[visionlist] International Workshop on Pattern Forecasting -- CfP due Oct 10th 2020

Fabio Galasso fabio.galasso at gmail.com
Fri Sep 4 12:32:55 -04 2020

Dear Colleagues,

May I draw your attention on an upcoming workshop on Pattern Forecasting
(PATCAST), to gather scientific contributions on forecasting, both
regarding the general theory and its manifold applications across the
various fields of science (computer vision, NLP, machine learning,
robotics, finance, environmental sciences, bioinformatics etc.)

Paper contributions are due on October 10th, 2020
Please consider submitting and participating.
And please spread the news.
The workshop would be at ICPR, on January 11th 2021.

More details in the CfP below and at:

Best regards,

(We apologize if you receive multiple copies of this message.)

International Workshop on Pattern Forecasting
January 11th, 2021, Milan, Italy
in association with ICPR 2020
>> PAPER submission:         October 10th, 2020<<

Anticipating patterns has become a crucial activity in the last years, due
to the combined availability of huge amount of data, techniques for
exploiting noisy information, transferring knowledge across domains, and
the need of forecasting services within many heterogeneous domains, from
computer science to environmental sciences, from economics to robotics and
from bioinformatics to social sciences and humanities. A growing spectrum
of applications in self-driving cars, weather forecasting, financial market
prediction, real-time epidemic forecasting, and social network modeling
needs to be explored within a same venue. This workshop aims therefore to
identify commonalities, gather lessons learnt across domains, discuss
modern and most successful techniques, and foster the exchange of new
ideas, which may extend to other novel fields too.

The International Workshop on Pattern Forecasting addresses the general
problem of forecasting patterns. This is not just limited to a specific
domain, but rather intended as cross-fertilization of different
disciplines. By doing so, it seeks to highlight possible general-purpose
approaches which may be applied to a large span of data types, promoting
and motivating further studies in specific directions. As an example,
techniques for predicting the diffusion of epidemics are currently adopted
to forecasting activities within social networks. We are convinced that
many other hybridations are ready to be explored.

We plan a number of invited talks by senior scientists from different
domains, an extensive poster session for stimulating collaborations among
young researchers, and a final panel to gather the major challenges emerged
in the day and the effective techniques. We anticipate fructuous discussion
on the relation between techniques and challenges and on the adoption of
techniques beyond those fields where they have been originally designed.

The workshop seeks contributions from researchers and practitioners from
different domains, to share current best algorithms and practices, to
foster discussion among diverse communities and to define common grounds
for joint progress, within the general artificial intelligence and pattern

The topics of interest for the convention include, but are not limited to,
the following areas:
- Forecasting in computer science, environmental sciences, economics,
robotics, bioinformatics, social sciences, humanities
- Short term/long term prediction
- Structured input/structured output forecasting
- Distributed (cloud) forecasting
- Real-time forecasting
- Hierarchical forecasting
- Judgemental forecasting
- Integration of system dynamics and forecasting models
- Performance measurement
- Knowledge sharing and organisational learning
- Forecasting visual patterns/styles
- Pedestrian/vehicle trajectory forecasting
- Forecasting for Industry 4.0
- Predictive maintenance
- Weather forecasting
- Earthquakes/eruption forecasting
- Econometric Forecasting
- Financial Forecasting and Risk Analysis
- Forecasting and Planning Systems
- Forecasting Electricity Load and Prices
- Forecasting for Workforce Management
- Forecasting Support Systems (FSS)
- Intermittent Demand Forecasting (Forecasting of Count Series)
- Robot planning
- Intention prediction
- forecasting for genomics
- Virality/trend prediction into social networks
- Forecasting as product recommendation

- Workshop date: January 11th
- Paper submission deadline: October 10st
- Paper author notification:  November 10th
- Camera-ready submission: November 15th
- Finalized workshop program: December 1st

- Pratik Prabhanjan Brahma, Volkswagen, Belmont, CA
- Thomas Brox, University of Freiburg, DE
- Carolina García Martos, Universidad Politécnica de Madrid, ES
- Marco Pavone, Stanford University, CA
- Giovanni Maria Farinella, University of Catania, IT
- Marco Bee, University of Trento, IT
- Dino Zardi, University of Trento, IT
- Novella Bartolini, Sapienza University, IT

Workshop Organizers:
- Marco Cristani, University of Verona, marco.cristani at univr.it
- Kris Kitani, Carnegie Mellon University, kkitani at cs.cmu.edu
- Fabio Galasso, Sapienza University, galasso at di.uniroma1.it
- Siyu Tang, ETH Zürich, siyu.tang at tuebingen.mpg.de

Further to the organizers, a panel of external reviewers would be employed
in the program committee, including:
- Sikandar Amin (OSRAM)
- Bharti Munjal (TUM)
- Nick Rhinehart (UC Berkeley)
- Wei-Chiu Ma (MIT)
- De-An Huang (Stanford)
- Namhoo Lee (Oxford)
- Ye Yuan (CMU)
- Yan Zhang (MPI Intelligent Systems)
- Miao Liu (Georgia Tech)
- Qiuhong Ke (University of Melbourne)
- Giorgio Roffo (University of Glasgow)
- Francesco Setti (University of Verona)

Submissions must be formatted in accordance with the Springer's Computer
Science Proceedings guidelines (
as full paper (12-15 pages). Accepted manuscripts will be included in the
ICPR 2020 Workshop Proceedings Springer volume. Once accepted, at least one
author is expected to attend the event and present the paper. Papers will
be presented as posters, since orals will be dedicated to invited talks.
Submission would be done via Microsoft CMT3:


Prof Fabio Galasso
Sapienza University

+39 345 5969678
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