CURRENT U.S. PhD students who are ~12-18 months from completion:  PROMISE asks you to apply. This is an initiative that is going out to all AGEPs across the nation.

The Academy for Future Science Faculty
Group II – Advanced Stage PhD Students
Get a BIG head-start on the next critical step toward an academic career!

With a grant from NIH, in 2011 we launched a brand new approach to assisting the development of young scientists called the Academy for Future Science Faculty. The Academy uses sophisticated coaching techniques to supplement what PhD students get from their research mentors and graduate programs. Students participate in annual summer conferences and stay connected with student colleagues and their Academic Career Coaches throughout the year. The Academy has been designed for students who have the long-term goal of becoming a faculty member. Phase I started in 2011 with 100 students just beginning the PhD. This current announcement for Phase 2 is for students LIKELY TO COMPLETE THEIR PHD WITHIN THE NEXT 12-18 MONTHS. All expenses will be paid so there will be no cost to you.

The Academy is being conducted as a true experiment – 60 students will be RANDOMLY selected to participate from those who apply. Selection will not be based on grades, GRE scores, publications or letters of recommendation. We encourage applications that will help us create a diverse group of participants in terms of race, ethnicity, religion, age, gender, sexual orientation, etc.

Be a part of the first group of advanced PhD students to join the Academy! Extended deadline: April 30! APPLY HERE –> https://nufsm.wufoo.com/forms/academy-for-future-science-faculty-group-ii/

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Details from the flyer: Academy2_Future_Faculty_Student_Recruitment_Flyer

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Sponsor: Science Careers Research Development Group 

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Related articles

• Yes, professors *DO* make more than $100,000/year! Here are some recent salaries … (promiseagep.wordpress.com)

CURRENT U.S. PhD students who are ~12-18 months from completion:  PROMISE asks you to apply. This is an initiative that is going out to all AGEPs across the nation.

The Academy for Future Science Faculty
Group II – Advanced Stage PhD Students
Get a BIG head-start on the next critical step toward an academic career!

With a grant from NIH, in 2011 we launched a brand new approach to assisting the development of young scientists called the Academy for Future Science Faculty. The Academy uses sophisticated coaching techniques to supplement what PhD students get from their research mentors and graduate programs. Students participate in annual summer conferences and stay connected with student colleagues and their Academic Career Coaches throughout the year. The Academy has been designed for students who have the long-term goal of becoming a faculty member. Phase I started in 2011 with 100 students just beginning the PhD. This current announcement for Phase 2 is for students LIKELY TO COMPLETE THEIR PHD WITHIN THE NEXT 12-18 MONTHS. All expenses will be paid so there will be no cost to you.

The Academy is being conducted as a true experiment – 60 students will be RANDOMLY selected to participate from those who apply. Selection will not be based on grades, GRE scores, publications or letters of recommendation. We encourage applications that will help us create a diverse group of participants in terms of race, ethnicity, religion, age, gender, sexual orientation, etc.

Be a part of the first group of advanced PhD students to join the Academy! Extended deadline: April 30! APPLY HERE –> https://nufsm.wufoo.com/forms/academy-for-future-science-faculty-group-ii/

——————-

Details from the flyer: Academy2_Future_Faculty_Student_Recruitment_Flyer

——————-

Sponsor: Science Careers Research Development Group 

——————-

Related articles

• Yes, professors *DO* make more than $100,000/year! Here are some recent salaries … (promiseagep.wordpress.com)

cadillacranchdressing:

Gym Class Heroes at UMBC Quadmania 2012

William H. Thomas, a geriatrician, author and UMBC Erickson School faculty member, calls himself a “nursing home abolitionist.” For years he has championed an innovative, new approach to senior care based on small, home-like environments. Today his vision is a reality.

The Green House Residences at Stadium Place opened in Baltimore last week. Coinciding with the launch of the new facility, Sheilah Kast of WYPR’s “Maryland Morning” interviewed Thomas about the future of senior living.

Tom Beck, Chief Curator, was interviewed about “Photographic Memory: Civil War Photographs from UMBC’s Special Collections” by Bill Vanko on WBAL’s “Maryland’s Morning News.” He described the exhibition and said that the intention of the show is commemorate the 150 anniversary of the Civil War.

MS Thesis Defense

Distributed Model Consensus for Models of Locally
Biased Measurements in Wireless Sensor Networks

Jacob Thompson

4:00pm Wednesday, 25 April 2012, ITE 325B, UMBC

Wireless sensor networks (WSNs) consist of interconnected microsensors, each of which collects measurements from its local environment, which are often used in monitoring and control applications. These applications make inferences about the global and local states of the deployment environment. However, due to the limited communication and energy resources at the sensors, gathering all the raw data at a central fusion/control point is impractical.

Hence, it is essential to have distributed learning and inference in WSNs, such as learning a consensus model from the locally learned models. Consensus is challenging due to the limited resources of the sensors and the inherent bias of the individual sensor models learned from their local sensing environments. Two leading approaches for this problem are the approach by Zheng et al which uses loopy belief propagation on a certain graphical model based on the WSN topology and the local models, and the approach by Xiao et al which relies on gossip averaging of the parameters of the local models.

We focus on multivariate linear regression models, such as Bayesian, Ridge, and Lasso regression models. We analyze and extend the loopy Gaussian belief propagation (GaBP) approach to model consensus, and compare its performance to the gossip averaging approach. We experimentally find that GaBP tends to converge much faster than gossip averaging, but to a less accurate estimated consensus model (especially in the presence of multiple cycles in its corresponding graphical model). We also find that gossip averaging along paths in the WSN, tends to provide much faster convergence to more accurate estimated consensus models as compared to GaBP.

Committee: Professors Kostas Kalpakis (chair), Tim Oates and Yun Peng