Bio

Jelena Marasevic is a Ph.D. student at Columbia University. Her research focuses on algorithms for fair and efficient resource allocation problems, with applications in wireless networks. She received her B.Sc. degree from University of Belgrade, School of Electrical Engineering, in 2011, and her M.S. degree in electrical engineering from Columbia University in 2012. For her M.S. degree, she received the M.S. Award of Excellence.

In Spring 2012, Jelena organized the first cellular networking hands-on lab for a graduate class in wireless and mobile networking. For this work, she received the Best Educational Paper Award at the 2nd GENI Research and Educational Experimentation workshop (GREE2013), and was also awarded the Jacob Millman Prize for Excellence in Teaching Assistance from Columbia University.

Earlier this year, Jelena was in a two-student team that won the Qualcomm Innovation Fellowship for a cross-disciplinary project on full-duplex wireless.

Links between systems and theory: Full-duplex wireless and beyond

Links between systems and theory: Full-duplex wireless and beyond

My research focuses on the optimization of wireless network performance by using analytical tools from optimization and algorithms research, and relying on the problem structure. From the theory perspective, the goal is to understand and describe the studied problems with realistic but tractable mathematical models, and ultimately devise algorithms with provable performance guarantees. From the systems perspective, the goal is to implement the devised algorithms and demonstrate their performance experimentally.

For example, in a cross-disciplinary project on full-duplex wireless communication — simultaneous transmission and reception on the same frequency channel — we have been exploring the interactions between the hardware design and the algorithms for medium access control (MAC). Our work has resulted in a number of insightful analytical results that characterize and quantify achievable throughput gains from full-duplex, based on realistic models of the full-duplex hardware. Moreover, we have obtained power allocation algorithms that are applicable to quite general hardware models and to both single-channel and multi-channel settings. Our algorithms maximize the sum of the rates over a full-duplex pair of users and over (possibly multiple) frequency channels, and are provably near-optimal. The algorithms provide output that agrees well on the modeled and the measured full-duplex hardware profile.

My work in the area of full-duplex currently involves design of adaptive algorithms for self-interference cancellation in full-duplex circuits, design and analysis of scheduling algorithms with fairness guarantees, and a testbed development.

Apart from full-duplex, I am also working on the design and analysis of fast iterative optimization methods for large-scale problems with fairness objectives.