Human Centered Machine Intelligence Lab
The Human Centered Machine Intelligence Lab is dedicated to shaping AI systems that are ethical,
fair, and accountable. Our vision is to advance research in fairness aware information retrieval,
human compatible AI, and trustworthy infrastructures that align intelligent technologies with
human values and the public good.
Our past and current Research Collaborators
Our past and current collaborators
Latest Publications
(2025).
A contrastive neural disentanglement approach for query performance prediction.
Machine Learning.
(2025).
Benchmarking prompt sensitivity in large language models.
ECIR.
(2025).
Bias-Aware Curriculum Sampling For Fair Ranking.
ACM SIGIR.
(2025).
Gender disentangled representation learning in neural rankers.
Machine Learning.
(2024).
Enhanced retrieval effectiveness through selective query generation.
ACM CIKM.
(2024).
It Takes a Team to Triumph: Collaborative Expert Finding in Community QA Networks.
ACM SIGIR Asia Pacific.
(2024).
Learning from Yesterday: Predicting early-stage startup success for accelerators through content and cohort dynamics.
Journal of Business Venturing Insights.