Update as of 2/22/16: The program title has changed for Master of Engineering in Biomedical Engineering to Master of Engineering in Biomedical Innovation.
To continue to offer degrees that make School of Engineering & Applied Science graduates competitive in the workplace, the school is offering two new master's degrees and a new graduate certificate starting this year.
A Master of Engineering in Biomedical Engineering, a 12-month, 30-credit program, will be offered beginning June 1 and is targeted to recent graduates with a bachelor's degree in engineering or physics. The program, to be known as Translation and Entrepreneurship in Engineering to Advance Medicine, or TE2AM, is designed to fulfill an unmet need — locally, nationally and internationally — for master's level programs to train engineers in the specific skills and distinctions of innovation, design and entrepreneurship in the biomedical field. Students will spend the summer semester identifying a medical problem, conducting market analysis and forming teams. In the fall semester, students will develop the product and business processes along with core engineering skills; then in the spring semester, they will cover advanced manufacturing techniques, how to bring the product to market and end by creating a working prototype.
Students will participate in a yearlong, 12-unit practicum, create a federal grant application for initial funding, complete a patent application and develop a business plan. They will integrate with the clinical and research community at the School of Medicine, the Olin Business School and industry to identify needs and develop medical solutions that will impact patient care.
"Once students complete this program, they will have a skill set comparable with engineers with multiple years of industry experience and will be competitive to join an existing medical device or biotechnology company or create a new startup company," said Steven C. George, MD, PhD, chair of the Department of Biomedical Engineering.
The Master's in Engineering Data Analytics and Statistics, offered through the Preston M. Green Department of Electrical & Systems Engineering and the Department of Mathematics in Arts & Sciences, is a 30-credit program targeted to recent graduates with a bachelor's degree in math, statistics or engineering, though other backgrounds are welcome. It is designed to prepare students to manage "Big Data" at companies that handle huge amounts of data, a rapidly growing need in credit card, insurance and tech companies.
The program has several tracks to appeal to students' different interests and goals, including a statistics track and an optimization and decision theory track. All tracks will share foundation courses in probability and statistics, computation and optimization.
"Students who complete this program will be prepared for careers that use statistical techniques to make informed decisions based on data analysis," said Martin Arthur, director of the program. "The combination of skills and knowledge provided through coursework will bridge the divide between statistics and optimization."
In addition, the Department of Computer Science & Engineering is offering a new graduate Certificate in Data Mining and Machine Learning, awarded in conjunction with a master's in computer science. The certificate program requires two courses: Machine Learning (CSE 517A) and Advanced Algorithms (CSE 441T/541T). In addition, students must take at least three foundations courses and one applications course.
"The availability of large-scale data, together with the emergence of powerful new computational techniques, has unlocked tremendous opportunities across disciplines as diverse as science, medicine and business," said Roch Guerin, PhD, chair of the Department of Computer Science & Engineering. "The certificate in Data Mining and Machine Learning combines in-depth coverage of the algorithmic foundation of data mining and machine learning with extensive hands-on experience using modern computational tools and applications. In completing the certificate, students acquire computational and algorithmic skills that uniquely position them to successfully tackle today's big data problems."