Question 1: What technologies are you working with, or have you worked with?

Before joining MIT, I focused on evaluating the equity of transit networks in the Netherlands. This involved approximating the mobility needs of diverse populations while navigating stringent data privacy laws. At MIT, my research has shifted towards predicting crowding in urban rail systems with access to much richer operational datasets while under stricter supervision and non-disclosure agreements (NDAs). Through both works, I've realized how data accessibility and public interest questions shape research outcomes. However, the tools I develop are often closed-source and restricted to the data I can access. The lack of standardization and varied data collection and distribution approaches among vendors make creating shareable tools for fellow researchers challenging. Additionally, while NDAs preserve private information, which is critical in the mobility context, they also limit innovation and equitable solutions in public transit.

Open-source tools in the transit space are emerging but face issues such as poor documentation, limited maintenance, and sometimes dependency on restricted data sources. There is a pressing need for innovative public transit tools and data standards that cater to operators' needs while simultaneously catering to operational researchers as major stakeholders. Here, the key is to foster cross-operability between services, modes, and industries. Building on standards like the General Transit Feed Specification (GTFS), we must rethink how to share and work with data around network connectivity, routing, and access to drive research in this field. One exciting data standard on the horizon in this regard is the new Transit ITS Data Exchange Specification (TIDES), which is currently in its proposal and development stage. This paradigm will standardize automatic fare collection, automatic vehicle location, and automatic passenger count data under one accessible format. Similarly, the open-source General Modeling Network Specification (GMNS) currently developed by the Zephyr Foundation, promises a unified standard to encode mobility networks in a cross-compatible format. On the side of tooling, a notable example of an open-source tool currently becoming a standard for travel-time-based analysis is the Rapid Realistic Routing on Real-World and Reimagined Networks (R5) software developed by MIT Transit Lab’s Andrew Stewart.

Question 2: How do you take account of MIT’s obligation to pursue the public interest in the work that you do? 

While many universities globally play a critical role in pushing operational research of public, shared, micro, and autonomous mobility, MIT has the image of the global center of excellence in engineering, which influences the weight of our voices in this sector. Research that exits MIT is under high scrutiny: it informs policymakers in the U.S. and beyond while being broadcasted to a global audience. Thus, working with and for the public is one of our central values.

Particularly in the field of public transit, we at the MIT JTL-Transit Lab set a high standard for outreach and open, inclusive discourse. On the one hand, JTL-Transit Lab PI Jinhua Zhao’s MIT Mobility Forum connects research, industry, and the public in an open and virtual format, exposing professionals, researchers, and members of the public to the forefronts of urban mobility research. Conversely, MIT JTL-Transit Lab’s Jim Aloisi curates the Transportation Research Council (TRC), which brings together some of the largest transit agencies in the U.S. The TRC aims to promote exchange among these agencies, inform joint research interests, and develop common research agendas.

Given our strong connection between research and public interest, I aim to shape my work to benefit the wider community. This involves creating accessible and transparent tools, advocating for open-source solutions, and supporting open access to data and results. Sharing our tools and data advances our research and supports broader progress in the public transit field, and is needed now more than ever.

Question 3: What more could you and others do to help MIT team meet its social obligation to pursue public interest technology?

MIT has established key pillars for community action, and it's our duty to amplify their importance through active outreach, transparent methodologies, and sharing our tools with the research community. I strive to view my research through an equity lens, constantly questioning how different factors affect transit users. For instance, in my work on crowding, I consider who benefits or suffers during peak times and how this impacts riders with reduced mobility or of specific demographics. I encourage others to develop their own set of equity-focused questions to guide their research. By doing so, we can collectively ensure our work supports public interest and promotes equitable, accessible transit solutions.

Riccardo is a second-year Master of Science in Transportation student. He has formal training in aerospace engineering, a BSc in Artificial Intelligence and Computer Science, and an MSc in Data Science. Through his past experiences at the UNSW Hyperloop project, Swiss Federal Railways, and Continuum Industries, he has entered the realm of the interdisciplinary field of public transportation research. His past work focused on equitable public transit network reduction using reinforcement learning. At MIT’s JTL Urban Mobility Lab, he is now working on monitoring, predicting, and mitigating in-station crowding with a special focus on the use of computer vision while contributing to the development of new tools and standards such as the General Modeling Network Specification (GMNS) as part of the standing committee.