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Aliya Bari is a PhD candidate at the University of Zurich (UZH), under the supervision of Professor Peter Schaber, and a Postgraduate Fellow at the Institute of Biomedical Ethics and History of Medicine (IBME) at UZH. She has also guest lectured at the University of California, San Diego, where she presented her research to students in the bioinformatics course. With an interdisciplinary background and an MBA, her research focuses on healthcare data monetization and its effects on patient equity and autonomy.
Before beginning her PhD, Aliya contributed to research at the Swedish Royal Institute of Technology (KTH), focusing on mHealth, patient empowerment, and patient-reported outcomes, particularly related to mental health and cancer. She also worked on developing and evaluating digital health solutions in Uganda.
Aliya’s current research examines the ethical challenges of healthcare data monetization, especially for vulnerable populations such as those with limited health literacy, socioeconomic disadvantages, or chronic illnesses. She explores how practices like de-identification, anonymization, and data aggregation impact these groups' vulnerability. A key aspect of her work is developing an ethical framework grounded in autonomy, beneficence, non-maleficence, and justice, tailored to healthcare data practices. She also proposes technical recommendations for responsible data governance, including innovative data-sharing technologies, bias-mitigating algorithms, and transparent auditing mechanisms.
She is also exploring feature-based data-sharing models, which empower patients to selectively share data while maintaining privacy. These models have the potential to enable equitable benefit-sharing, including compensation or improved healthcare services. Through collaborations with industry partners, she conducts ethical audits of real-world data practices and develops actionable recommendations to ensure transparency and patient-centric data governance.
Previously, Aliya was an independent deal advisor for Mergers & Acquisitions at Blackrock and KKR, specializing in technical due diligence on advanced AI and data systems. She advised institutional investors and hedge funds on data-intensive acquisitions and provided expertise on technical aspects of M&A strategies.
