Alba V. Olivares-Nadal
I hold a Ph.D in Mathematics, specializing in Operations Research, and I'm currently a Lecturer (Assistant Professor) at UNSW Business School
I am an academic with strong roots in the intersection between theoretical and applied mathematics, analytics and Artificial Intelligence (AI) methods. Since I obtained my PhD in Mathematics in September 2016, I have held various international roles. I’ve been a Postdoctoral Researcher at The University of Chicago Booth School of Business and at the University of Zurich, and I was an Assistant Professor at the University Pablo de Olavide (UPO) in Spain. I have also spent extended periods visiting the London Business School. My experiences at different universities have provided me with unique research and educational perspectives, international collaborators, and varied tools, which together have shaped my academic identity. Leveraging these diverse experiences, my innate curiosity and my passion for generating social impact I produce novel research fostering social good.
Research Interests
Currently, my research spans several exciting areas:
Healthcare: I devise AI methods that leverage extensive datasets to assist doctors in enhancing their decision-making capabilities. For instance, I work with Booth and The University of Chicago Medical Centre (UCM) to evaluate and improve the impact of UCM's Care Management Program. Through my nonprofit Math 4 Change I work developing interpretable rules for predicting the inefficacy of tuberculosis first-line treatment in Mozambique, providing doctors with useful decision-support tools to combat this disease. Still in Mozambique, I am applying AI to unravel the determinants of low birth weight in newborns in Quelimane, potentially providing critical insights for medical interventions
Responsible Supply Chain Management: I develop innovative AI methods and algorithms to enable responsible decision-making in supply chains. For example, I collaborate with industry to tailor and apply AI methods to mitigate food waste through optimized inventory decisions. I also work with a startup to deliver AI solutions that promote inclusivity and body positivity by providing women with a broad selection of undergarments that fit both their unique body shape and their preferences, underscoring the transformative potential of research in social norms and self-perception.
Assessing and combating biases: I analyze large datasets to evaluate biases in human or AI-driven decisions, and I propose new AI methods to alleviate these. I’m analyzing the fairness of Israeli judicial proceedings concerning Arab cases. Since our results suggest significant disparities based on the petitioner’s ethnicity, we aim to provide equitable legal insights to support NGOs aiding Palestinian communities. I'm also interested in forging AI methods that identify and counteract biases, particularly for underrepresented minorities in personalized medicine. I have a special interest in gendered medicine, which I believe can help address the traditional underrepresentation of women in medical studies and trials, which often leads to unsatisfactory treatment healthcare delivery. I also seek to understand and devise strategies to improve healthcare delivery for Aboriginal communities in Australia, ensuring more equitable and effective medical care across diverse demographic groups.
Selected Publications and Working Papers
“Constructing decision rules for multiproduct newsvendors: An integrated estimation-and-optimization framework” European Journal of Operational Research, 315(3), 1021-1037 (2024)
“A Robust Perspective on Transaction Costs in Portfolio Selection” with Víctor DeMiguel. Operations Research, 66 (3), pp. 733-739 (2018)
“A Sparsity-Controlled Vector Autoregressive Model” with Emilio Carrizosa and Pepa Ramírez-Cobo. Biostatistics, 18 (2), pp. 244-259 (2017)
“Robust Newsvendor Problem with Autoregressive Demand” with Emilio Carrizosa and Pepa Ramírez-Cobo. Computers & Operations Research, 68, pp. 123-133 (2016)
“Dynamic Basis Function Generation for Network Revenue Management” with Dan Adelman and Christiane Barz. Submitted (2024)
“Thompson Sampling for Infinite-Horizon Discounted Decision Processes” with Dan Adelman and Cagla Keceli. Submitted (2024)
“Measurized Discounted Markov Decision Processes” with Dan Adelman. Submitted (2024)
“A Primal-Dual Algorithm for the Long-Run Average Reward Problem” with Dan Adelman. Working paper (2024)
“Timewise Lagrangian Dualization of Weakly Coupling Constraints in Markov Decision Processes” with Dan Adelman. Working paper (2024)
“Optimizing Treatment Allocation to Maximize the Health of a Population” with Dan Adelman. In preparation (2024)
“Evaluating the Impact of a Care Management Program on Healthcare Utilization” with Pauline Mourot, George Weyer and Dan Adelman. Working paper (2024)
