ICAIF'21 Workshop on NLP and Network Analysis in Financial Applications - November 3, 2021

[Mihai Cucuringu]

ICAIF'21 Workshop on NLP and Network Analysis in Financial Applications
Virtual Workshop, November 3, 2021; 1:00-5:00 PM EST
https://sites.google.com/view/nlp-na-in-finance-2021

Summary
Applications of Natural Language Processing (NLP) and graph machine learning in finance have received tremendous attention within the last decade. An increasing number of areas from the applied finance community are successfully leveraging and blending tools from NLP, network analysis and graph machine learning, for tasks ranging from asset pricing, portfolio construction, and risk management, to understanding large scale supply chain networks, market crash and fraud detection. This workshop aims to illustrate the broad interplay between those techniques and analysis tools in the context of financial applications, showcasing a suite of problems of interest to both researchers and practitioners. The main goal of the proposed workshop is to bring the researchers and practitioners both from academia and industry together to brainstorm and interact on various sub-topics in the aforementioned theme; to understand the established as well as emerging novel ideas and different schools of thoughts; and, provide a place to achieve new interdisciplinary research.

Keynote Speakers
Tomaso Aste, University College London
Abhijit Bose, Capital One
Bayan Bruss, Capital One
Fabio Cacciolli, University College London
Rama Cont, University of Oxford
Zhi Da, U. Notre Dame
Petter Kolm, NYU
Slavi Marinov, Man AHL
Andreea Minca, Cornell University
Hung Nguyen, Princeton University
TBC, NVIDIA

Call for Papers

We invite papers on NLP and Network Analysis with applications to the financial industry. Topics of interest include, but are not limited to, the following:
-Analysis of financial markets as complex networks
-Network models for portfolio management and systemic risks
-Natural Language Processing (NLP) and financial news networks
-Sentiment analysis in financial news and networks
-Graph-based machine learning models for financial applications
-Other applications of NLP and networks in finance

We also invite tutorials and introductory papers to bridge the gap between academia and the financial industry:
- Overview of Industry Challenges: Short papers from financial industry practitioners that introduce domain specific problems and challenges to academic researchers. These papers should describe problems that can inspire new research directions in academia, and should serve to bridge the information gap between academia and the financial industry.
- Algorithmic Tutorials: Short tutorials from academic researchers that explain current solutions to challenges related to the technical areas mentioned above, not necessarily limited to the financial domain. These tutorials will serve as an introduction and enable financial industry practitioners to employ/adapt latest academic research to their use-cases.

Submission Guidelines
All submissions must be PDFs formatted in the Standard ACM Conference Proceedings Template. Submissions are limited to 6 content pages or less, including all figures and tables but excluding references. Following the conference submission policy, reviews are double-blind, and author names and affiliations should NOT be listed.

Key dates
Submission deadline: Oct 14,  2021 11:59 PM Pacific Time at  https://cmt3.research.microsoft.com/NLPNAInFinance2021
Author notification:  Oct 20, 2021
Camera ready papers due: Nov 1, 2021
Workshop: Nov 3 2021; 1:00 - 5:00 PM EST

Organizers
Nitesh Chawla, University of Notre Dame
Mihai Cucuringu, University of Oxford & The Alan Turing Institute
Xiaowen Dong, University of Oxford    
Dhagash Mehta, Vanguard (Primary Organizer)
Senthil Kumar, Capital One
Stefan Zohren, University of Oxford