We are witnessing fast development of the acquisition of big data, as well as emerging AI and blockchain technologies, in both financial market and business operations. As a data processing and system-modeling tool, signal processing, closely married with AI and machine learning, is being used or has great potential in applications in finance and business, such as in capital market analysis, quantitative trading strategy, risk management, economics modeling, marketing data and business analytics, supply chain, business performance modeling and analysis, and blockchain systems. These applications pose new challenges for signal processing since the business data are often nonstationary, non-Gaussian and “dirty”, with unknown/hidden causal relationships. In addition, in business applications, controlled experiments usually cannot be conducted and ground truth is often not available for testing and verifying the models. This symposium aims to attract relevant research contributions within the disciplines of finance/business, mathematics, data science and engineering to facilitate scientific cross-pollination. It will serve the signal processing community to be exposed to the state of the art in finance and business applications, and to foster future research in this emerging area. Topics of interest include but are not limited to the signal processing and AI machine learning methods and applications in:

  • Big Data Analytics in Finance, Marketing and Business
  • Finance and Electronic Trading
  • Financial and Time Series Forecasting
  • Market Modeling (microstructure, price behavior and discovery, limit order book, etc.)
  • Economics and Marketing Modeling
  • Social Media Analysis for Economics and Marketing
  • Statistical Modeling and Monte-Carlo Methods in Business
  • Portfolio Optimization and Management, Risk Analysis and Models
  • Workforce Analytics and Human Capital Management
  • Multimedia Analytics, Customer and Sales Analytics
  • Quantitative Analysis in Sports
  • Supply chain, Business Performance Modeling and Analysis
  • Blockchain, IoT and other Emerging Business Applications

Paper Submission: Prospective authors are invited to submit full-length papers (up to 4 pages for technical content including figures and possible references, and with one additional optional 5th page containing only references) and extended abstracts (up to 2 pages, for paper-less industry presentations and Ongoing Work presentations) via the GlobalSIP 2019 conference website. Manuscripts should be original (not submitted/published anywhere else) and written in accordance with the standard IEEE double-column paper template. The accepted abstracts will not be indexed in IEEE Xplore, however the abstracts and/or the presentations will be included in the IEEE SPS SigPort. Accepted papers and abstracts will be scheduled in lecture and poster sessions. We are also inviting industry talks. Please contact the Symposium Chairs if you are interested in giving an industry talk. 

Important Dates:

  • June 17, 2019: Paper submission due
  • July 15, 2019: Notification of Acceptance
  • August 15, 2019: Camera-ready papers due

For inquiries please contact the Symposium Chairs: Xiao-Ping (Steven) Zhang (xzhang@ee.ryerson.ca) or Kumar Bhaskaran (bha@us.ibm.com

Distinguished Symposium Talks

Please contact the Symposium Chairs if you are interested in giving an industry talk. 

Contact the Symposium Chairs: Xiao-Ping (Steven) Zhang (xzhang@ee.ryerson.ca) or Kumar Bhaskaran (bha@us.ibm.com

Symposium Topics

Submissions Are Welcome on These Topics

  • Big Data Analytics in Finance, Marketing and Business
  • Finance and Electronic Trading
  • Financial and Time Series Forecasting
  • Market Modeling (microstructure, price behavior and discovery, limit order book, etc.)
  • Economics and Marketing Modeling
  • Social Media Analysis for Economics and Marketing
  • Statistical Modeling and Monte-Carlo Methods in Business
  • Portfolio Optimization and Management, Risk Analysis and Models
  • Workforce Analytics and Human Capital Management
  • Multimedia Analytics, Customer and Sales Analytics
  • Quantitative Analysis in Sports
  • Supply chain, Business Performance Modeling and Analysis
  • Blockchain, IoT and other Emerging Business Applications

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CFP GlobalSIP 2019 All Symposia
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Symposium Paper Submission

Prospective authors are invited to submit full-length papers (up to 4 pages for technical content including figures and possible references, and with one additional optional 5th page containing only references) and extended abstracts (up to 2 pages, for paper-less industry presentations and Ongoing Work presentations).. Manuscripts should be original (not submitted/published anywhere else) and written in accordance with the standard IEEE double-column paper template. Accepted full-length papers will be indexed on IEEE Xplore. Accepted abstracts will not be indexed in IEEE Xplore, however the abstracts and/or the presentations will be included in the IEEE SPS SigPort. Accepted papers and abstracts will be scheduled in lecture and poster sessions.

Symposium Key Dates

Please note those important deadlines

Please note the Symposium Key Dates below so you don’t miss any important deadlines.

Camera-Ready Papers Due

Mon, Mar 11th, 2019

Paper Submission Deadline

Sat, Jun 29th, 2019

Review Results Announced

Sat, Sep 7th, 2019

Hotel Room Reservation Deadline

Tue, Nov 5th, 2019

Symposium Organizing Committee

Kumar Bhaskaran

General Co-Chair
IBM Thomas J Watson Research Center, USA

Xiao-Ping (Steven) Zhang

General Co-Chair
Ryerson University, Canada

Technical Committee

  • Sebastien Blandin, IBM Research, Singapore
  • Sue Ann Chen, IBM Research, Australia
  • Stephen M. Chu, IBM Research, China 
  • Li Deng, Citadel, USA 
  • Qingliang Fan, Xiamen University, China
  • Mei Han, PingAn AI Lab, USA 
  • Xiansheng Hua, Alibaba, China 
  • David Kedmey, EidoSearch, Canada
  • Tao Mei, JD.com, China
  • Arash Mohammadi, Concordia University, Canada
  • Konstantinos N. Plataniotis, University of Toronto, Canada
  • Fang Wang, Wilfrid Laurier University, Canada 
  • Yada Zhu, IBM Research, USA