2017-09-19 15:00:00 2017-09-19 16:00:00 America/New_York Research Seminar Series - Aniket Kate Assistant Professor, Department of Computer Science, Purdue University WTHR 320

September 19, 2017

Research Seminar Series - Aniket Kate

Event Date: September 19, 2017
Hosted By: School of Industrial Engineering
Time: 2:00 - 3:00 PM
Location: WTHR 320
Contact Name: Erin Gough
Contact Phone: 765-496-0606
Contact Email: egough@purdue.edu
Open To: All
Priority: No
School or Program: Industrial Engineering
College Calendar: Show
Assistant Professor, Department of Computer Science, Purdue University

"Blockchains: A Technical Perspective on the Future of Decentralization"


In the eight years since blockchains were first proposed in the form of Bitcoin, their use as verifiable distributed ledgers for financial and supply-chain transactions has become widespread. As Bitcoin and other blockchain systems such as Ethereum and Hyperledger continue to mature, it is becoming very likely that blockchains as a means to facilitate verifiable assets transfers are here to stay. In fact, the disruptive potential of blockchains is now widely claimed to be equal to that of the Internet.

This talk will take a bird's eye view of the blockchain evolution to identify the ground rules and assumptions of this transparency enhancing technology. We will also shade some light on promising future research directions as well as applications of blockchains in the science, the engineering and beyond. 


Photo of Aniket Kate

Dr. Aniket Kate is an Assistant Professor in the computer science department at Purdue University. Before joining Purdue in 2015, he was a faculty member and an independent research group leader at Saarland University in Germany, where he was heading the Cryptographic Systems Research Group. He completed his postdoctoral fellowship at Max Planck Institute for Software Systems (MPI-SWS), Germany in 2012, and received his PhD from the University of Waterloo, Canada in 2010. His research integrates applied cryptography, distributed computing and statistics towards designing, implementing and analyzing privacy and transparency enhancing technologies.