16th International Conference on Distributed Computing and Internet Technology
9th – 12th January 2020
Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India

Invited Speakers


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Hrushikesha Mohanty
Professor of Computer Science at University of Hyderabad now on lien at KIIT DU.

Talk Title:
Trust: Arthropomorphic Algorithmic

Bud Mishra
Professor of Computing at Courant Institute, New York University

Talk Title:
Prospero’s Books: A Distributed Architecture for AI.

Nobuko Yoshida
Professor of Computing at Imperial College, London

Talk Title:
A very gentle introduction to multi-party session types

Adegboyega Ojo
Senior Research Fellow and the E-Government Group Leader (under the Linked Data Strand) at the Insight Centre for Data Analytics, National University of Ireland, Galway.

Talk Title:
Constructing knowledge graphs from data catalogues

Y. N. Srikant
Professor at IISc Bangalore

Talk Title:
Distributed Graph Analytics

Dale Miller
Professor, INRIA Saclay-Paris

Talk Title:
A distributed and trusted web of formal proofs

Hrushikesha Mohanty
Professor of Computer Science at University of Hyderabad now on lien at KIIT DU.

Talk Title:
Trust: Arthropomorphic Algorithmic

Abstract

Computer Science often emulates humanlike behaviours including intelligence that has taken to storms in every other domain where human deals with. A computing system with a defined role and goal is called an agent with humanlike capability for decision making in dynamic and complex real world it is situated in. Largely this aspect of a computing unit needs ability to learn, act and forecast. Broadly the study in Artificial Intelligence (AI) also deals with such aspects. Researchers of both the schools of computing viz. Intelligent Agents and AI systems, propose several algorithms to emulate human like behaviours. These algorithms here, are labelled as anthropomorphic algorithms. In particular, here our discussion is focussed on trust. The idea of trust as conceptualised, computed and applied in different domains, is discussed. Further, it points out the dimensions that need to be looked at, in order to endow computing systems with trust as a humanitics.

Y. N. Srikant
Professor at IISc Bangalore

Talk Title:
Distributed Graph Analytics

Abstract

Graph Analytics is important in different domains: social networks, computer networks, and computational biology to name a few. This paper describes the challenges involved in programming the underlying graph algorithms for graph analytics for distributed systems with CPU, GPU, and multi-GPU machines and how to deal with them. It emphasizes how language abstractions and good compilation can ease programming graph analytics on such platforms without sacrificing implementation efficiency.

Dale Miller
Professor, INRIA Saclay-Paris

Talk Title:
A distributed and trusted web of formal proofs

Abstract

Most computer checked proofs are tied to the particular technology of a prover’s software. While sharing results between proof assistants is a recognized and desirable goal, the current organization of theorem proving tools makes such sharing an exception instead of the rule. In this talk, I argue that we need to turn the current architecture of proof assistants and formal proofs inside-out. That is, instead of having a few mature theorem provers include within them their formally checked theorems and proofs, I propose that proof assistants should sit on the edge of a web of formal proofs and that proof assistant should be exporting their proofs so that they can exist independently of any theorem prover. While it is necessary to maintain the dependencies between definitions, theories, and theorems, no explicit library structure should be imposed on this web of formal proofs. Thus a theorem and its proofs should not necessarily be located at a particular URL or within a particular prover’s library. While the world of symbolic logic and proof theory certainly allows for proofs to be seen as global and permanent objects, there is a lot of research and engineering work that is needed to make this possible. I describe some of the required research and development that must be done to achieve this goal.

Bud Mishra
Professor of Computing at Courant Institute, New York University

Talk Title:
Prospero’s Books: A Distributed Architecture for AI.

Abstract

This preliminary note and its sequels present a distributed architecture for AI (Artificial Intelligence) based on a novel market microstructure. The underlying game theory is based on Information-Asymmetric (Signaling) games, where deception is tamed by costly signaling. The signaling, in order to remain honest (e.g., separating), may involve crypto-tokens and distributed ledgers. Here, we will present a rough sketch of the architecture and the protocols it involves. Mathematical and computational analyses will appear in the subsequent sequels.

Nobuko Yoshida
Professor of Computing at Imperial College, London

Talk Title:
A very gentle introduction to multi-party session types

Abstract

Multiparty session types (MPST) are a formal specification and verification framework for message-passing protocols without central control: the desired interactions at the scale of the network itself are specified into a session (called global type). Global types are then projected onto local types (one for each participant), which describe the protocol from a local point of view. These local types are used to validate an application through type-checking, monitoring, and code generation. Theory of session types guarantees that local conformance of all participants induces global conformance of the network to the initial global type. This paper provides a very gentle introduction of the simplest version of multiparty session types for readers who are not familiar with session types nor process calculi.

Adegboyega Ojo
Senior Research Fellow and the E-Government Group Leader (under the Linked Data Strand) at the Insight Centre for Data Analytics, National University of Ireland, Galway.

Talk Title:
Constructing knowledge graphs from data catalogues

Abstract

We have witnessed about a decade’s effort in opening up government institutions around the world by making data about their services, performance and programmes publicly available on open data portals. While these efforts have yielded some economic and social value particularly in the context of city data ecosystems, there is a general acknowledgment that the promises of open data are far from being realised. A major barrier to better exploitation of open data is the difficulty in finding datasets of interests and those of high value on data portals. This article describes how the implicit relatedness and value of datasets can be revealed by generating a knowledge graph over data catalogues. Specifically, we generate a knowledge graph based on a self-organizing map (SOM) constructed from an open data catalogue. Following this, we show how the generated knowledge graph enables value characterisation based on socio-metric profiles of the datasets as well as dataset recommendation.