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רונן דר 2013-2014

מוסד לימודים לדוקטורט:
אוניברסיטת תל-אביב
תחום אקדמי:
הנדסת חשמל
מנחה/מנחים בדוקטורט:
פרופ' מאיר פדר ופרופ' מרק שטייף
נושא הדוקטורט:
Information Theory in Optical-Fiber Communications
מוסד בתר-דוקטורט:
אינטל ואנוביט טכנולוגיות
מוסד נוכחי:
מעבדות בל
כתובת דוא"ל:
עמוד הבית

Ronen received his B.Sc. degree (cum laude) in 2008 and the M.Sc. degree (summa cum laude) in 2011 from the Tel Aviv University, Israel, both in Electrical Engineering. Since 2011 he is a Ph.D. student under the supervision of Prof. Meir Feder and Prof. Mark Shtaif, in the school of EE at Tel Aviv University.

In his PhD research Ronen studies information theoretic aspects of communication over the nonlinear optical-fiber channel. The ever-growing demand for data network traffic raised the need for determining an ultimate limit to the data rate at which optical communication systems can work reliably. Estimation of the optical-fiber channel capacity has therefore come to be one of the most challenging and important problems in the field of optical communication. The difficulty in estimating the the capacity is mostly due to fiber nonlinearity which generates complicated nonlinear interactions between the various transmitted channels. Since cooperation between the channels is not always available in a network architecture and joint processing of the entire spectrum of channels is prohibitively complex, the induced nonlinear interference is customarily treated as noise and is considered to be the main factor in limiting the optical-fiber capacity. Concurrently, Ronen studies the statistical properties of this nonlinear interference noise and its effect on the achievable information rates.

During 2006-2012 Ronen served as an Algorithm engineer in Intel’s mobile wireless group and Anobit Technologies, a developer of advanced signal processing technologies for the storage markets (acquired by Apple Inc. in 2011).

Ronen is a recipient of the Intel award for excellence in academic studies and research (2013), the Weinstein award for an outstanding publication in the field of signal processing (2013), and the Weinstein prize for academic excellence (2011).