Digital Signal Processing Group :: Professor Alan V. Oppenheim
Internal Link
Link: About DSPG Link: Research Link: People Link: Publications Link: Partners & Affiliations
Professor Alan V. Oppenheim
Faculty
Staff
Students
Visitors and Affiliated Scientists
Alumni
People > Visitors and Affiliated Scientists
 

Tom Baran

Research Affiliate and Visiting Lecturer

Dr. Baran is currently a Research Affiliate in the RLE Digital Signal Processing Group, and a Visiting Lecturer in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. He is also an MITx fellow. He received the S.B. degree (summa cum laude) in electrical engineering and in biomedical engineering from Tufts University in 2004 and the M.S. degree in electrical engineering from MIT in 2007. He performed his Ph.D. thesis research at MIT with Prof. Oppenheim, receiving the Ph.D. degree in 2012. Dr. Baran has significant experience in both teaching and research in signal processing. His research interests lie in the general field of signal processing theory and in signal-flow architectures for distributed signal processing, and his interests often tend toward acoustic applications. He is also author of Autotalent, a widely used open-source library for musical pitch correction.

Dr. Baran was awarded the MIT School of Engineering Graduate Student Extraordinary Teaching and Mentoring Award in 2011, and in 2010 was awarded the MIT EECS Carlton E. Tucker Award for Teaching Excellence. He also received Best Student Paper at the 2011 IEEE DSP Workshop and in 2006 was awarded the MIT EECS Morris J. Levin Award for Outstanding Oral Thesis Presentation. Dr. Baran is a member of IEEE, Eta Kappa Nu, Tau Beta Pi and Sigma Xi.

http://tombaran.info/

 

Petros Boufounos

Affiliated Scientist

 


 

Sefa Demirtas

Affiliated Scientist

sefademirtas@gmail.com

Sefa Demirtas received the B.Sc. degree in electrical and electronics engineering (summa cum laude) from Bogazici University in Istanbul, Turkey, in 2007 and the M.Sc. and Ph.D. degrees in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT), Cambridge, MA, in 2009 and 2014, respectively. While at MIT, he was a Research Assistant with the Digital Signal Processing Group (DSPG) and he held several Teaching Assistant positions in the EECS department mainly in graduate and undergraduate level signal processing classes. He has had summer internships in Computational Biomedicine Lab in University of Houston, Procter & Gamble and Nitronex Corporation.

Dr. Demirtas is currently a Research Scientist at Analog Devices Lyric Laboratories in Cambridge, MA. His current research interests lie broadly in signal processing and statistical inference and learning.

 

Dan E. Dudgeon

Affiliated Scientist


Dr. Dan E. Dudgeon has been active in the fields of image processing, array signal processing, multidimensional signal processing, and target recognition for over forty years. He is currently retired. From 2002 to 2011, he was a senior principal systems engineer with BAE Systems' Signal Processing Technology department, working on developing signal processing techniques for distributed sensing and distributed communications applications. From 1979 through 2002, he participated in and supervised various research programs in multidimensional signal processing and machine vision at the MIT Lincoln Laboratory, including work on an experimental target recognition system for
laser radar imagery and model-based target recognition algorithms for synthetic aperture radar data. From 1974 through 1978, he worked at Bolt, Beranek, and Newman, Inc., Cambridge MA, developing algorithms for processing underwater acoustic signals and tracking acoustic targets.

In addition to numerous papers on multidimensional signal processing and automatic target recognition, he co-authored "Two-Dimensional Digital Filtering" in the Proceedings of the IEEE, which was awarded the 1976 IEEE Browder J. Thompson Memorial Prize. He also co-authored the texts "Multidimensional Digital Signal Processing", published by Prentice-Hall in 1984, and "Array Signal Processing: Concepts and Methods", published by Prentice-Hall in 1993.


Because of his contributions to the field of multidimensional signal processing, Dr. Dudgeon was named a Fellow of the IEEE in 1987. In 1988 he was named a Distinguished Lecturer of the IEEE Acoustics, Speech, and Signal Processing Society. He was a charter member of the IEEE Signal Processing Society's Technical Committee on Multidimensional Signal Processing, and during 1986-7 he served as its chairman. He also served as Secretary of the IEEE Signal Processing Society from 1988-91 and on its Board of Governors from 1995-96.


Dr. Dudgeon was educated at the Massachusetts Institute of Technology, receiving both Bachelor's and Master's degrees in Electrical Science and Engineering in 1970. As a graduate student he was affiliated with the Digital Signal Processing Group of the MIT Research Laboratory of Electronics as well as the MIT Lincoln Laboratory, receiving the Doctor of Science degree specializing in Signal Processing in 1974.

 

Charles Rohrs

Affiliated Scientist

Charlie Rohrs received his BS degree from Notre Dame in 1976 and his Masters and PhD from MIT in 1978 and 1982 respectively. He served on the faculty at the University of Notre Dame from 1982 until 1997 and a Visiting Professor at MIT from 1997 until 2000. Charlie spent much of his career at The Tellabs Research Center, the research arm of Tellabs Operations, Inc., a manufacturer of telecommunications equipment for public service network providers. From 1985 until 1995, Dr. Rohrs was Director of the Research for Tellabs as the company grew from sales in the tens of millions to over a billion dollars in sales. In 1995, he became the first Tellabs Fellow. From 2001 to 2009, Charlie has worked at MIT, first as a Principal Research Scientist in the Laboratory for Information and Decision Systems (LIDS) and then in the DSP group in RLE.

While Dr. Rohrs is best known for his early contributions to the study of robustness in adaptive control, he has also contributed work in adaptive control, adaptive signal processing, communication theory, and communication networks. He has been active in analyzing and designing traffic control schemes for communication networks. In this area, his work was among the first to apply the techniques of linear control theory to such schemes. He has recently become interested in the problems of switching algorithms and large sensor networks.

 

James Ward

EECS Lincoln Lecturer

Dr. James Ward is Assistant Head of the Communication Systems Division at MIT Lincoln Laboratory.  He helps direct a portfolio of programs spanning technology development, architecture definition, analysis and prototyping to advance the nation's communications capabilities.  This portfolio spans satellite communications, robust tactical networks, laser communications and communications-related sensing. Dr Ward also holds a Lincoln Lecturer postion with the MIT EECS Department where he teaches graduate courses in digital signal processing and radar.

Dr. Ward is an author of over 25 papers and a widely referenced technical report on space-time adaptive processing.  He is a Fellow of the IEEE and a recipient of the MIT Lincoln Laboratory Technical Excellence Award.  In 2003, he received the IEEE Aerospace and Electronic Systems Society Fred Nathanson Young Radar Engineer Award for contributions to adaptive radar and sonar signal processing. He is a past member of the National Academy Naval Studies Board and has served the Air Force Scientific Advisory Board. Dr Ward hold a BS degree from the University of Dayton, and MS and PhD degrees in electrical engineering from The Ohio State University.

Home / About DSPG / Research / People / Publications / Partners & Affiliations © Massachusetts Institute of Technology
Link: Research Laboratory of Electronics at MIT Link: Department of Electrical Engineering and Computer Science    Link: Massachusetts Institute of Technology