In Conversation with Hossein Hamid.

Hossein joined the Basemap team in February 2021 to develop the EVR algorithm in collaboration with the University of Surrey. It’s his task to enhance the background calculations within EVR to make it even more precise!

What are you researching at Basemap?

My main objective at Basemap is empowering EVR software with Machine learning models that make the software able to forecast EV’s (Electric Vehicles) energy consumption, weather condition and to propose the most efficient route. Machine Learning gives systems the ability to automatically learn and improve from experience without being explicitly programmed.

Why did you decide to explore this area of research?

Individual action on climate change and global warming can include personal choices in many areas, such as diet, modes of long (and short) distance travel, household energy use, consumption of goods and services. Therefore, my personal choice was taking an individual action that is going to improve many EVR users’ impact on climate change and global warming. Using my skills as a developer to have a wider impact on the environment and individuals’ ease to adopt EVs into their businesses and personal lives.

Why are you enthusiastic about working with Basemap/EVR?

At Basemap every idea will be appreciated and considered. Basemap, as a company, has such a high-potential for growth, I feel that I can present all my abilities, implement my knowledge and grow the team. Along with all this, I am developing myself in software development, with the help of my team members, which is awesome.

What did you do in life before Basemap?

I did an MSc degree at the University of Surrey in 2019 which I found interesting. I joined Future AI and Robotics for Space application (Fair-Space) as a Machine learning and AI researcher in 2020 to develop fault detection, identification and prediction using Machine learning techniques for Autonomous vehicles, Spacecrafts and Robot systems.

What are you most excited about bringing to EVR?

EVR offers new opportunities to reduce energy consumption through different avenues. Developments of such technologies can benefit from studies on fuel and energy consumption. By considering a high-level machine learning model in EVR, I am making EVR more intelligent and productive.

Where do you think the future of this technology is going?

Due to increasing concerns about global warming and energy security many organisations are seeking to reduce their fuel use by employing EVs. Also, with battery prices reportedly falling, electric cars are expected to be as cheap as fuel-powered cars in the foreseeable future. While the majority of EVs are smart and can be connected to a network, I expect a high demand for this technology in the future that makes the high-ways intelligent, connected, efficient with less safety risk.

 

Try EVR for free for 3 months – simply follow this link to create an account and you can start using it today!

Start Free Trial

Get in touch today!

  • Latest Tweet

    Find out a little more about the science behind the EVR algorithm and the future of EVR, in our interview with Hossein Hamid, Machine Learning and AI Developer, here at Basemap.

    https://evrouting.com/in-conversation-with-hossein-hamid/