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Maribeth Bottorff is one of our three class-of-2016 undergraduate majors who went to work for Google. We are extremelly proud of her. At our request, she has written the short article below about her undergraduate experiences and her advice for getting a job at Google or other major tech companies.
My name is Maribeth Bottorff and I graduated in May 2016 with a Bachelor of Science in Computer Science from UofSC. In July, I started my full-time job as a software engineer with Google through their Engineering Residency, a rotational program for new graduates. When I tell people I work at Google, I get the same reactions: “Wow, you must be so smart!” or “Wow, how did you get that job?” or “Wow, that’s awesome!” Yes, it is awesome and, yes, I’m really excited about it. But, no, I am not a prodigy, though I have worked hard to get here. And now I’m going to tell you how I got the job.
We congratulate Dr. Ioannis Rekleitis for receiveing an NSF research award for his project titled "Enhancing Mapping Capabilities of Underwater Caves using Robotic Assistive Technology"
This project develops robotic assistive technologies to improve mapping capabilities of underwater caves. The project enables the practical construction of accurate volumetric models for water-filled caves. The technology of this robotic system can also be deployed on underwater vehicles enabling the autonomous exploration of caves and other underwater structures. Furthermore, the data and software, released under an open-source license, enable researchers to test algorithms on computer vision, state estimation, and sensor fusion, in challenging environments. The project integrates research and education through training graduate and undergraduate students and enhancing several graduate and undergraduate courses at the University of South Carolina.
Dr Jianjun Hu has received an equipment award from NVIDA corporation for his project on Breast Cancer Diagnosis with Deep learning based image and microarray analysis.
The main purpose of this project is to develop and apply methods in deep learning to solve problems in the emerging field of computational pathology of breast cancer using both large scale of histopathology images and microarray datasets. This project may lead to the development of novel data-driven diagnostic tools for cancer detection, risk prediction, and diagnosis.
The film Ward One: Reconstructing Memory captures the enduring memories of former residents of Ward One, a Columbia neighborhood lost to urban renewal, along with the efforts of faculty and students at the University of South Carolina to preserve their stories. It shows students in our Critical Interactives course building a mobile app that brings this past back to life.
We would like to congratulate our Discovery Day winners. Omar Ansari won a first place award for his poster "The use of remote telepresence in collegiate classrooms to facilitate eLearning". Steven Dao and Austin Pahl won a first place award for "Enhancing Interactor Experience in the Ward One App". Nicholas Weidner won second place for "Underwater Cave Mapping using Stereo Vision". Blakeley Hoffman won second place for "Cooperative Set Function Without Communication". Theodore Stone and Nathaniel Stone won an honarable mention for "Correlating a Smart Soccer Ball’s Impact Acceleration to Impact Force". Adel Alamri won an honarable mention for "Speech Signs - Signing with Children."
Dr. Gabriel Terejanu, along with Dr. Sourav Banerjee (Mechanical Engineering), Dr. Anindya Chanda and Dr. Robin Kloot (Environmental Health Sciences), has received an award from the Natural Resources Conservation Service (NRCS)/USDA for a data collection project with the title "Using Cover Crops and Soil Health to Reduce Crop Stress and Aflatoxin Contamination". As part of this project the researchers will deploy a sensor network to collect environmental data from a cornfield in collaboration with a local farmer. The data will be used to develop and demonstrate a predictive framework for calculating aflatoxin occurrence in South Carolina cornfields prior to harvest.