Interview with PhD student from TU Delft: Daniyal Selani

“Working with experts from diverse fields in a consortium like SPIDeRR enhances my knowledge and broadens my viewpoint through exposure to varied perspectives and expertise”

We interviewed Daniyal Selani, who has been working as a PhD student at TU Delft on the SPIDeRR project for the past year. He is part of the first work package within the project and works closely with Prof. Rachel Knevel, Prof. Marcel J.T. Reinders, and Dr. Erik van den Akker.

Data science solutions
Selani brings a combination of academic and industry expertise in data science and machine learning to the SPIDeRR consortium. “I joined as a PhD student specifically for the SPIDeRR consortium, focusing my research on manifold alignment for rheumatology data science. We're utilizing diverse data types to predict rheumatic complaints in patients.” Prior to doing his PhD, Selani served as a data scientist at ING for approximately a year following the completion of a master’s degree in artificial intelligence from VU Amsterdam in 2022. 

At present, Selani's primary focus is on collaborating with Leiden University Medical Centre (LUMC) on data analysis endeavours. “I'm tasked with analysing rheumatic questionnaire data, which we're authorized to utilize for modeling purposes. My key responsibility involves experimenting with various algorithms to ascertain their efficacy in determining the need for medical attention among individuals.” These algorithms are designed to augment healthcare practitioners' understanding of patients' conditions and aid in deciding whether a specialist referral is warranted. Furthermore, Selani is actively engaged in crafting the digital twin proposal within work package 4. This initiative aims to establish comprehensive guidelines concerning data types and usage, fostering consistency and precision across our consortium.

Data science solutions
Selani brings a combination of academic and industry expertise in data science and machine learning to the SPIDeRR consortium. “I joined as a PhD student specifically for the SPIDeRR consortium, focusing my research on manifold alignment for rheumatology data science. We're utilizing diverse data types to predict rheumatic complaints in patients.” Prior to doing his PhD, Selani served as a data scientist at ING for approximately a year following the completion of a master’s degree in artificial intelligence from VU Amsterdam in 2022. At present, Selani's primary focus is on collaborating with Leiden University Medical Centre (LUMC) on data analysis endeavours. “I'm tasked with analysing rheumatic questionnaire data, which we're authorized to utilize for modeling purposes. My key responsibility involves experimenting with various algorithms to ascertain their efficacy in determining the need for medical attention among individuals.” These algorithms are designed to augment healthcare practitioners' understanding of patients' conditions and aid in deciding whether a specialist referral is warranted. Furthermore, Selani is actively engaged in crafting the digital twin proposal within work package 4. This initiative aims to establish comprehensive guidelines concerning data types and usage, fostering consistency and precision across our consortium.

Challenges
One of the primary challenges involves handling and accurately interpreting a large volume of self-reported questionnaire data, explains Selani. “This necessitates technical expertise and validation with doctors' reports to ensure the data's reliability.” He also emphasizes the challenge of convincing others to provide access to data and ensuring its quality, noting his role in effectively gathering and utilizing the data. “Although collecting the data isn't my direct responsibility, securing permission to access it is vital. My main task is to ensure that, once obtained, the data meets specific quality standards for our models.”

Fostering collaborative patient impact
Selani thrives on tackling technical challenges and collaborating with experts from diverse backgrounds. “Working with professionals from various fields offers fresh perspectives and enriches my understanding. Being part of a consortium like SPIDeRR exposes you to diverse people, viewpoints, and expertise, broadening your horizons”, Selani says. He emphasizes his commitment to ensuring that his work directly benefits real patients, rather than solely focusing on data analysis. While he may not have direct patient interaction, his goal is to contribute to improving patient outcomes. Selani: “There will likely be trials in the future to assess the impact of our work on both healthcare professionals and patients. Our aim is to enhance the patient journey by providing tools for informed decision-making.” Selani also highlights the importance of collaboration with patient research partners across all work packages, facilitating interaction between data specialists, ethicists, and those directly affected. “Although this vision may be a couple of years away, it's a goal I'm diligently working towards. Furthermore, integrating focus groups from various work packages can offer valuable insights and foster collaboration among researchers facing similar challenges.”

Future
Transitioning to SPIDeRR, Selani hadn't contemplated the future extensively. However, he anticipates the intriguing outcome of collaborative efforts over the next four to five years, given the challenge of aligning numerous institutions and expertise. Selani: “Personally, I aim to leverage the collective hard work of others, confident that I'll have something to contribute to, as I aspire to pursue research and development roles, whether in academia or industry, benefiting from both environments”.