Division of Sleep Medicine @ Harvard Medical School
Trainee Profile
Dennis A. Dean
Computational Research Associate, Division of Sleep Medicine, Department of Medicine, Brigham and Women's Hospital
Other Affiliation(s)
University of Massachusetts, Doctoral Student
Address
Division of Sleep Medicine, Brigham and Women's Hospital221 Longwood Avenue - RF Room 486 L
Boston, MA 02149
USA
Phone 617-525-6709
Fax 617-264-6875
Email ddean@rics.bwh.harvard.edu
Society Memberships
Society for Industrial and Applied MathematicsAssociation of Multi-Cultural Members of Partners
Latinos in Information Sciences and Technology Association
IEEE Engineering in Medicine and Biology Society
Institute of Electrical and Electronics Engineers
Society for Research on Biological Rhythms
Research Unit(s)
Analysis and Modeling Group, Division of Sleep Medicine, Brigham and Women's Hospital
Neuroscience Statistics Laboratory, Massachusetts General Hospital - Massachusetts Institute of Technology
Machine Learning Group, Department of Computer Science, University of Massachusetts (Director, Gary Livingston, PhD)
Neuroscience Statistics Laboratory, Massachusetts General Hospital - Massachusetts Institute of Technology
Machine Learning Group, Department of Computer Science, University of Massachusetts (Director, Gary Livingston, PhD)
Research Interests
I am interested in problems that integrate mathematical, computer science, and experimental techniques into a common analytic framework.
Biomathematical Modeling Unit
My work prior to starting graduate school falls into two broad categories:
(1) Model development and refinement, and
(2) Simulation methods and schedule optimization. The work that is uniquely my own are methods I have been developing to design and optimizing schedules base on models of circadian phase and neurobehavioral performance. I recently developed the circadian adjustment method which given a shifting sleep/wake schedule and/or non-24 hour day automatically determines optimum countermeasure placement.
Neuroscience Statistics Research Laboratory
My area of study is EEG/MEG source localization. As a starting point, I am studying the Minimum Norm Estimate (MNE); which is one method of constraining source localization to the cortical surface. Components of the EEG/MEG source localization problem currently under investigations are (1) methods for determining source confidence intervals, and (2) methods for automatically organizing, distributing, and paralyzing large imaging computations.
Pulse Analysis: The use of Markov Chain Monte Carlo techniques to fit a biophysical model of hormone secretion to data. The techniques under development can be used to determine biophysical parameters (i.e. secretion and decay rate) and parameter confidence intervals. The advantage of the techniques under development is the determination of hidden state variables such as the number of pulses.
Machine Learning Group
In my Master's work I, studied the use of Machine learning to automatically derive models from experimental data. Specifically, I studied the use of Bayesian networks in identifying model structures that capture the dynamics present in the data. Bayesian networks where selected because its graphical interpretation provides a natural framework for which to communicate models to biologists.
Biomathematical Modeling Unit
My work prior to starting graduate school falls into two broad categories:
(1) Model development and refinement, and
(2) Simulation methods and schedule optimization. The work that is uniquely my own are methods I have been developing to design and optimizing schedules base on models of circadian phase and neurobehavioral performance. I recently developed the circadian adjustment method which given a shifting sleep/wake schedule and/or non-24 hour day automatically determines optimum countermeasure placement.
Neuroscience Statistics Research Laboratory
My area of study is EEG/MEG source localization. As a starting point, I am studying the Minimum Norm Estimate (MNE); which is one method of constraining source localization to the cortical surface. Components of the EEG/MEG source localization problem currently under investigations are (1) methods for determining source confidence intervals, and (2) methods for automatically organizing, distributing, and paralyzing large imaging computations.
Pulse Analysis: The use of Markov Chain Monte Carlo techniques to fit a biophysical model of hormone secretion to data. The techniques under development can be used to determine biophysical parameters (i.e. secretion and decay rate) and parameter confidence intervals. The advantage of the techniques under development is the determination of hidden state variables such as the number of pulses.
Machine Learning Group
In my Master's work I, studied the use of Machine learning to automatically derive models from experimental data. Specifically, I studied the use of Bayesian networks in identifying model structures that capture the dynamics present in the data. Bayesian networks where selected because its graphical interpretation provides a natural framework for which to communicate models to biologists.
Mentor(s)
Emery N. Brown, MD, PhD; Elizabeth Klerman, MD, PhD; Gary Livingston, PhD
Teaching
Interactive Lecture and Computer Laboratory. Using the Circadian Performance Simulation Software to Understand Circadian rythmns and Performance. Presented as part of the Chautauqua Short Course Program sponsored by the National Science Foundation. (2003 -2006)
Lecture. Using Simulations in Circadian Research. Presented at Circadian Biology: From Cellular Oscillators to Sleep Regulation (MCB 186), Department of Cellular and Molecular Biology, Harvard College (2003)
Lecture. Using Simulations in Circadian Research. Presented at Circadian Biology: From Cellular Oscillators to Sleep Regulation (MCB 186), Department of Cellular and Molecular Biology, Harvard College (2003)
Related Links
Home Page
CV (pdf, 63kb)
Honors and Awards
2007 Best Modeling Poster Presentation award at the Conference for African American Researchers in the Mathematical Sciences
2006 Partners Healthcare Service Award
2005 Association of Multi-cultural Members at Partners Educational Scholarship
2005 Travel Sponsorship, Case Studies in Bayesian Statistics 8
2002 Trainee Research Merit Award, Association of Professional Sleep Societies Meeting
2001 First Time Travel Award, Association of Professional Sleep Societies Meeting
1999 Inducted into Upsilon Pi Epsilon, Computer Science Honor Society
1999 Northeastern University Minority Research Fellowship
1998 Northeastern University Research Fellowship
Home Page
CV (pdf, 63kb)
Honors and Awards
2007 Best Modeling Poster Presentation award at the Conference for African American Researchers in the Mathematical Sciences
2006 Partners Healthcare Service Award
2005 Association of Multi-cultural Members at Partners Educational Scholarship
2005 Travel Sponsorship, Case Studies in Bayesian Statistics 8
2002 Trainee Research Merit Award, Association of Professional Sleep Societies Meeting
2001 First Time Travel Award, Association of Professional Sleep Societies Meeting
1999 Inducted into Upsilon Pi Epsilon, Computer Science Honor Society
1999 Northeastern University Minority Research Fellowship
1998 Northeastern University Research Fellowship
Selected Publications
Dean II DA, Fletcher A, Hursh SR, Klerman EB. Developing Mathematical Models of Neurobehavioral Performance for the "Real World".
J Biol Rhythms. 2007; 22:246-258. [PMID: 17517914]
Indic, P, Forger, DB, M.A. St. Hilaire, Dean II, DA, Brown, EN, Kronauer, RE, Klerman, EB, Jewett, ME, Comparison of amplitude recovery dynamics of two limit cycle oscillator models of the human circadian pacemaker.
Chronobiology International. 2005;22(4):613-29. [PMID: 16147894]
Forger, D.B., Dean II, D.A., Gurdziel, K., Leloup, J-C., Lee, C., von Gail, C. , Etchegary, J-P., Kronauer, R.E., Goldbeter, A., Peskin, C. S., Jewett, M.E. and Weaver, D.R. Development and Validation of Computational Models for Mammalian Circadian Oscillators.
OMICS. 2003 Winter;7(4):387-400. [PMID: 14683611]
J Biol Rhythms. 2007; 22:246-258. [PMID: 17517914]
Indic, P, Forger, DB, M.A. St. Hilaire, Dean II, DA, Brown, EN, Kronauer, RE, Klerman, EB, Jewett, ME, Comparison of amplitude recovery dynamics of two limit cycle oscillator models of the human circadian pacemaker.
Chronobiology International. 2005;22(4):613-29. [PMID: 16147894]
Forger, D.B., Dean II, D.A., Gurdziel, K., Leloup, J-C., Lee, C., von Gail, C. , Etchegary, J-P., Kronauer, R.E., Goldbeter, A., Peskin, C. S., Jewett, M.E. and Weaver, D.R. Development and Validation of Computational Models for Mammalian Circadian Oscillators.
OMICS. 2003 Winter;7(4):387-400. [PMID: 14683611]
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