Dan Klein

Sr. Research Manager

Dan Klein

Sr. Research Manager


Daniel J. Klein has a Ph.D. in Aeronautics and Astronautics from the University of Washington, Seattle, where he also obtained a Master of Science. He also has a Bachelor of Science (Honors) in Mechanical Engineering from the University of Wisconsin, Madison, where his undergraduate thesis described the design and implementation of automated processing algorithms for retinal fundus and scheimpflug image analysis. Previous to IDM, Daniel was a postdoctoral scholar in the Electrical and Computer Engineering department at the University of California, Santa Barbara, where he worked on the theory and practice of multi-agent control systems. Daniel’s past research includes coordinated control of unmanned aerial vehicles, distributed estimation leveraging cycles in the measurement topology, and infection-like information propagation in mobile ad-hoc networks. His work also includes the development of a nonlinear phase-coupled oscillator theory that enabled a group of airplane-like vehicles to track a target in a coordinated manner, which was demonstrated using a small school of free-swimming robotic fish. Additional areas of research have included information propagation in delay-tolerant networks, sensor-guided flight, coordinated target tracking, acoustic source localization, computer vision systems, optimization, medical image processing, and distributed state estimation. As a member of IDM’s research team, Daniel’s time is split between developing the HIV model and building research tools. His HIV work focuses on building the contact network using ideas from feedback control to guide the dynamical relationship formation process. He is exploring structural assumptions in HIV modeling, HIV model calibration, the impact of interventions, and parameter sensitivity. The research tools he is developing allow researchers to run simulations in parallel on a supercomputer and view the results, as well as to explore large parameter spaces to find interesting regions, and to calibrate model parameters. In his spare time, Daniel guest lectures at the University of Washington, participates in the HIV Modeling Consortium and other related groups, and is a frequent presenter at conferences.

Biography

Daniel J. Klein has a Ph.D. in Aeronautics and Astronautics from the University of Washington, Seattle, where he also obtained a Master of Science. He also has a Bachelor of Science (Honors) in Mechanical Engineering from the University of Wisconsin, Madison, where his undergraduate thesis described the design and implementation of automated processing algorithms for retinal fundus and scheimpflug image analysis. Previous to IDM, Daniel was a postdoctoral scholar in the Electrical and Computer Engineering department at the University of California, Santa Barbara, where he worked on the theory and practice of multi-agent control systems. Daniel’s past research includes coordinated control of unmanned aerial vehicles, distributed estimation leveraging cycles in the measurement topology, and infection-like information propagation in mobile ad-hoc networks. His work also includes the development of a nonlinear phase-coupled oscillator theory that enabled a group of airplane-like vehicles to track a target in a coordinated manner, which was demonstrated using a small school of free-swimming robotic fish. Additional areas of research have included information propagation in delay-tolerant networks, sensor-guided flight, coordinated target tracking, acoustic source localization, computer vision systems, optimization, medical image processing, and distributed state estimation. As a member of IDM’s research team, Daniel’s time is split between developing the HIV model and building research tools. His HIV work focuses on building the contact network using ideas from feedback control to guide the dynamical relationship formation process. He is exploring structural assumptions in HIV modeling, HIV model calibration, the impact of interventions, and parameter sensitivity. The research tools he is developing allow researchers to run simulations in parallel on a supercomputer and view the results, as well as to explore large parameter spaces to find interesting regions, and to calibrate model parameters. In his spare time, Daniel guest lectures at the University of Washington, participates in the HIV Modeling Consortium and other related groups, and is a frequent presenter at conferences.

Publications

Wednesday, August 2, 2017

The main focus of this work is on the use of PSPO to maximize the pseudo-likelihood of a stochastic epidemiological model to data from a 1861 measles outbreak in Hagelloch, Germany.

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Thursday, June 15, 2017

​Age of sexual partner is a major risk factor for HIV acquisition in both men and women, independent of one’s own age.​

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Monday, January 2, 2017
The VMMC program for HIV prevention has proven successful in reaching a large population of uncircumcised men in western Kenya, but as of 2014, pockets of low circumcision coverage still existed.​​
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Tuesday, April 5, 2016
Could future generations could be protected from HIV using a prevention "age fence," analogous to the ring-fencing strategies used to control the spread of smallpox?
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Thursday, October 1, 2015
Mathematical models are widely used to simulate the effects of interventions to control HIV and to project future epidemiological trends and resource needs.
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Monday, July 20, 2015

The South African government is currently discussing various alternative approaches to the further expansion of antiretroviral treatment (ART) in public-sector facilities.

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Thursday, July 2, 2015

Migrant populations such as mine workers contributed to the spread of HIV in sub-Saharan Africa.

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Thursday, May 21, 2015

In the last 20 years, China ramped up a DOTS (directly observed treatment, short-course)-based tuberculosis (TB) control program with 80% population coverage, achieving the 20

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Tuesday, April 21, 2015

In the last 20 years, China ramped up a DOTS (directly observed treatment, short-course)-based tuberculosis (TB) control program with 80% population coverage, achieving the 2015 Millennium Developm

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Monday, December 1, 2014
Using an individual-based mathematical model, we quantified the impact of EAG campaigns in terms of probability of elimination, reduction in polio transmission and age stratified immunity levels.
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Thursday, July 31, 2014

Decision makers need efficient algorithms to draw meaningful conclusions from detailed stochastic simulations with respect to a goal-oriented objective.

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Thursday, July 24, 2014

Evidence that antiretroviral therapy reduces HIV infectiousness, suggests that increasing the number of HIV-positive adults who are on treatment could have the potential to change the course of the

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Wednesday, January 1, 2014

Recent scientific findings have demonstrated the efficacy and effectiveness of antiretroviral therapy (ART) for preventing transmission in heterosexual partnerships.

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Wednesday, August 28, 2013

The difficulty of choosing a strategy for allocating transmission-blocking interventions stems from an incomplete picture of the epidemiological drivers of generalized HIV epidemics, such as the ep

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Monday, December 10, 2012

This paper presents an algorithm to form heterosexual relationships of a desired joint age–mixing distribution. It includes control of the rates at which individuals seek new relationshi

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Tuesday, July 10, 2012

Mathematical modelling is used to investigate the potential impact of treatment on HIV incidence but substantial uncertainties will remain because information on all the factors that could influenc

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Tuesday, July 10, 2012

Several mathematical models that simulate HIV infection and disease progression have been developed to investigate the impact of expanding access to ART on the incidence of HIV (the number of new i

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Sunday, June 17, 2012

The EMOD model for HIV was compared to several other HIV models in an article by Eaton et al. published in PLoS Medicine.

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