Kiaei and Kulkarni Receive the Best Poster Award at the M.S. Data Science Poster Fair
Congratulations to our Data Science M.S. students who presented their Capstone Projects at the inaugural Data Science M.S. Poster Fair. Their projects showed how Data Science can be applied to a wide range of topics, including social web, biology, medicine, statistical modeling, and scalable algorithms.
Shayesteh Kiaei and Akshay Kulkarni were both awarded the Best Poster Award. Kiaei's poster, "Parametric Topic Modeling on Unit Hypersphere with Word Embeddings," focused on a form of text mining which discovers the main topics exhibited in a large collection of documents. Kulkarni's poster, "Trip Mode Prediction," looked into using SmartPhone sensors to develop a more robust classification system for data collected from GPS and accelerometers with a goal to help people find their destinations in a more effective manner.
All posters that were presented can be accessed below, including the two Best Posters from the fair.
- "An epigenome correlation map using Infinium 450 DNA methylation array" by Qimeng Chen
- "Outbreak Alert and Characterization Using Big Data" by Wei Chen
- "Spatial-Temporal Analysis for Data Driven Decision Making" by Dhruv Dhokalia
- "Investigation on Algorithmic Trading" by Qing Hu
- "Using Fuzzy String Matching to Automate Importing Data to SQL Server" by Michael Justice
- "Applying Neural Networks to Movie Recommendation" by Utkarsh Kajaria
- "Parametric Topic Modeling on Unit Hypersphere with Word Embeddings" by Shayesteh Kiaei (tied for Best Poster)
- "Trip Mode Prediction" by Akshay Kulkarni (tied for Best Poster)
- "Predict seizures in long-term human intracranial EEG recordings" by Feng Li
- "Ontology-based classification of social media text data" by Sasank Maganti
- "Churn Prediction on Movielens" by Rohan Sadale
- "Phasor Measurement Unit (PMU) Event Classification" by Benjamin Sorenson
- "Evaluating Apache Spark for unstructured communication and computation" by Ancy Tom
- "Learning to Classify DSTL Satellite Images" by Ting Wang
- "Optimizing Machine and Human Classifications in Citizen Science" by Marco Willi
- "Multiple Imputation for Missing Values" by Yuemin Xu
- "Deep Learning for Micro-Array Based Cancer Classification" by Lijuan Zhong: