Special Sessions

LOD 2021 Special Sessions

I) Special Session on Data Science for Sustainable Cities

Chairs: Alberto Castellini, Alessandro Farinelli, Giuseppe Nicosia, Varun Ojha

The amount of data generated nowadays by society, city infrastructures, and digital technologies around us is astonishing. The analysis, modeling and knowledge extraction of/from these data is a key asset for understanding urban environments and improving the efficiency of urban mobility, air quality and other forms of sustainability. This special session provides a platform to share high-quality research ideas related to data science methods and technologies for urban environments, a topic of crucial importance for many Sustainable Development Goals (i.e., SDG 7 on Sustainable Energy and SDG 11 on Sustainable Cities and Communities). Another important goal is to establish a meeting point for researchers in academia and industry who develop methodologies and technologies for data science, machine learning and artificial intelligence with specific applications in smart and sustainable cities.

Data acquisition and data analysis in sustainable cities
Data-driven predictive modeling for urban and built environments
Time series analysis and forecasting for urban environments
Anomaly detection for multivariate sensor data
Robust machine learning and model verification
ICT platforms for collecting, visualizing and analyzing data in urban environments
Data analysis for mobility and transportation
Data analysis for air quality monitoring
Data analysis for heating management
Data analysis for smart buildings and smart grids
Model explainability and interpretability in urban applications
Predictive modeling for district heating networks
Predictive modeling for energy-efficient cities
Innovative sensing platforms (e.g., mobile sensors) for data gathering
Data gathering and management for citizen science in urban environments
Data security, privacy and blockchain
Analytics for municipalities and urban stakeholders
Cloud and big data platforms
Smart hospitals and healthcare for sustainable cities
Data-driven modeling for urban complex systems
Data analytics for emergency management
Urban Analytics
Information diffusion and social networks for sustainable cities
Epidemic data analysis in urban environments
City monitoring and Urban planning
Senseable cities
Analytics for smart growth and effective infrastructure

A selection of the best papers accepted for the presentation at the special session will be invited to submit an extended version for publication on Frontiers in Sustainable Cities (https://www.frontiersin.org/journals/sustainable-cities#)

CfP-LOD-2021_DataScienceSustCities_v3

Important Dates for the “Special Session on Data Science for Sustainable Cities”:

* Paper Submission Deadline: Thursday April 29, 2021 (Anywhere on Earth)
* Abstract/Poster/Demo Submission Deadline: Sunday May 9, 2021 (Anywhere on Earth)
* Reviews Released to Authors: by Tuesday June 15, 2021
* Rebuttal Due: by Tuesday June 22, 2021
* Decision Notification to Authors: by Wednesday June 30, 2021
* Camera Ready Submission Deadline: by Saturday July 10, 2021

II) The 7 Special Sessions on Machine Learning

Multi-Task Learning
Reinforcement Learning
Deep Learning
Generative Adversarial Networks
Deep Neuroevolution
Networks with Memory
Learning from Less Data and Building Smaller Models

III) The 7 Special Sessions on Data Science and Artificial Intelligence

Simulation Environments to understand how AI Systems Learn
Chatbots and Conversational Agents
Data Science at Scale & Data in the Cloud
Urban Informatics & Data-Driven Modelling of Complex Systems
Data-centric Engineering
Data Security, Traceability of Information & GDPR
Economic Data Science

IV) Special Session on Multi-Objective Optimization

Comparative studies of various many-objective optimization techniques
Designing and constructing many-objective benchmark test problems
Designing quality/performance metrics for many-objective solutions/algorithms
Development of meta-heuristic algorithms for many-objective optimization problems
Evolutionary many-objective optimization methods in search-based software engineering
Evolutionary many-objective optimization methods applied to real-world problems
Exact methods from mathematical programming for many-objective optimization problems
Many-objective optimization in bi-level optimization problems
Many-objective optimization in combinatorial/discrete optimization problems
Many-objective optimization in computational expensive optimization problems
Many-objective optimization in constrained optimization problems
Many-objective optimization in dynamic environments
Many-objective optimization in large-scale optimization problems
Objective reduction techniques
Preference articulation in many-objective optimization
Preference-based search in many-objective optimization
Study of parameter sensitivity in many-objective optimization
Theoretical analysis and developments in many-objective optimization
Visualization for decision-making in many-objective optimization
Visualization for many-objective solution sets
Visualization for the search process of meta-heuristic algorithms
Multi-objective Optimization: new algorithms and concrete applications
Industrial problems, transportation and logistics problems
contributions to theoretical aspects of Multi-Objective Optimization (MOO) and Multi-Criteria Decision Aiding (MCDA)
descriptions of actual application cases
software contributions to MOO or MCDA
inter-disciplinary research, presenting the contributions of MOO and/or MCDA to other scientific disciplines, or integrating other disciplines into MOO or/and MCDA
decision aiding and multi-objective optimization for sustainability