2nd International Conference on Energy and AI

A virtual conference organised by @ENERGYandAI showcasing the latest research in Energy & AI research + connecting the community. 10th-12th of August 2021

[2nd International Conference on Energy and AI @ICEAI21]

And that's the end of the Energy & AI conference. Thanks to all our speakers, contributors, helpers and attendees. For those of you who missed Day 3. The recording is now online to catch up on the interesting talks and discussion https://t.co/WmDrJsCZns

[2nd International Conference on Energy and AI @ICEAI21]

And we're off with the 3rd day of the conference with Prof. Markus Kraft's talk on A Dynamic Knowledge-Graph Approach to Digital Twins - The Universal Digital Twin. Join with the link below
https://t.co/SkXPSshJPO

[2nd International Conference on Energy and AI @ICEAI21]

Miss Day 2? Recording the talks online from Dr. Dhammika Widanalage's (Data-driven modelling of lithium-ion battery aging), Prof. Zhiguo Qu's (Prediction and control of heat and mass transfer in porous media using deep learning) and Dr. Shuang Zhai https://t.co/00XMKA4g03

[2nd International Conference on Energy and AI @ICEAI21]

The last day of the Energy & AI conference finishes with the much anticipated session chaired by @Jin_Xuan_ with Prof. Markus Kraft (A Dynamic Knowledge-Graph Approach to Digital Twins), Prof. @RaffaellaOcone (Engineering equitable research and innovation) and Dr. Nada Zamel!

[2nd International Conference on Energy and AI @ICEAI21]

Miss day 1? Revisit the fantastic talks from Dr. Alpha Lee (Data-driven understanding of battery degradation), Dr. Jing Zhang (Energy and AI-One Year on) and Prof. @venkvis (Robotic Experimentation and Machine Learning for Next-Generation Batteries) https://t.co/VeCFcvfvbp

[2nd International Conference on Energy and AI @ICEAI21]

After the fantastic talks and discussion on day 1 of the event, we're ready for day 2 of the conference chaired by @huizhi_wang with Dr. Dhammika Widanalage, Prof. Zhiguo Qu and Dr. Shuang Zhai where we'll explore further into how AL is helping #batteries and #fuelcells

[2nd International Conference on Energy and AI @ICEAI21]

We're excited to be kicking off the 2nd International Conference on Energy & AI today with Dr. Jing Zhang @ElsevierEnergy "Energy & AI-One year on", Dr. Alpha Lee @Cambridge_Uni "Data-driven understanding of battery degradation" and @venkvis. Details below
https://t.co/XyXayHs9d5

[2nd International Conference on Energy and AI @ICEAI21]

Thrilled to have Prof. Jianguo Lin @NanjingUnivers1 give an invited talk on "New research paradigm of hydrogen energy materials led by artificial intelligence". Find out how AI can be used to accelerate #fuelcell materials discovery in his talk https://t.co/2pLJmUeLDC

[2nd International Conference on Energy and AI @ICEAI21]

#Solar energy is a key energy vector, however it's generation is variable. Check out Veeraraghava Raju Hasti's talk @LifeAtPurdue on "Solar Energy forecast models based on gradient boosting algorithms" to see how ML can help us predict PV generation https://t.co/3W9OpMXMYz

[2nd International Conference on Energy and AI @ICEAI21]

Amazing rate of progression in commercial #hydrogen #fuelcell trucks in #China. Dr. Shuang Zhai from Shanghai REFIRE gives a great overview of progress in his invited talk "Development of vehicle FC system based on big data platform and AI technology" https://t.co/bOY6RxXbOv

[2nd International Conference on Energy and AI @ICEAI21]

Low-temperature start-up can be challenging for PEM #fuelcells. Find out how we can model this dynamic behaviour in Kangcheng Wu's talk "Data-driven PEMFC prediction and real-time optimization using semi-recurrent sliding-window method" @TJU1895 https://t.co/HHr30QvYIt

[2nd International Conference on Energy and AI @ICEAI21]

Energy is a diverse field of research and we're thrilled to see the various ways artificial intelligence has been applied to solve problems including: flame combustion, hydrocracking, fuel cells, energy consumption etc. Check out the playlist for all talks
https://t.co/1o8c4xb3KA

[2nd International Conference on Energy and AI @ICEAI21]

We are honoured to have Prof. Yun Wang from @UCIrvine present his invited talk on "Machine learning and artificial intelligence in PEM fuel cell development". Find out how ML/AI can tackle the various technical barriers exist for #fuelcell deployment https://t.co/tOdhwx9seY

[2nd International Conference on Energy and AI @ICEAI21]

Disaggregating energy consumption data is key to manage domestic appliances. Listen to Vidushani Dhanawansa's talk on "An investigation of the effects of kernel tuning on the performance of CNN architectures: A case study of load monitoring applications" https://t.co/jHRQl37HzG

[2nd International Conference on Energy and AI @ICEAI21]

Predicting #fuelcell performance under dynamic conditions is key for real world implementation. Check out this work by Kai Wang at FAW Group who uses LSTM to address this issue. "PEM Fuel Cell Degradation Predication by Long Short term Memory Network" https://t.co/tbTMCJltdb

[2nd International Conference on Energy and AI @ICEAI21]

The number of people in a room strongly affects its energy demands. Find out from Wuxia Zhang @UniofNottingham how ML can help. "Building occupancy prediction through machine learning for enhanced energy efficiency, air quality and thermal comfort" https://t.co/wje3nvCKBb

[2nd International Conference on Energy and AI @ICEAI21]

Lithium-ion #batteries have complex degradation pathways. @XinhuaLiu5 @Beihang1952 explores how we might track and predict degradation in her talk on "Online state of health estimation on lithium ion batteries based on machine learning method" https://t.co/YrKLnZQSJH

[2nd International Conference on Energy and AI @ICEAI21]

Predicting #electricity loads can be a complex problem. Nattapong Puttanapong from @thammasat_uni explores how machine learning approaches can help "Forecasting household electricity demand using machine learning algorithms - A case of Thailand"
https://t.co/XNiad1Om03

[2nd International Conference on Energy and AI @ICEAI21]

The temperature of rooms affects energy consumption and comfort. Is there a way to optimise both? Fateh Boulmaiz and colleague's works @CNRS explores how "Killing two birds with one stone - Improving building energy efficiency and occupant comfort"
https://t.co/N6i5RH4r21

[2nd International Conference on Energy and AI @ICEAI21]

Image based detection methods can be a powerful tool. Listen to Paige Wenbin Tien to see how this can improve energy consumption predictions in buildings "Scenario based analysis of deep learning occupancy+window recognition approach for energy efficiency" https://t.co/2EdoRcAaKA