News
| Nov 15, 2011 | Presentation accepted for Neuroscience 2011 Using the statistics of binocular images to model spontaneous activity in the developing visual system [abstract] |
| Nov 14, 2011 | Posture from tremor paper published in Experimental Brain Research [pdf] |
| Sep 2011 | Balance and Gait in PD improved by balance board training, Physical Medicine and
Rehabilitation [abstract] |
| May 24, 2011 | Tilt adaptation using mobile phones paper, PLoS ONE. [abstract] |
| Apr 27, 2011 | Automated activity recognition and identification using mobile phone accelerometry, Neural Control of Movement 2011. [abstract] |
| Apr 2, 2011 | Parkinson's Research Day poster (mobile phone work) [pdf] |
| Nov 16, 2010 | Oculomotor adaptation talk at SFN 2010. [pdf] |
Mark V. Albert - http://mva.mePostdoctoral Research AssociateSensory Motor Performance Program (SMPP) of Northwestern University and the Rehabilitation Institute of Chicago office: room 1479 345 E Superior St Chicago, IL 60611 phone: 607-339-8536 email: mark @ mva.me |
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Research Interests in brief:
- Using mobile phones to track movements
- applying machine learning to mobile phone accelerometry, improving activity recognition
- tracking patient activities, falls, and symptoms of motor disorders over time
- Computational perception/neuroscience
| Northwestern University medical school | 2009- | Research Associate |
| Loyola University Chicago Computer Science department | 2010-2011 | Adjunct Faculty |
| Cornell University | 2004-2009 | Ph.D in Computational Biology |
| Carnegie Mellon University | 2001-2004 | Research assistant: human fMRI & monkey neurophysiology |
| University of Vienna | 2000-2001 | Fulbright Scholar |
| Pittsburg State University | 1996-2000 | BS in chemistry, math, physics, and computer science |
Courses Taught (2010-2011):
- COMP 383: Computational Biology
- COMP 398: Independent Study (phone activity recognition)
- COMP 271: Data Structures
- COMP 150: Intro to Computing
* Normative: approaching problems by answering the question "what ought to be" rather than "what is". For example, we can understand the visual system by directly measuring and characterizing neural responses to stimuli, but a normative approach would be to understand the responses as an efficient encoding of visual experience. Many modeling approaches answer questions of "what" or "how" for neural responses, but normative models also help to answer "why".