Raj Nadakuditi, associate professor of electrical engineering and computer science, has been named the 2021 recipient of the Ernest and Bettine Kuh Distinguished Faculty Award for his outstanding contributions in the area of computational data science and machine learning.
Nadakuditi’s research occurs at the interface of statistical signal processing, machine learning and random matrix theory, with applications such as sonar, radar, wireless communications and optics. An important component of his work is the application of his work to real-world settings, in particular, interpreting very low-level signals from sensors or finding patterns and useful information big data. Examples of his research include using visible light to image inside the body, and multi-modal fusion of diverse information sources to tease out meaningful data.
In recent years, Raj has devoted himself to democratizing education in the computational sciences. He created the graduate level course “Computational Data Science and Machine Learning” that attracts hundreds of students from more than 60 different majors across the university. Through development of this course, he co-created a new way to teach computational science, via a software platform called Mynerva, that gives instructors the tools to write cloud-based interactive textbooks targeted to their own specific subject matter. He co-founded the company Mynerva, Inc. with recent EECS alumnus Travis DePrato.
He also created the online platform, Continuum, which provides high-quality online education in areas of high demand in industry. He is currently teaching courses in Computational Machine Learning, Applied Computational Linear Algebra for Everyone, and a new course called “The Joy of Coding” designed especially for individuals, including high school students, who may be new to coding.
Within Electrical and Computer Engineering, he works tirelessly on behalf of all graduate students to make them feel welcome, and to keep students in his general area of signal processing engaged through low-key seminars, which contribute greatly to their professional development. He has also developed methods to enhance recruiting of potential graduate students as well as faculty members to Michigan, with a special focus on underrepresented individuals.
Nadakuditi has co-chaired numerous professional workshops, and co-developed the Michigan Summer School on Random Matrix Theory. He has received a Young Investigator Award from the Office of Naval Research, the Air Force Office of Scientific Research, and the Defense Advanced Research Projects Agency.
About the Ernest and Bettine Kuh Distinguished Faculty Award
Ernest and Bettine Kuh established the Ernest and Bettine Kuh Distinguished Faculty Award to recognize an outstanding young faculty member for their teaching, research, and service. The award includes an annual stipend.
Ernest Kuh (1918-2015) graduated from Michigan with his bachelor’s degree in electrical engineering in 1949. He then received his master’s and doctoral degrees in electrical engineering from Stanford University. A pioneer in electronic circuit theory, he is widely considered one of the fathers of electronic design automation (EDA).