Prior to joining Michigan Tech in 2012, Tim was an NSF/CRA Computing Innovation Fellow at Michigan State University (MSU) and a Research Associate at the University of Missouri (MU). At MSU, Dr. Havens developed machine-learning methods for clustering in large heterogeneous data sets. His work at MU focused on multi-modal data fusion and detection algorithms and fuzzy clustering. Before working on his Ph.D., he was an Associate Technical Staff at MIT Lincoln Laboratory, where he analyzed airborne directed energy systems, laser-illuminated target ID systems, and GPS signals in support of the U.S. Air Force. His interests include mobile robotics, explosive hazard detection, heterogeneous and big data, fuzzy sets, and sensor networks, and data fusion. He has coauthored over 80 technical publications and is an Associate Editor of the IEEE Trans. Fuzzy Systems. He has been funded by Michigan DOT, USDOT, US Army, NSF, the RAND/John A. Hartford Foundation, and the Leonard Wood Institute.