Dr. Rittika Shamsuddin aims to improve communication between researchers in fields of computer science, biology, and medicine via knowledge-sharing and by developing algorithms and experiments, which will increase the interpretability and generalizing ability of various machine learning and artificial intelligence models. Such libraries and developments are necessary for extending the technological success of computational fields to solve problems in healthcare/biology with a higher degree of trustworthiness and reliability than exists at present. She has multiple internal grants, published papers and is active in service.
Dr. Shamsuddin is also very passionate about computer science and programming and has been an active advocate for CS, especially among women, since her Ph.D. years. She believes that programming is a way of thinking and can be taught and learned through the use of the newer technology-based curriculum.
She obtained her Ph.D. from the University of Texas at Dallas on Analyzing and Synthesizing Healthcare Time Series Data for Decision-Support, where she worked in the Multimedia Systems Laboratory led by Prof. Balakrishnan. Before that, she graduated from Mount Holyoke College, with a double major in Biology and Computer Science, where her honor thesis included working on Using Rigidity Analysis To Identify Hinge Motion in Proteins under the supervision of Professor Audrey St. John.
Health informatics and information systems
Data mining and knowledge discovery
Data engineering and data science
I am always looking for bright, hard-working research students (undergraduate, Master, and/or Ph.D.), who can work independently, are eager to learn new skills, can synthesize information from different sources, work professionally, and preferably have a background in machine learning and data science.
I am happy to work on research with interested students at any educational level for independent studies, creative components, honors, and/or any other professional/educational research purposes. However, in order to obtain a research assistantship (if available), the students need to meet certain criteria.
Graduate student eligibility for research supervision (and/or research assistantship, if applicable):
1) Must be a CS Ph.D. student, who has satisfactorily passed one semester of CS 5070 with me, or a CS Master student enrolled in Master Thesis track.
2) The student must be enrolled in CS5070 for at least 3 credits per semester for the duration of employment. Based on the performance in the CS5070 position may be extended.
Note: While I am happy to work with Master students on their Creative Component, funds are not available to them.
Undergraduate student eligibility includes:
1) Eagerness to learn and do research
2) Spend at least 5-6hrs/week on research
3) Assistantships as student workers or other scholarships are sometimes available.
If interested, email me your CV and any other relevant information.