Brandeis Visual Analytics Lab
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Advances in data visualization and machine learning offer incredible possibilities, but the role of the human mind remains critical in the analysis and interpretation of complex information. At the Brandeis Visual Analytics Lab, we design systems that harness the strengths of both human intuition and computational power, making data-driven discovery accessible to all.

Our research, led by Professor Dylan Cashman, focuses on enhancing the interpretability of machine learning models and developing interactive tools that aid in the exploration of data. Whether through columnar data augmentation using knowledge graphs or studying the human role in model selection, our projects aim to empower users in their analytical processes.

Background

Professor Dylan Cashman earned his PhD in Computer Science from Tufts University and has a background in data science from Novartis. He now leads the Visual Analytics Lab at Brandeis University, working at the intersection of human-computer interaction, machine learning, and data visualization. His research has earned recognition, including Best Paper Awards at international conferences such as IEEE VIS and Eurovis.

Our ongoing work involves creating innovative tools for visual data analysis, fostering collaboration with academic and industry partners, and exploring the role of human insight in applied machine learning systems.

Our team is fairly small and composed of both undergraduate and graduate students. If you are interested in working with professor Dylan Cashman on project, reach out to him via email. Please include a CV and explain what got you interested in research and what your goals are in conducting research with our lab. We like to work with students who are passionate about what they choose to work on. We all thrive in a culture of mutual respect.