# Kishori Konwar

> Kishori Konwar is a data scientist and distributed-systems researcher known for work on fault-tolerant storage, computational biology, and blockchain infrastructure as a co-founder of Optimum.

- Canonical URL: https://iq.wiki/wiki/kishori-konwar
- Categories: People in crypto
- Tags: Founder, Researcher
- Created: 2026-11-02T12:50:38.914Z
- Last updated: 2026-11-02T12:50:38.914Z
- Source: IQ.wiki — the world's largest blockchain and crypto encyclopedia (https://iq.wiki)

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**Kishori Konwar** is the co-founder of [Optimum](https://iq.wiki/wiki/optimum) with [Muriel Médard](https://iq.wiki/wiki/muriel-medard) and [Kent Lin](https://iq.wiki/wiki/kent-lin). Konwar’s distinctive work at the company applies random linear network coding (RLNC) to [blockchain](https://iq.wiki/wiki/blockchain) data propagation. He served as Optimum’s chief technology officer from April 2024 to May 2026, chief scientific officer from May to October 2026, and adviser from October 2026.[\[2\]](#cite-id-9hxe25wo9p)​[\[1\]](#cite-id-c3ykg3z576)​

## Education

Konwar earned a PhD in distributed computing and an MS in statistics and mathematics from the University of Connecticut, with both degrees listed for 2000–2006. He received an MTech in computer science from the Indian Statistical Institute in Kolkata in 1998–2000 and an MSc in physics from the Indian Institute of Technology Kanpur.[[1]](#cite-id-c3ykg3z576)[[3]](#cite-id-pw7xzlwrwe)
## Career

### Early Career and Computational Biology

From December 2006 to September 2008, Konwar worked in New York as a core market risk strategist and quantitative developer at Goldman Sachs, contributing to financial-risk calculations for firmwide portfolios. He then worked at KPMG US as a derivatives valuation specialist in financial risk management from November 2008 to August 2010.[[1]](#cite-id-c3ykg3z576)

From August 2010 to March 2015, Konwar was a postdoctoral researcher at the University of British Columbia, where he conducted research in computational biology and bioinformatics. His work in these fields included research on microbial communities in low-oxygen ocean regions, a multimodal cell census and atlas of the mammalian primary motor cortex, and a microfluidic device for analyzing single microbes and microbial communities.[[1]](#cite-id-c3ykg3z576)[[3]](#cite-id-pw7xzlwrwe)

### Distributed Computing Research

Konwar joined the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory (CSAIL) as a distributed-computing researcher in March 2015. His work there, continuing through September 2018, addressed distributed transactions, fault-tolerant storage, erasure coding, and the design of atomic data objects. He later served as a visiting scientist at MIT’s Research Laboratory of Electronics from January 2019 to December 2020, with work that included distributed key-value storage.[[1]](#cite-id-c3ykg3z576)[[3]](#cite-id-pw7xzlwrwe)

From September 2018 to January 2022, Konwar was a data scientist at the Broad Institute of MIT and Harvard. He designed and implemented cloud-based pipelines for genomic-data processing and analyzed data using machine-learning and statistical methods. He subsequently worked as a research data scientist at Meta from January 2022 to January 2023.[[1]](#cite-id-c3ykg3z576)

### Optimum

[Optimum](https://iq.wiki/wiki/optimum) was founded in 2024 to apply RLNC to [blockchain](https://iq.wiki/wiki/blockchain) data propagation. Konwar co-founded the company with [Muriel Médard](https://iq.wiki/wiki/muriel-medard) and [Kent Lin](https://iq.wiki/wiki/kent-lin), bringing experience in distributed systems, coding theory, and artificial intelligence. He served as chief technology officer from April 2024 to May 2026, then as chief scientific officer from May to October 2026, and became an adviser in October 2026.[[2]](#cite-id-9hxe25wo9p)[[1]](#cite-id-c3ykg3z576)[[3]](#cite-id-pw7xzlwrwe)

In April 2025, [Optimum](https://iq.wiki/wiki/optimum) announced an $11 million seed round led by 1kx, with participation from [Robot Ventures](https://iq.wiki/wiki/robot-ventures), Finality Capital, Spartan, [CMT Digital](https://iq.wiki/wiki/cmt-digital), SNZ, Triton Capital, Big Brain, CMS, LongHash, NGC, Animoca, GSR, Caladan, Reforge, and others. The company also launched a private [testnet](https://iq.wiki/wiki/testnet) with 40 [validator](https://iq.wiki/wiki/validator) partners; it reported that more than $24 billion in ether stake was connected. Named partners included Everstake, [Kiln](https://iq.wiki/wiki/kiln), Bunker, P2P, InfStones, Luganodes, [Alchemy](https://iq.wiki/wiki/alchemy), Blockdaemon, and Nethermind.[[2]](#cite-id-9hxe25wo9p)

Optimum also launched mump2p, its first data-propagation protocol, on [Ethereum](https://iq.wiki/wiki/ethereum) [mainnet](https://iq.wiki/wiki/mainnet) with more than 20 [validators](https://iq.wiki/wiki/validator) and over 1.4 million staked ether. The company’s work on [blockchain](https://iq.wiki/wiki/blockchain) propagation builds on Konwar’s research into distributed systems and coding methods.[[2]](#cite-id-9hxe25wo9p)

## Research

### Distributed Storage and Fault Tolerance

At MIT, Konwar co-authored research on storing and retrieving data reliably across distributed systems, including systems that use erasure codes to reduce the amount of data that must be stored or communicated. In “A Layered Architecture for Erasure-Coded Consistent Distributed Storage,” he and his collaborators proposed Layered Data Storage, a two-layer system in which clients access nearby edge servers and those servers interact with a persistent back end. The design supports multiple readers and writers in an asynchronous message-passing system, using regenerating codes in the back end to reduce storage and read-communication costs. The paper established liveness and atomicity under stated crash-failure limits for the edge and back-end servers.[\[3\]](#cite-id-pw7xzlwrwe)​

In “Storage-Optimized Data-Atomic Algorithms for Handling Erasures and Errors in Distributed Storage Systems,” Konwar, N. Prakash, and Nancy Lynch presented SODA, a multi-writer, multi-reader atomic-memory algorithm based on maximum-distance-separable codes. SODA uses an (\[n, n-f]) code to tolerate (f) crashes among (n) servers, with total storage cost (n/(n-f)). The paper also introduced SODA\_err, which handles both failed servers and error-prone coded elements using a code sized for those failures. The authors compared SODA’s lower storage costs with CASGC, noting that SODA has higher communication costs.[\[3\]](#cite-id-pw7xzlwrwe)​

Konwar and collaborators also developed RADON, a family of erasure-code-based algorithms for repairing crashed [nodes](https://iq.wiki/wiki/node) through message exchanges with active [nodes](https://iq.wiki/wiki/node). RADON\_C provides liveness and atomicity under a network-stability condition that limits how many nodes are crashed or being repaired during a broadcast. RADON\_R offers a replication-based alternative under the same condition. A stronger stability condition supports algorithms that preserve atomicity at the cost of an additional phase in reads and writes.[\[3\]](#cite-id-pw7xzlwrwe)​

His related work included ARES, an adaptive and reconfigurable erasure-coded atomic-storage system; Fast Lean Erasure-Coded Atomic Memory Object; and research on erasure-coded storage architectures for edge computing. The research also produced two listed US patents: “Storage-optimized data-atomic systems and techniques for handling erasures and errors in distributed storage systems” and “Layered Distributed Storage System and Techniques for Edge Computing Systems.”[\[1\]](#cite-id-c3ykg3z576)​

### Transactions and Distributed Ledgers

In “SNOW Revisited: Understanding When Ideal READ Transactions Are Possible,” Konwar and co-authors examined when read-only transactions can combine low latency with strong consistency guarantees. They proved that the desired SNOW properties are impossible with three or more clients. In a multi-writer, single-reader setting, they showed the properties can be achieved when clients can communicate with one another, but not when that communication is disallowed. The paper also corrected an earlier claim about Eiger and introduced two algorithms that provide strong guarantees with bounded latency.[\[3\]](#cite-id-pw7xzlwrwe)​

In “Formalizing and Implementing Distributed Ledger Objects,” Konwar and collaborators defined a distributed ledger object as a sequence of records governed by specified operations and properties. They formalized atomic, sequential, and eventual consistency, described implementations over asynchronous systems with crash-prone processes using atomic broadcast, and introduced a validated ledger in which each record must satisfy a validation rule.[\[3\]](#cite-id-pw7xzlwrwe)​

### Coding and Blockchain Data Propagation

Konwar’s later research connected coding theory with [blockchain](https://iq.wiki/wiki/blockchain) data distribution. “From Indexing to Coding: A New [Paradigm](https://iq.wiki/wiki/paradigm) for Data Availability Sampling,” published in 2025 with Moritz Grundei, Vipindev Adat, Vasudevan, and [Muriel Médard](https://iq.wiki/wiki/muriel-medard), proposed committing to uncoded data while using coding during sampling. Rather than sampling symbols from a fixed-rate, pre-committed erasure code, the approach uses on-the-fly coding to make samples more expressive. The authors described a protocol using RLNC and argued that concrete implementations could offer assurances multiple orders of magnitude stronger than established schemes based on Reed–Solomon or low-density parity-check codes.[\[3\]](#cite-id-pw7xzlwrwe)​

A 2025 paper titled “OPTIMUMP2P” proposed a [peer-to-peer](https://iq.wiki/wiki/peer-to-peer-trading-p2p) gossip algorithm using RLNC to accelerate information dissemination while maintaining reliable delivery when malicious actors corrupt transmitted data. Its authors reported simulation and real-world evaluations showing performance gains over libp2p’s Gossipsub protocol, and discussed earlier [Ethereum Foundation](https://iq.wiki/wiki/ethereum-foundation-ef) research on RLNC for [block](https://iq.wiki/wiki/block) propagation.\[3]

Two 2026 arXiv papers further addressed [Optimum](https://iq.wiki/wiki/optimum)’s network design. “OPTIMUM-DERAM: Highly Consistent, Scalable, and Secure Multi-Object Memory using RLNC” and “[Optimum](https://iq.wiki/wiki/optimum) Peer-Turbo: A Scalable and Efficient Solution for P2P Broadcasting” list Konwar among their co-authors.[\[1\]](#cite-id-c3ykg3z576)​

### Computational Biology and Other Research

Konwar’s publication record also includes research in genomics, phylogenetics, bioinformatics, and microbial ecology. “Microbial ecology of expanding oxygen minimum zones,” co-authored with Jody J. Wright and Steven Hallam, reviewed microbial communities in ocean regions with low oxygen. Other listed work includes “MetaPathways: a modular pipeline for constructing pathway/genome databases from environmental sequence information” and “A multimodal cell census and atlas of the mammalian primary motor cortex,” the latter produced by the BRAIN Initiative Cell Census Network and other authors.[\[1\]](#cite-id-c3ykg3z576)​[\[3\]](#cite-id-pw7xzlwrwe)​

His earlier research included “Approximation Algorithms for Minimum PCR Primer Set Selection with Amplification Length and Uniqueness Constraints.” The paper studied how to minimize the number of polymerase chain reaction (PCR) primers needed to amplify selected single-nucleotide-polymorphism loci. It presented a logarithmic-approximation greedy algorithm under an amplification-length bound and a randomized-rounding approach for unique amplification, with tests on random cases and cases derived from genomic databases.[\[3\]](#cite-id-pw7xzlwrwe)​

His research has also addressed 5G communications. In “5G NR CA-Polar Maximum Likelihood Decoding by GRAND,” Konwar and co-authors studied GRAND maximum-likelihood decoding for 5G New Radio control-channel CA-Polar codes. The paper reported simulation results indicating that GRAND, including a simple soft-detection variant, could be used to decode those codes.[\[3\]](#cite-id-pw7xzlwrwe)​

Konwar’s listed research areas include distributed systems and fault tolerance, parallel computing, advanced database systems, genomics, bioinformatics, and genomic networks. His publication record lists the National Science Foundation, the Air Force Office of Scientific Research, and the U.S. Department of Energy among funders of his work.[\[1\]](#cite-id-c3ykg3z576)​