Mostafa El Gamal, WPI, Electrical and Computer Engineering, 2016-2017 (graduated Spring 2017)
Paulo Ferreria, WPI, Electrical and Computer Engineering, 2016-2017 (graduated Spring 2017)
Aaron Birt, WPI, Material Science and Engineering, 2016-2017 (graduated Spring 2017)
Jaroslaw Glowacki , 6-26-2016 Laboratory for Computation and Visualization in Mathematics and Mechanics, Ecole Polytechnic Federal Lausanne, Trip funded by LCVMM.
Kakar Tabassum, WPI, Data Science, 2016-2017
Suhas, Srinivasan, WPI, Data Science, 2016-2017
Xinyuan Sun, WPI, Data Science, 2016
Viseth Sean, WPI Data Science, 2016
Kevin Guth, Aura Ramirez, Erik Sola (with Lane Harrison), Cyber Data Analytics, Fall 2017/Spring 2018
Luke Buquicchio, Juan Louis Estrada, Everett Harding (with Stephan Sturm), Collaboration with Zurich University of Applied Sciences on Deep Learning, Fall 2017/Spring 2018
Emily Bigwood, Owen Chace, Ranier Gran, Stephanie Martin, WPI Career Development Center collaboration, Fall 2017/Spring 2018
Michael Giancola (with Jacob Whitehill), Doubly Stochastic Matrices for Style Analysis in Mechanical Turk Data, Fall 2017/Spring 2018
Casidy Litch (with Lane Harrison), Cyber Data Analytics, Fall 2016/Spring 2017
Ian Jacoway, Gina Rios, Shannon Feeley (with Stephan Sturm), Process Mining for Credit Suisse, Fall 2016/Spring 2017
Sadie Gauthier, Zachery Peters, Emily Weber, Robert Vigeant, WPI Career Development Center collaboration, Fall 2016/Spring 2017
Yao Yuan Chow (with George Heineman), “Application of Data Analytics to Cyber Forensic Data”, Fall 2016
Kathleen Kay, “Inverse Methods for Manifold Learning”, Spring 2016
Maryann VanValkendburg (with Gu Wang), Data for Improving Mathematical Sciences Education, Fall 2017/Spring 2018
Fall 2017:
Bahadur, Nitish, Applications of non-linear dimension reduction to finance, Ph.D. advisor
Baker, Lauren, Machine Learning for Carbon Nano-tube sheets
Gajamannage, Kelum, Non-linear dimension reduction, Postdoctoral mentor
Jutras, Melanie, Anomaly Detection in the Domain Name Service, Master’s thesis
Li, Wenjing, Ensemble methods in machine learning, Ph.D. advisor
Liu, Haitao (co-advisor with Jian Zou), Graphical Models, Ph.D. advisor
Lui, Yingnan, Deep Learning for Financial Time-series, Ph.D. advisor
Medina, Patricia, Deep Learning for LIDAR Processing, Postdoctoral mentor
Reese, Tyler Michael (co-advisor with Joseph D. Fehribach and Brigitte Servatius), Kirchhoff Graphs, Ph.D. advisor
Weiss, Matt, Supervised Machine Learning for Chemical Sensors, Ph.D. advisor
Sun, Fangzheng, Deep Canonical Correlation Analysis, Master’s thesis
Zhou, Chong, Robust Auto-encoders, Ph.D. advisor
Zou, Xiaozhou, Adversarial Neural Networks, Master’s thesis
Spring 2017:
Bahadur, Nitish, Applications of non-linear dimension reduction to finance, Ph.D. advisor
Cinelli, Forrest, Balanced Matrices are Adjacency Matrices for d-regular Graphs, Undergraduate ISP
Gajamannage, Kelum, Non-linear dimension reduction, Postdoctoral mentor
Keller, Josh, Applying Robust Principal Component Analysis to Anomaly Detection in Car Networks, Masters Capstone
Li, Wenjing, Ensemble methods in machine learning, Ph.D. advisor
Liu, Haitao (co-advisor with Jian Zou), Graphical Models, Ph.D. advisor
Reese, Tyler Michael (co-advisor with Joseph D. Fehribach and Brigitte Servatius), Kirchhoff Graphs, Ph.D. advisor
Weiss, Matt, Supervised Machine Learning for Chemical Sensors, Ph.D. advisor
Zhong, Lu, Truncated norms for compressed sensing, Master’s thesis
Zhou, Chong, Robust Auto-encodes, Ph.D. advisor
Zou, Xiaozhou, Adversarial Neural Networks, Master’s thesis
Fall 2016:
Ali Benamara (co-advised with Mohamed Eltabakh <meltabakh@WPI.EDU>) Exabyte Scale Robust PCA
Bahadur, Nitish, Applications of non-linear dimension reduction to finance, Ph.D. advisor
Gajamannage, Kelum, Non-linear dimension reduction, Postdoctoral mentor
Li, Wenjing, Ensemble methods in machine learning, Ph.D. advisor
Liu, Haitao (co-advisor with Jian Zou), Graphical Models, Ph.D. advisor
Mukne, Neehar Clustering of Internet Nodes Using Latencies, Directed Research
Reese, Tyler Michael (co-advisor with Joseph D. Fehribach and Brigitte Servatius), Kirchhoff Graphs, Ph.D. advisor
Weiss, Matt, Supervised Machine Learning for Chemical Sensors, Ph.D. advisor
Zhong, Lu, Truncated norms for compressed sensing, Master’s thesis
Zhou, Chong, Robust Auto-encodes, Ph.D. advisor
Zou, Xiaozhou, Adversarial Neural Networks, Master’s thesis
Zou, Chen, Robust non-linear dimension reduction, Directed Research
Spring 2016:
Holmes, Andrew, Steps Toward Constructing Matrices that Satisfy the Restricted Isometry Property, Master's Capstone
El Gamal, Mostafa, Non-linear Dimension Reduction, Research Collaboration (non-credit)
Lama, Suman, Large Scale Processing of PCAP Datga, Directed Research
Li, Nan, Hypothesis Testing for Graphical Models, Master's thesis.
Li, Wenjing, Geolocation of Internets Nodes Using Robust PCA, Research Collaboration (non-credit)
Liu, Haitao (co-advisor with Jian Zou), Graphical Models, Ph.D. advisor
Kay, Kathleen, Inverse Methods for Non-linear Dimension Reduction, MQP.
Mukne, Neehar Clustering of Internet Nodes Using Latencies, Research Collaboration (non-credit)
Orr, Jonathan, Quality Control for Nano-tube Yarns, Master's Capstone (Funded by Nanocomp).
Reese, Tyler Michael (co-advisor with Joseph D. Fehribach and Brigitte Servatius), Kirchhoff Graphs, Ph.D. advisor
Yang, Fan, Using ADMM to Detect K-Sparse Vector, Directed research. (non-credit)
Zhou, Chong, Kernel Based Deep Learning, Master's thesis.
Data Science GQP Advisor, Seceon Corp.
Fall 2015:
Biradar, Rakesh Nagendra, eRPCA for robust prediction in graph communities. Master's thesis. (GRADUATED)
Holmes, Andrew. Steps Toward Constructing Matrices that Satisfy the Restricted Isometry Property, Master's Capstone
Li, Nan, Hypothesis Testing for Graphical Models, Master's thesis.
Pandey, Shivangi, Statistical Methods in Data Science, ISP.
Li, Wenjing, Geolocation of Internets Nodes Using Robust PCA (with Mukne, Neehar) Master's capstone.
Reese, Tyler Michael, Kirchhoff Graphs, Ph.D. advisor (co-advisor with Joseph D. Fehribach and Brigitte Servatius)
Yang, Fan, Using ADMM to Detect K-Sparse Vectors, Master's capstone.
Zhou, Chong, Kernel Based Deep Learning, Master's thesis (and entering Data Science Ph.D. program)
Summer 2015:
Amadeo, Lily Large Scale Matrix Completion and Recommender Systems, Master's thesis. (GRADUATED)
Biradar, Rakesh Nagendra, eRPCA for robust prediction in graph communities. Master's thesis.
Li, Nan, Hypothesis Testing for Graphical Models, Master's thesis.
Liu, Yingnan, Detecting Anomalies in Border Gateway Protocol Data, Master's capstone
Yang, Fan. Using ADMM to Detect K-Sparse Vectors, Directed research (non-credit)
Zhou, Chong. , Kernel Based Deep Learning, Master's thesis)
Spring 2015:
Biradar, Rakesh Nagendra, eRPCA for robust prediction in graph communities. Directed research.
Reese, Tyler Michael, Kirchhoff Graphs, Ph.D. advisor (co-advisor with Joseph D. Fehribach and Brigitte Servatius)
Rosales, Elisa R , Random Forests for prediction in healthcare data. Masters in Applied Statistics capstone project.