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Energy Informaticshttps://www.scimagojr.com/journalsearch.php?q=21101048366&tip=sid&clean=0Indexing servicesThe full text of all articles is deposited in digital archives around the world to guarantee long-term digital preservation. You can also access all articles published by SpringerOpen on SpringerLink. We are working closely with Web of Science (Clarivate Analytics) to ensure that articles published in Energy Informatics will be available in their databases when appropriate. The journal is currently indexed in the following databases:SCOPUSEi CompendexDOAJInstitute of Scientific and Technical Information of ChinaNaverProQuestOCLC WorldCat Discovery ServiceEBSCOGoogle Scholar Article processing charges (APC)Authors who publish open access in Energy Informatics are required to pay an article processing charge (APC). The APC price will be determined from the date on which the article is accepted for publication.The current APC, subject to VAT or local taxes where applicable, is: £940.00/$1490.00/€1190.00Visit our open access support portal and our Journal Pricing FAQs for further information. Aims and scopeThis journal aims to provide a unique platform for researchers and practitioners of energy informatics in various scientific, technological, engineering and social fields to disseminate original research on the application of digital technology and information management theory and practice to facilitate the global transition towards sustainable and resilient energy systems.The journal publishes essential, peer-reviewed, interdisciplinary research addressing scientific, engineering and business topics related to energy, including but not limited to:Innovation in data-driven energy services and business modelsBig Data-driven smart Energy Management SystemsManagement of data and information flow in the Digital Energy System 4.0Data analytics for energy-cost efficient system operationPrivacy issues in energy data managementDigitalization of energy production, delivery and consumption, including policy and strategyDigital technologies for enabling energy-aware user behaviorContextual computing for supporting human and energy system interactionsEnergy-efficient Cloud Computing and data centersCyber security issues for safe and reliable Smart grid operationSocial media’s role in the transition towards sustainable energyApplication of Artificial Intelligence and Agent-based technology in smart energy systemsModel-based and data-driven energy forecasting, including energy production and useManagement of public and private procurement of digital energy technologySocioeconomic opportunities and barriers for adoption of digital energy technologiesSociotechnical aspects related to design and implementation of smart energy systemsInnovation management in smart energy business eco-systemsDigital entrepreneurship in emerging energy marketsSmart grid communication architectures and protocols for improving grid resiliency, including graceful degradation and self-healingDemand-side management, including demand response, dynamic pricing and incentive designMicrogrid and distributed generation management and controlMonitoring and control of Smart Buildings, including Smart Grid interoperability

Call for Papers2025 IEEE 2nd International Conference on Deep Learning and Computer VisionJinan|ChinaApr. 18-21, 2025Full paper submission Deadline: Feb. 10th, 2025Acceptance Notification: Mar. 26th, 2025Registration Deadline: Apr. 11th , 2025Conference Date: Apr. 18-21st, 2025Link: https://www.icdlcv.orgContact: icdlcv@126.comYou are kindly encouraged to contribute to and help shape the conference through submissions of your research abstracts and papers to DLCV 2025 conference. Topics of interest for submission include:Track 1: Deep LearningMachine LearningUnsupervised LearningDeep Reinforcement LearningConvolutional Neural Networks (CNN)Deep Hierarchical Networks (DHN)Recurrent Neural Network (RNN)Neuro-Fuzzy AlgorithmsAutoencodersGraph Representation LearningClustering, Classification and RegressionEvolutionary MethodsAutonomic ComputingUser ModelingInformation Retrieval and ReuseQuestion-AnsweringCognitive ArchitecturesDeep Learning Approach in Recommendation SystemsTrack 2: Computer VisionBig data and computer visionBiomedical image analysisImage and video codingImage and video retrievalRemote sensing imageComputational photographyOptimization and method of studySensor and displayData collection and performance analysisComputer vision of deep learningDocument image analysisCharacter identificationAnalysis, behavior identityVisual modelsVideo analysisMultimodal information processingVisual and languageMotion and tracking3D reconstructionHuman-computer interaction

Application deadline: July 4th, 2024Location: Nova Information Management School Universidade Nova de Lisboa Campus de Campolide Lisbon, PortugalLink: https://academicpositions.com/ad/nova-ims/2024/faculty-positions-for-assistant-professor-businesss-intelligence-and-analytics/218536The PositionNOVA Information Management School (NOVA IMS) at Universidade Nova de Lisboa invites for an expression of interest for a position as a Professor (at Assistant/ Associate or Full Professor level) in Business Intelligence and Data Warehouses.The position is to be filled in NOVA IMS’ facilities in Lisbon, Portugal.Salary and conditions are competitive and will be commensurate with qualifications and experience.QualificationsNOVA IMS seeks a candidate with a strong commitment to excellence in scholarly research and teaching. He/ she will be expected to teach in undergraduate as well as graduate programme classes related to Business Intelligence and Databases and one or more of the following areas of expertise:Business IntelligenceDatabase Management SystemData WarehousingData AnalyticsThe successful applicants should have a strong academic background and an international profile in the aforementioned expertise areas with a record of research publications in top-ranked field journals. Moreover, relevant experience in obtaining funding and managing national and international research projects will be considered an advantage.The successful candidate should be able to provide strong and committed leadership in education, including curriculum development, course coordination and educational innovation, the preparation and delivery of lectures, seminars and tutorials, consultation with students, and marking and assessment.The main requirements for applicants are listed below:PhD or doctoral degree from a recognized university;Excellent scientific achievements, documented by internationally recognized publications;Excellent didactic skills;Demonstrate an excellent teaching ability at both the undergraduate and graduate levels;High capacity to develop pedagogical innovations and to manage a programme;Excellent communication skills (oral, written, presentation);Proficient in English (oral and written);Ability to teach in English;Collaborative skills, initiative, result oriented, organization, and capacity to work in an interdisciplinary environment.The SchoolNOVA Information Management School (NOVA IMS, www.novaims.unl.pt) is the School of Information Management and Data Science of Universidade Nova de Lisboa. It is one of the 9 academic units of Universidade NOVA de Lisboa, a university institution with internationally recognized research and quality teaching.It is dedicated to converting data into value, under the motto “Data with Purpose”, through a wide range of activities, namely teaching, and research and development activities that are largely supported by international partnerships, offering a unique research environment to address its main research challenges.The quality of its training is recognized globally, through different national and international accreditations, and outstanding positions achieved in various fields, namely in the Eduniversal ranking (seven of its masters and postgraduate degrees are recognized among the best in the world in their respective areas).NOVA IMS has more than 30 years of accumulated experience in data processing and analysis, which it now puts at the service of digital transformation and the “Big Data” environments in which we live in, namely through a wide range of laboratories (NOVA ANALYTICS LABS powered by NOVA IMS). Today, it has more than 3.000 students from 81 different countries, and high levels of internationalization in all the activities it carries out from Lisbon to the world.How to applyInterested candidates are invited to send the application material listed below by email to rh@novaims.unl.pt (mentioning the reference of the application):A cover letter including motivation to join NOVA IMS;A complete curriculum vitae with a list of publications and a list of classes taught;A copy of the three most significant recent publications, communications or working papers.Reference: NOVAIMS_ BusinessIntelligenceandAnalytics