activity
20192025
most citedFair and Diverse Allocation of Scarce Resources

24 citations · 28 across the 5 of their papers we have counts for

collaborators

7 papers

cs.AI2025

Bi-Level Contextual Bandits for Individualized Resource Allocation under Delayed Feedback

Mohammadsina Almasi, Hadis Anahideh

Equitably allocating limited resources in high-stakes domains-such as education, employment, and healthcare-requires balancing short-term utility with long-term impact, while accou…

cs.LG2024

Fair Multivariate Adaptive Regression Splines for Ensuring Equity and Transparency

Parian Haghighat, Denisa G'andara, Lulu Kang +1

Predictive analytics is widely used in various domains, including education, to inform decision-making and improve outcomes. However, many predictive models are proprietary and ina…

cs.CY2023★ 2 cited

Inside the Black Box: Detecting and Mitigating Algorithmic Bias across Racialized Groups in College Student-Success Prediction

Denisa Gándara, Hadis Anahideh, Matthew P. Ison +1

Colleges and universities are increasingly turning to algorithms that predict college-student success to inform various decisions, including those related to admissions, budgeting,…

math.OC2020★ 24 cited

Fair and Diverse Allocation of Scarce Resources

Hadis Anahideh, Lulu Kang, Nazanin Nezami

We aim to design a fairness-aware allocation approach to maximize the geographical diversity and avoid unfairness in the sense of demographic disparity. During the development of t…

cs.LG2020

Fair Active Learning

Hadis Anahideh, Abolfazl Asudeh, Saravanan Thirumuruganathan

Machine learning (ML) is increasingly being used in high-stakes applications impacting society. Therefore, it is of critical importance that ML models do not propagate discriminati…

cs.LG2020

Fair Active Learning

Hadis Anahideh, Abolfazl Asudeh, Saravanan Thirumuruganathan

Machine learning (ML) is increasingly being used in high-stakes applications impacting society. Therefore, it is of critical importance that ML models do not propagate discriminati…

math.OC2019★ 2 cited

High-dimensional Black-box Optimization Under Uncertainty

Hadis Anahideh, Jay Rosenberger, Victoria Chen

Optimizing expensive black-box systems with limited data is an extremely challenging problem. As a resolution, we present a new surrogate optimization approach by addressing two ga…