Marina K.

Type
Public sector project: HORIZON EU (H2020) research and innovation action including 33 partners - INCIT-EV

Description
Between early 2023 and 2024, I was immersed in a compelling role as a Project Manager at a research foundation in Turin, where I contributed to a Horizon 2020 Research and Innovation Action project called INCIT-EV, involving a vast network of 33 partners. This project aimed to demonstrate an innovative set of charging infrastructures, technologies, and associated business models designed to improve the EV user experience.

My main responsibility was orchestrating the development of a cutting-edge Decision Support System (DSS) alongside two internal developers and two external partners, while also coordinating a Work Package consisting of 13 partners. The DSS tool was tailored to assist Mobility Planners and Policy Makers in crafting customized action plans to promote the uptake of electric vehicles in cities. By facilitating seamless collaboration and communication, my aim was to foster a sense of shared purpose among stakeholders, ultimately working towards a more sustainable future for urban mobility. In addition to the coordination activities, I also played a pivotal role in enhancing the tool's usability from the users’ perspective.

Read more
You can read more about the project on the official website. The Decision Support System (DSS) tool will be accessible to the public in the near future here.

Type
Public sector project: HORIZON EU (H2020) research and innovation action including 69 partners - SHOW

Description
During late 2022, I was involved in a Horizon 2020 project called SHOW, which aimed to support the deployment of shared, connected, and electrified automation in urban transport, with the goal of advancing sustainable urban mobility. As part of the project, real-life urban demonstrations took place in 20 cities across Europe, integrating fleets of automated vehicles into public transport, demand-responsive transport (DRT), Mobility as a Service (MaaS), and Logistics as a Service (LaaS) schemes.

One of the demonstration sites was the city of Turin, where two autonomous shuttles operated in the hospital area along an authorized path of about 5 km. To drive operational improvements, I developed a Power BI dashboard for shuttle tracking in Turin, leveraging my expertise in data analysis and visualization.

Read more
I cannot share more details on the dashboard for autonomous shuttle tracking for privacy reasons, but you can read more about the project on the official website and also on the Turin pilot case.

Type
Personal project: result of a Global Summer School in Urban Data Analytics

Description
In July 2025, I participated in a week-long workshop "Image Based Analytics for Data Driven Mapping of Urban Vulnerabilities" by Institute for Advanced Architecture of Catalonia (IAAC) in Barcelona, which explored how digital innovation and urban analytics can create more inclusive cities by integrating citizens' needs into urban design. By using multiscalar datasets, specifically Google Street View imagery, open data and tools like QGIS, I analyzed the urban environment in one neighborhood of Barcelona (Nou Barris) and developed sustainable design proposals. I chose Nou Barris neighbourhood because of its':

• highest rates of childhood obesity in the city (official ASPB data),
• lowest income per capita,
• known deficit in quality public space and sports infrastructure, particularly near schools,
• politically under-prioritized situation in terms of urban renewal compared to central districts.

The data taken into consideration included:

• Google Street View Imagery in order to assess the conditions and accessibility of parks and playground areas
• Barcelona open data on socio-economic indicators, schools, open playgrounds and parks
• Open Street Map data on fast food restaurants and similar facilities

The ongoing analysis in QGIS software showed how certain areas of Nou Barris neighbourhood are deprived of open playgrounds and parks, while flourishing with fast food facilities. Once finished, this page will be updated.

Read more
The maps I created and data analysis code are available on my Github.

Type
Private sector project: Commissioned by a local Trade Union in Italy.

Description
In 2021, as a part of a large-scale project evolving around the prediction of mobility demand in Piedmont, I analyzed the mobility behaviours in the region during and after the COVID-19 pandemic thanks to open data from Apple, Google and Facebook.

The data taken into consideration included:

• general movements from Facebook (Movement Range Maps)
• requests for travel indications by car from Apple Maps (Mobility Trends Report)
• shopping areas and entertainment venues attendances; and office attendances from Google Maps (COVID-19 Community Mobility Reports)

Considering the period from March 2020 until June 2021, this analysis showed how mobility habits changed (at least temporarily), especially in the case of shopping, entertainment and office attendances where the % change was still below the baseline (-22% in the case of offices).

Read more
Due to privacy reasons, I cannot share more information about this project, but the data analysis code is available on my Github.

Type
Private sector project: A research project resulted with a published article.

Description
In 2019, I had the privilege of being selected as one of the top 8 graduates and was subsequently awarded an Applied Data Science Fellowship. This fellowship provided me with the opportunity to conduct comprehensive research on the relationships between road crashes and urban features. My tasks included analyzing relevant literature, collecting and cleaning data, performing statistical analyses, and utilizing machine learning algorithms to gain insights into the complex interplay of road crashes and urban characteristics.

Following the OECD's recommendations for a modern road safety approach and employing casualty matrices, I systematically examined crash causation in 24 European cities, identifying cars as the predominant threat, with variations observed across different urban environments. Further analysis of urban features, including population density and infrastructure, revealed a noteworthy correlation: cities with higher pedestrian presence and lower speed limits demonstrated fewer casualties (see Fig 1.). While acknowledging potential reporting biases, my research emphasizes the need for an evidence-based road safety paradigm. This research advocates for urban decision-makers to prioritize walkability and address car-related hazards, fostering enhanced safety, public health benefits, and sustainable urban development.

Read more
You can read the scientific paper on EPJ Data Science. The source code of the project is stored on my Github.

Type
Personal project: Daily social mapping project happening every November.

Description
The idea of this online challenge is to create maps based around different themes each day of November using the hashtag #30DayMapChallenge. There are no restrictions on the tools, technologies or the data that can be used in the maps, the point is learning and sharing - that's is why I decided to give it a try and have some fun while doing so.
I mainly used the datasets that are publicly available, but I also played around with some web scraping (where possible) and the results are providing some useful insights, mainly for Italy - since that's where I live at the moment. You can see one of the maps I created here below:

Read more
The source code and other maps I created are hosted on my dedicated GitHub repo.