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Michael Ira Miller (born 1955) is an American biomedical engineer and neuroscientist and is a leading researcher in brain mapping in the field of  medical imaging at  the Johns Hopkins University. Miller is the Hershel Seder Professor of Biomedical Engineering and Johns Hopkins University Gilman Scholar. Miller is well known for his pioneering work in the field of computational anatomy  with Ulf Grenander. He is the Director of the Johns Hopkins Center for Imaging Science within the Whiting School of Engineering and is also Co-Director with Richard L. Huganir of the Johns Hopkins  Kavli Neuroscience Discovery Institute.

Biography
Miller did his undergraduate studies at The State University of New York at Stony Brook where he received his Bachelor of Engineering degree in 1976. He then joined the Department of Biomedical Engineering at the Johns Hopkins University, where he received his Master of Science degree in Electrical and Computer Engineering in 1978 and a Ph.D. degree in Biomedical Engineering in 1983.

Following his Ph.D., Miller joined the Biomedical Computer Laboratory at Washington University in St. Louis to work on Medical imaging with Donald L. Snyder, then chair of Electrical Engineering at Washington University School of Engineering and Applied Science. Miller joined the faculty of Electrical Engineering in 1985 and remained on the faculty at Washington University through 1998 as the Newton R. and Sarah Louisa Glasgow Wilson Professor in Engineering. . During this period, Miller did several sabattical years as a visiting professor to the Brown University Division of Applied Mathematics to work with Ulf Grenander on image analysis.

In 1998 Miller joined the Department of Biomedical Engineering  at  Johns Hopkins University where he has remained as the Herschel and Ruth Seder Professor of Biomedical Engineering and the Director of the Center for Imaging Science ,  one of the nations premier groups in image analysis. In March of 2011, Miller was appointed by President Ronald J. Daniels and then Provost Lloyd B. Minor as one of 17 inaugural University Gilman Scholars selected across all divisions of the University , recognizing the scholars as having represented the highest ideals of the University in demonstrating distinguised records in research, artistic achievement, creativity, teaching and service.

In 2015, Miller was selected as the Co-director of the newly awarded Kavli Institute for Discovery Neuroscience.

Michael Miller is a fellow of the American Institute for Medical and Biological Engineering, and a senior member of the Institute of Electrical and Electronics Engineers.

Early Years in Neural Coding at Johns Hopkins
Miller's did his Ph.D. work with Murray B. Sachs and Eric D. Young in the Neural Encoding Laboratory at Johns Hopkins University working on neural codes in the Auditory system. Other graduate students in the lab with Miller were Patrick Barta, Pete Bernardin, Dan Gibson, Thomas Schalk, Herbert Voigt, Raimond L. Winslow.

Miller and Sachs focussed their work on   rate - timing   population codes of complex, speech features including voice-pitch and consonant-vowel syllables demonstrating representations of their spectral-temporal discharge patterns distributed across the primary  auditory-nerve. These neural codes formed the basis for the discussions at the 1982 New York Academy of Science meeting on efficacy and timeliness of Cochlear implants.

Early Years in Medical Imaging at Washington University
Miller's impact in the field of brain mapping in Medical imaging, specifically statistical methods  for  iterative image reconstruction began in the mid 80's when he joined Donald L. Snyder at Washington University to work on time-of-flight positron emission tomography (PET) systems being instrumented in Michel Ter-Pogossian's group. Miller's noteable contribution working with Snyder was to stabilize likelihood-estimators of radioactive tracer intensities via the  method-of-sieves . This became the main approach for controlling noise artifacts in the context of low count, time-of-flight emission tomography.

It was during this period that Miller met Lawrence (Larry) Shepp, with Miller visiting Bell Laboratory several times to speak as part of the Henry Landau seminar series. Shepp remained a mentor and friend throughout Miller's career.

The Pattern Theory Era and Computational Anatomy
Miller joined the Pattern Theory group at Brown University in 1993 during a sabattical from Washington University to work with Ulf Grenander on problems in image analyis within the Bayesian framework of Markov random field models. Their first noteworthy work together was on the ergodic properties of jump-diffusion processes for inference in  hybrid parameter spaces, which was delivered by Miller at the Journal of the Royal Statistical Society as a  discussed paper. This was the first class of random sampling algorithms defined with ergodic properties proven to sample from distributions supported across discrete sample spaces and supported over the continuum, likening it to the extremely popular Gibb's sampler of Geman and Geman as well as more classical diffusion based samplers associated to Langevin dynamics.

They continued their work together for approximately 15 years after the first sabattical year, with Miller supported as a visiting professor in the Division of Applied Mathematics at Brown. The Millers joined the Grenanders several summers in Sweden at the Grenanders' house in Vastervik, and staying at the Mittag-Leffler Institute in Stockholm as well. During this period, the two worked on linguistic structures and Unification grammars attempting to extend the random field models of Pattern theory to probabilistic structures that exploit the conditional probabilities of directed acyclic graphs. Grenander had modeled the generative theories of Noam Chomsky having published on entropies of Context-Free languages as part of his early work with the Brown Linguistics group, this providing an early bridge for Miller to the Grenander pattern theory school through his own efforts on entropies of the super-critical branching processes.

The two started their work together on human shape and form during this period. Grenander had already published influential papers on deformable templates for hands ; Miller published with Gary Christensen and Richard Rabbitt on the use of flows for dense  template or image matching. Computational anatomy was introduced as a formal theory of human shape and form in the May 1997 lecture given by Grenander and Miller at the 50th Anniversary of the Division of Applied Mathematics at Brown University, and subsequent publication. In the same year with Paul Dupuis, they published the foundational paper establishing the necessary Sobolev smoothness conditions requiring vector fields to have strictly greater than two generalized derivatives (in space of 3-dimensions) which are square-integrable, to ensure that smooth submanifold shapes are carried smoothly by the flows.

Collaborating with the French on Shape and Form
David Mumford appreciated the smoothness results on existence of flows, and encouraged Miller and the French group at École normale supérieure de Cachan who had been working independently to collaborate. In 1998, Mumford organized the Trimestre "Questions Mathématiques en Traitement du Signal et de l'Image" at the Institute Henri Poincaré, out of which emerged the collaborations between Miller, Trouve and Younes on shape which continue to date. The earliest equations on geodesics generalizing the Euler equation on fluids supporting localized scale (compressible) appeared, ,the diffeomorphometry metric first appeared implying a metric structures for shape and form, and subsequenlty the conservation of momentum law. This completed the generative theory of Computational anatomy since the random orbit model could be defined as shoots of the geodesic. The Hamiltonian formalism was subsequently described.

Contributions to Brain Mapping
The Computational anatomy framework establishing high-dimensional brain mapping at the morphological scale of MRI became the defacto standard for cross-section analyses of populations being studied via MRI at 1 mm. Numerous codes now exist for diffeomorphic template or atlas mapping, with many codes now available such as ANTS, DARTEL, DEMONS, LDDMM, StationaryLDDMM, all actively used codes for constructing correspondences between coordinate systems based on sparse features and dense images.

While at Washington University, Miller started a long-term research program with John Csernansky, working on the neuroanatomical phenotyping of Alzheimer's disease, Schizophrenia and mood disorder. In 2005, they published with John Morris an early work on predicting conversion to Alzheimer's disease based on clinically available MRI measurements using the diffeomorphometry technologies. This was one of the papers influencing the recommendations of the working group to include MR based morphometry markers of medial temporal lobe structures for consideration in clinical diagnosis. In 2014, with Marilyn Albert and Laurent Younes, the Johns Hopkins University BIOCARD, team led by Marilyn Albert demonstrated that the original Braak staging of earliest change associated to the entorhinal cortex in the medial temporal lobe could be demonstrated via diffeomorphometry methods in the population of clinical MRI's , and subsequently that this could be measured via MRI in clinical populations upwards of 10 years before clinical symptom. This has the potential to impact clinical treatment of the disease.

Selected works
Miller has published two books, the first with Donald L. Snyder, the second with Ulf Grenander.