I am no longer at Boston University. I am currently working at Systems & Technology Research. A new page is coming soon. For now, please refers to my Linkedin account.
Information Sciences and Systems LabBoston University Electrical and Computer Engineering Department Boston, MA 02215
email: firstname.lastname@example.orgView my resume
I am currently a postdoc in the Information Sciences and Systems Lab at Boston University, ECE Department . I received a BS, MS and PhD in Electrical Engineering from Boston University in 2007, 2010 and 2013. My thesis advisors were Prof. Venkatesh Saligrama and Prof. David Castanon.
My current research deals with reducing cost in different aspects of machine learning. My other areas of interest are:
- supervised, semi-supervised and unsupervised machine learning: theory and algorithms
- statistical signal processing in image reconstruction and inverse problems
- optimization methods
In the past, I worked on automated alignment and surface characterization in concentrated solar power dish systems at Sandia National Laboratories in Albuquerque, New Mexico.
J. Wang, K. Trapeznikov, V. Saligrama. “Online Local Linear Classification”, CAMSAP December 2013
K. Trapeznikov, V. Saligrama, D. Castanon. “Multi-Stage Classifier Design“, Machine Learning, 2013 paper (long journal version)
K. Trapeznikov, V. Saligrama, D. Castanon. “Two Stage Decision System“, IEEE Stochastic Signal Processing Workshop, August 2012
C.E. Andraka, J. Yellowhair, K. Trapeznikov, J. Carlson., B. Myer, K. Hunt. “AIMFAST: An Alignment Tool Based On Fringe Reflection Methods Applied To Dish Concentrators“, J. Solar. Energy Eng 2011 paper
C.E. Andraka, S. Sadlon, B. Myer, K. Trapeznikov, C. Liebner. “Rapid Reflective Facet Characterization Using Fringe Reflection Techniques”, J. Solar. Energy Eng 2013 paper
“Supervised Sequential Classification Under Budget Constraints”, Graduation Day Talk, Information Theory and Applications Workshop, San Diego, 2013
“Multi-Stage Decision System”, 8th Algorithm Development for Security Applications Workshop, Boston, 2012
Organizer: Int. Conf. on Machine Learning 2013 Workshop on “Machine Learning with Test-time budgets”
“Sequential Decision System Design”, Workshop on Multi-Trade Offs in Machine Learning, Conference on Neural Information Processing Systems, Lake Tahoe, Nevada, 2012
“Multi-Stage Classifier Design”, Research and Industrial Collaboration Conference (RICC), at Awareness and Localization of Explosive Related Threats (ALERT) DHS Center of Excellence, October, Boston, 2011
“Active Boosted Learning“, Boston University Science Day, 2011
“Active Boosted Learning”, Research and Industrial Collaboration Conference (RICC), at Awareness and Localization of Explosive Related Threats (ALERT) DHS Center of Excellence, October, Boston, 2010