Graduate Student Success- Data Sciences
Stories from Graduates and Alumni
Share your success
Do you have a success to share with Marquette University's Graduate School? We'd love to hear from you. Tell us about your new job, presentation, publication, or any other award or honor you've recently received. We will post your story here and on the Marquette University Facebook and Twitter pages.
I want to share my success story
It was during the pursuit of his Ph.D. at Marquette University that Iain was first introduced to the field of MRI physics, which has since become the focus of his research career currently at Duke University. The Computational Sciences program exposed him to truly invaluable statistical and computational tools that enabled me to research the statistical impact of image reconstruction and processing algorithms frequently used in the field of functional MRI. The research training that Iain received at Marquette ultimately led him to pursue a postdoctoral associate position in MR Physics at Duke University’s Brain Imaging and Analysis Center, and he has since been promoted to a Medical Instructor position in the Department of Neurology.
As an extension of his prior research, his work at Duke has centered around the development of MRI acquisition and processing techniques for achieving diffusion tensor imaging data with ultra-high spatial resolution and fidelity. Specifically, his research has been applied to patients with intractable epilepsy - where no apparent abnormalities are present in conventional MR scans - and he has been working closely with neurologists and neurosurgeons to develop advanced MR tools for localizing epilepsy foci during presurgical planning.
"The tools and knowledge I gained at Marquette have been applied to every facet of my research here at Duke, and I would certainly not be in the position I am in now without them.", says Iain.
Christopher Beal, a doctoral student at Marquette University, was named Aurora Research Institute’s first Colton Scholar in Cardiology Research.
Beal, who is completing his doctorate in computational sciences, is developing software that aims to predict serious cardiac events in patients with hypertrophic cardiomyopathy using electrical activity of the patient’s heart.
“The software will use machine learning methods to recognize patterns in electrocardiograms,” Beal said. “The software will be designed specifically to aid the work of cardiologists, providing another tool to help them better identify high-risk patients and quickly determine the right course of treatment.”
The Colton Scholar program was made possible through a generous $1 million donation to Aurora Health Care Foundation. The fund, which is in honor of A. Jamil Tajik, MD, was created with the intention of providing a researcher the opportunity to advance understanding of cardiovascular disease under the mentorship of Tajik, who is the president emeritus of Aurora Cardiovascular Services and an internationally known cardiovascular disease expert.
“Our graduate program is designed to equip students with a distinctive blend of theoretical and computational skills, for employment in industry, research laboratories and institutions of higher education,” said Dr. Gary Krenz, a professor in the Department of Mathematical and Statistical Sciences and Beal’s doctoral research advisor. “Christopher’s research is an outstanding example of the important, challenging 21th century interdisciplinary problems that our students embrace. We are proud of the work that he is doing as his research could make a tremendous difference in people’s lives.”
Anmol is a Computational Sciences graduate student in the department of Mathematics, Statistics and Computer Science and a Research Assistant in the Parallel Computing Lab. His research work is focused in the area of High Performance Computing (HPC) where he spends his time speeding up algorithms and computational methods in scientific computing and data science.
Most of his current work is on boosting performance of Computational Geometry algorithms and GeoSpatial computations. In his journey as a graduate student in Marquette, his team won First Place in the “Hack It Till You Crack It” Data Science Hackathon organized by Northwestern Mutual.
Anmol was also was the winner of the “Deep Learning Challenge” organized by Marquette University Office of Statistical Consulting and Training. His paper, "OpenACC Based GPU Parallelization of Plane Sweep Algorithm for Geometric Intersection" received the best paper award in the Workshop on Accelerator Programming Using Directives (WACCPD) held in conjunction with The International Conference for High Performance Computing, Networking, Storage, and Analysis.
According to Anmol, "This would not have been possible without the tremendous support and guidance of my advisor - Dr. Satish Puri. I am also extremely thankful to the MSCS department for their help and inspiration."
Colin is presenting his paper, "Predicting Natural Gas Pipeline Alarms" at the International Symposium on Forecasting in Greece on June 16-19, 2019. His paper covers his research, forecasting alarms in natural gas pipelines. Dr. Richard Povinelli, Associate Professor of Electrical and Computer Engineering and Director of Computer Engineering Laboratories is Colin's adviser and has helped him achieve this success with teaching, patience, and encouragement.
Colin is currently pursuing his M.S. degree, but has been accepted into the Computer Science PhD program in Fall 2019.
Md Kamrul Hasan, is an Arthur J. Schmitt Leadership Fellow at Marquette University 2018-19 and a graduate student of Mathematics, Statistics, and Computer Science (MSCS) Department. As a fourth year PhD student in Computational Sciences program of MSCS department at Marquette, his research focuses on the development of a smartphone-based point of care tool to estimate the hemoglobin level noninvasively. The study considers two different approaches. For more information on Md Kamrul Hasan, please visit his graduate school web page.
Read more about Hasan's study
First, he is analyzing the lower eyelid-image data captured by different smartphones. His algorithm extracts the image pixel's color information and converts it to hyperspectral data to predict the clinically measured hemoglobin level. The project is funded by the National Institutes of Health (NIH).
Second, a 10-second fingertip-video captured under different (infrared) lighting conditions is processed for feature extraction. Deep Neural Network-based algorithm is applied to train the model for the hemoglobin level estimation. This project is funded by numerous grants from Ubicomp Lab, MSCS Department of Marquette. His recent work titled as “SmartHeLP: Smartphone-based Hemoglobin Level Prediction Using an Artificial Neural Network” is accepted in American Medical Informatics Association, 2018. His research has been published in Smart Health Journal on “Smartphone-based Human Hemoglobin Level Measurement Analyzing Pixel Intensity of a Fingertip Video on Different Color Spaces” in 2017.
Professor Sheikh Iqbal Ahamed, Chair of Computer Science and the director of the Ubicomp Lab is supervising Hasan's research work. Hasan's dissertation title is “BEst (Biomarker Estimation): Health Bio-marker Prediction Noninvasively, Ubiquitously and Frequently.” He has presented his work and attended workshops and conferences at other universities including Purdue, University of Chicago, Yale, Columbia, University of Southern California, and University of Colorado Boulder.
Drew presented at the 2018 Rehabilitation Engineering and Assistive Technology Society of North America in Washington D.C. on July 12-15. Her presentation received honorable mention in the student paper competition.
During her third year, Drew presented at the Rehabilitation Engineering and Assistive Technology Society of North America's national conference in Washington D.C. Drew presented two posters: Access Ruler: An Accessible Measurement Application for Determining Accessibility in the Built Environment and xFACT: Developing Usable Surveys for Accessibility Purposes. Access Ruler relies on using a laser ruler, in conjunction with an iOS application that obtains measurements taken by the ruler and stores them in a list. Pairing the laser ruler with the application is a single-button process. Access Ruler improves the accessibility of the process of measuring building features for accessibility, in addition to retaining accuracy and ease of use. xFACT is a desktop application designed to assist in deploying accessible, usable assessments. xFACT can create one survey for multiple types of assessments, and tailor it to the needs of the user with very little effort on their part, thus improving the assessment-taking process for determining accessibility, and other such uses.
Francine Robinson - Master's in Computing (Alumni)
Coming from a non-technical background, Marquette University’s Graduate program equipped me with the skills necessary to enter the IT workforce. After completing a vigorous IT boot camp, I was quickly immersed into courses, gaining knowledge in the areas of Network and System Administration, Business Systems, Database Systems, Enterprise Architecture, IoT, Computing, Security, and Predictive Analysis. During my educational tenure, I was given the opportunity to experience the variability that the IT field offers. Also, because Marquette used cutting edge technology, I was able to attend over half of my courses remotely, unknowingly preparing me for my current role as a Professional Business Systems Analyst in Application Engineering at Aurora Health Care, where I use the same technology to occasionally work remotely. Choosing Marquette was one of the best decisions that I have ever made, as I credit this program to helping me jump-start my career in IT!
Ricardo Franco - M.S. Computing, Specialization in Big Data and Data Analytics (Alumni)
As a Clinical Laboratory Scientist with an undergraduate degree in biology, I found that I really enjoyed analyzing data and desired a career where I could utilize my passion for healthcare and computer science. Marquette's graduate program allowed me the flexibility I needed to continue to work full time, take a wide range of classes and still complete my degree in two years. I was able to learn many of the most desired skills in the industry by professors whom were also professionals by trade with many years of experience in their respective fields. This allowed them the ability to relate material to their real world experiences, giving insights into the industry that I have since found to be invaluable. I am proud to say that right after graduating with an MS in Computing and specialization in Big Data & Data Analytics from Marquette University, I was able to obtain a mid-level Data Analyst position at the healthcare conglomerate, Kaiser Permanente in Denver, Colorado.
Piyush Saxena- Ph.D. in Computational Sciences (Alumni)
Coming from a Civil engineering background Marquette’s was one of the very few programs that allowed me to leverage my experience as an engineer to succeed in an analytical field without excessive coursework. During my time I was exposed to some of the best research labs and industry-academia collaborations. One such collaboration with Direct Supply evolved into what became a significant part of my dissertation. That industry connection took professional development to new heights for me. I was able to do novel research while being empowered by leaders in academia and industry. The Computational Sciences program provides a sound support structure while encouraging the flexibility that drives innovation. I currently work as a Data Scientist at Direct Supply in Milwaukee. Direct Supply is a Senior-Living industry juggernaut. Using Deep Learning to improve the lives for American seniors, that is what the program empowered me to do!