ERSP | 2016-2017 Projects
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Andrew Kahng group

Working on text-to-speech conversion for one of Prof. Kahng’s classes. Their work involves synthesizing speech based on the text given, and the sound files of the speaker.

Current Students

Meiyi He, Siya Li, Lusha Li
Mentor

Prof. Andrew Kahng

Dean Tullsen group

Working on improving performance and efficiency in computing by using the principles of Approximate Computing. They are using Pin (a tool to insert code in a program to analyze its performance) to find values that remain unchanged, or have changed by an insignificant amount, in order to reduce redundant computations and increase efficiency.

Current Students

Zhiran Chen, Vivian Lam, Yuxuan Zhang
Mentor

Prof. Dean Tullsen, Atieh Lotfi

Debashis Sahoo group

Building a database that includes patients with different types of cancers that are related to brain metastasis. They are focusing only on the brain metastasis related data in order to identify patterns that may establish links between genes and brain metastasis.

Current Students

Yutong Qiu, Joyce Fang, James Jiang, Shijie Fan
Mentor

Prof. Debashis Sahoo

Ilkay Altintas group

Working on integrating Kepler (an open-source application for workflows), on the XSEDE environment. Their work majorly involves running four basic workflows on the virtual machine, and give the documentation of all the problems faced, in order to facilitate the smooth use of Kepler on XSEDE resources and minimize the number of problems faced by scientists using Kepler.

Current Students

Kevin Khuong, Amanda Smith, Parth Shah, Robert Eaton
Mentor

Dr. Ilkay Altintas, Shweta

Julian McAuley group

Their project involves recommending the type of workout a user should follow using machine learning techniques, based on the user’s data like health condition, etc. and other parameters such as speed, altitude, etc.

Current Students

Shuo Li, Zhizhen Qin, Shuai Huang
Mentor

Prof. Julian McAuley

Rob Knight group

Using different machine learning techniques to distinguish obese from lean individuals. The key feature they are using is gut microbiota, which has been shown to be an important factor in determining the success of bariatric surgery. They are working on replicating existing studies, and possibly enhancing the results of the studies.

Current Students

Shweta Kinger, Barbara He, Xiaobin Lin, Victoria Tom
Mentor

Prof. Rob Knight

Ryan Kastner group

They are working on using augmented reality for robotic minimally invasive surgery. Their work involves performing scans on pig liver, and writing code to find the overlap between the actual 3-D image and the reconstructed 3-D image.

Current Students

Eduardo Tapia, Brendon Chen, Xinyi Yang
Mentor

Prof. Ryan Kastner, Michael Barrow

Sorin Lerner group

Working on analyzing quadcopter failures by using different machine learning techniques and comparing them to get the optimal output. The classification of the failure of a quadcopter will depend on several features like the yaw, pitch and roll, altitude of the quadcopter, etc.

Current Students

Jiayin Wang, Purisa Jasmine Simmons, Lichen Zhang, Catherine Lin
Mentor

Prof. Sorin Lerner

Steven Swanson group

Conducting a user study to test the effectiveness of Tazi, an interface to program robots. They are performing user studies with participants having different abilities and experience in coding (ranging from novice to expert programmers).

Current Students

Allison Reiss, Erick Soto, Jingxuan Wei, Isaiah Aponte
Mentor

Prof. Steven Swanson

Tajana Rosing group

They are working on mapping abnormal air quality changes, specifically on obstacle detection and modeling air quality. For this purpose, they are testing different sensors to measure accuracy and ensure robustness. They are also working on choosing subgroups of sensors that can accurately predict the values of the other sensors to model air quality efficiently.

Current Students

Jonathan Luck, Woojin Cheon, Robin Osekowsky, Joshua Ramos
Mentor

Prof. Tajana Rosing