain Universe with Zero Knowledge Proofs

Bridges are communication protocols that facilitate the transfer of information such as messages, funds or other data between blockchains. While useful, building bridges is a risky business. Some of the most expensive hacks in blockchain history have targeted bridges alone.

Systemization of Knowledge: ZK-Friendly Hash Functions

In this article we present a systematization of knowledge (SoK) on the usage of hash functions in Zero Knowledge Proofs (ZKP’s). Since ZKP’s operate on finite fields, traditional time-tested hash functions like SHA256 are unsuitable due to overhead in proving and verification of large number of bitwise operations.

Application of Graph Methods for Efficient Quotient Polynomial Evaluation in Halo2

In this paper we present our research on applications of graph methods to parallelize the quotient polynomial in the Halo2 Zero-Knowledge Proof (ZKP) system.

Sparkworks - Native Hardware Acceleration in Arkworks

We demonstrate integration of our cloud-ZK FPGA acceleration by running Arkworks Groth16 over the BN254 curve This work can easily be extended to support other primitives in the Arkworks framework and various System/HW configurations

Sumcheck 201

In this chapter, we explore sum-check protocols from the point of view of parallelizable computation in devices such as GPUs. We explore algorithmic modifications to the sum-check protocol, for products of Multi-Linear Extensions (MLE) to improve parallel compute and address memory bottlenecks.

Sumcheck 201, Chapter 2: Checkfold - Folding Sumcheck Instances

In this chapter, we construct a knowledge-reduction argument for the sumcheck protocol that reduces the proving of a large-sized sum-check to the proving of a folded small-sized sum-check.