Publications

2023

1. “Microtransit Optimizer for Mobility-on-Demand”
   Michael Wilbur, Sophie Pavia, Abhishek Dubey, Pravesh Koirala, Zakariyya Al-Quran, Maxime R Coursey, Philip Pugliese, Accepted at IEEE International Conference on Smart Computing (SMARTCOMP) 2023 Best Demo Award
2. “Learning Circular Tabular Embeddings for Heterogeneous Large-scale Structured Datasets”
   Michael Gubanov, Anna Pyayt, Sophie Pavia, to appear in EDBT, DOLAP 2023

2022

1. “Visualizing and Querying Large-scale Structured Datasets by Learning Multi-layered 3D Meta-Profiles”
   Michael Gubanov, Anna Pyayt, Sophie Pavia in IEEE BigData, 2022
2. “Leveraging Scalable Profiling to Learn and Visualize the Latest Trustworthy COVID-19 Medical Research Findings”
   Michael Gubanov, Sophie Pavia, Anna Pyayt, William Goble, in ACM CIKM, 2022
3. “Simplifying Access to Large-scale Structured Datasets by Meta-Profiling with Scalable Training Set Enrichment”
   Sophie Pavia, Rituparna Khan, Anna Pyayt, Michael Gubanov, in ACM SIGMOD, 2022
4. “Hybrid Metadata Classification in Large-scale Structured Datasets”
   Sophie Pavia, Nick Piraino, Kazi Islam, Anna Pyayt, Michael Gubanov, invited paper in the journal of Data Intelligence, Rinton Press, Special Issue on “Best of DEXA”, 2022

2021

1. “Towards Unveiling Dark Web Structured Data”
   Sophie Pavia, Rituparna Khan, Anna Pyayt, Michael Gubanov, in IEEE BigData, 2021
2. “Learning Tabular Embeddings at Web Scale”
   Sophie Pavia, Rituparna Khan, Anna Pyayt, Michael Gubanov, in IEEE BigData, 2021