Energy and AI

An Elsevier journal for cutting-edge researches at the interface between #Energy🔥 and #AI💡. EiC: Donghan Jin, Editors: @RaffaellaOcone @Kui_Jiao @Jin_Xuan_

[Billy Wu @ICBillyWu]

📢 Check out our latest paper on "Diagnosing health in composite battery electrodes with explainable deep learning and partial charging data" in @ENERGYandAI led by @Haijun85407986 with colleagues from @Imperial_ESE @ImperialMechEng.
https://t.co/uUwgu0yrn3

[Paolo De Angelis @Paolo1193]

🌐🧠 Learn how #DeepNeuralNetworks transform #energy #engineering in our new @ENERGYandAI paper. 🔬🚀 Deep learning for energy efficiency and policy design. ⚛️🔋🌱⚡️🌍

📄: https://t.co/sjQ83Ow5fH

#DeepLearning #AI #Energy
@small_polito @PoliTOnews

[XiaoYu Wu @XiaoYuWu10]

I am co-editing a special issue on "AI for Energy Materials" in @ENERGYandAI Journal, together with with Prof @prodip_k_das (@EdinburghUni) and Prof. Fei Gao (@FemtoSt). Please consider submit your results! More info: https://t.co/uPh0yyh8d8

[Energy and AI @ENERGYandAI]

The 4th International Conference on Energy and AI will be held during 10-13 Aug 2023 in Xining, China. Come and join us to discuss exciting progress in the field and experience the beautiful Qinghai Lake
👉https://t.co/7ofhX5aLbH

[Jin Xuan @Jin_Xuan_]

How can #AI🤖help chemical engineers👩‍🔬 build better processes? We are developing machine learning tools to help techno-economic analysis & optimisation of emerging chemical processes such as CO2 capture via enhanced weathering 👇
https://t.co/7fc95WEM2F
@ENERGYandAI @SCCESurrey

[Billy Wu @ICBillyWu]

Well done to @Haijun85407986 for publishing his work on the use of convolutional neural networks for diagnosing #battery degradation in @ENERGYandAI. Here we accelerate the diagnostic process of extracting insight from voltage profiles

[Raffaella Ocone @RaffaellaOcone]

HAPPY NEW YEAR!

1st email of 2022: delighted to see our paper on #MachineLearning published! Thanks to my excellent collaborators @Jin_Xuan_ @XinYeeTai @ChristieSteve @LboroEng -looking forward to continuing our collaboration in 2022

https://t.co/A0cjj0kDFm

[Energy and AI @ENERGYandAI]

We are excited to announce that the 3rd International Conference on #Energy and #AI will be a blended online/in-person event in Belfort, France 🇫🇷, July 11-12, 2022. Please submit your abstract via the conference website https://t.co/ZJkDYZrsdD

[Tryambak Gangopadhyay @tryambakganguly]

One of our 2021 papers. On 3D Convolutional Autoencoder. @ENERGYandAI

Paper: https://t.co/XQvf4lZk9I

The model can accurately detect early precursors of instability from hi-speed video in a cyber-physical system with a better visual understanding of transitions.

#DeepLearning

[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]

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]

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]

#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]

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