ΑΙhub.org
 

Forthcoming machine learning and AI seminars: July 2023 edition


by
11 July 2023



share this:
laptop and notebook

This post contains a list of the AI-related seminars that are scheduled to take place between 11 July and 31 August 2023. All events detailed here are free and open for anyone to attend virtually.

11 July 2023

APOLLO: an AI driven national platform for CT coronary angiography for clinical and industrial applications
Speaker: Lee Hwee Kuan
Organised by: Cambridge Centre for AI in Medicine
Sign up here.

12 July 2023

AI for Policy, Decision-Making, Economics, and Finance
Speakers: Elena Verdolini, Jessica Eastling and Claire Huck
Organised by: Climate Change AI (part of summer school)
Watch the livestream here.

14 July 2023

AI for Energy Systems
Speakers: Priya Donti and Nsutezo Simone Fobi
Organised by: Climate Change AI (part of summer school)
Watch the livestream here.

17 July 2023

Listening to nature: harnessing AI and acoustics for biodiversity conservation
Speakers: Juan Daza and Juan Sebastián Ulloa
Organised by: ITU and United Nations
Register here.

19 July 2023

Impacts and Regulation of AI & Climate
Speakers: George Kamiya, Lynn Kaack, Sasha Luccioni and Alice Lépissier
Organised by: Climate Change AI (part of summer school)
Watch the livestream here.

21 July 2023

AI for Transportation
Speakers: Konstantin Klemmer and Nikola Milojevic-Dupont
Organised by: Climate Change AI (part of summer school)
Watch the livestream here.

25 July 2023

AI for Human and Social Systems
Speaker: Hannah Druckenmiller
Organised by: Climate Change AI (part of summer school)
Watch the livestream here.

28 July 2023

Decarbonizing AI: The Good, the Bad, and the Ugly
Speaker: Noman Bashir (University of Massachusetts Amherst)
Organised by: Climate Change AI
Register here.

3 August 2023

Title to be confirmed
Speaker: To be confirmed
Organised by: I can’t believe it’s not better (ICBINB)
Check the website nearer the time for instructions on how to join.

28 August 2023

Distributed communication-constrained learning
Speakers: Alexander Jung (Aalto University), Danijela Cabric (UCLA), Stefan Vlaski (Imperial College London), Lara Dolecek (UCLA), Yonina Eldar (Weizmann Institute of Science)
Organised by: One World Signal Processing
To receive the link to attend, sign up to the mailing list.

31 August 2023

Harnessing Machine Learning for Climate Policy
Speaker: Angel Hsu (University of North Carolina and Data-Driven EnviroLab)
Organised by: Climate Change AI
Register here.


To see past and forthcoming events for 2023, please see our dedicated 2023 seminar page.

If you’d like to visit the webpages of the universities and other organisations that are running regular programmes of seminars, then click here to see our list.

If you are aware of any seminars (both standalone and series) that we’ve missed then please just send us an email and we’ll add them to the list.




Lucy Smith is Senior Managing Editor for AIhub.
Lucy Smith is Senior Managing Editor for AIhub.




            AIhub is supported by:



Related posts :



Deploying agentic AI: what worked, what broke, and what we learned

  15 Sep 2025
AI scientist and researcher Francis Osei investigates what happens when Agentic AI systems are used in real projects, where trust and reproducibility are not optional.

Memory traces in reinforcement learning

  12 Sep 2025
Onno writes about work presented at ICML 2025, introducing an alternative memory framework.

Apertus: a fully open, transparent, multilingual language model

  11 Sep 2025
EPFL, ETH Zurich and the Swiss National Supercomputing Centre (CSCS) released Apertus today, Switzerland’s first large-scale, open, multilingual language model.

Interview with Yezi Liu: Trustworthy and efficient machine learning

  10 Sep 2025
Read the latest interview in our series featuring the AAAI/SIGAI Doctoral Consortium participants.

Advanced AI models are not always better than simple ones

  09 Sep 2025
Researchers have developed Systema, a new tool to evaluate how well AI models work when predicting the effects of genetic perturbations.

The Machine Ethics podcast: Autonomy AI with Adir Ben-Yehuda

This episode Adir and Ben chat about AI automation for frontend web development, where human-machine interface could be going, allowing an LLM to optimism itself, job displacement, vibe coding and more.

Using generative AI, researchers design compounds that can kill drug-resistant bacteria

  05 Sep 2025
The team used two different AI approaches to design novel antibiotics, including one that showed promise against MRSA.

#IJCAI2025 distinguished paper: Combining MORL with restraining bolts to learn normative behaviour

and   04 Sep 2025
The authors introduce a framework for guiding reinforcement learning agents to comply with social, legal, and ethical norms.



 

AIhub is supported by:






 












©2025.05 - Association for the Understanding of Artificial Intelligence