Sanjeev R. Kulkarni is affiliated with Princeton University in the United States. Their research primarily falls within the field of Computer Science, with significant contributions in several subfields including Artificial Intelligence, Computer Networks and Communications, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, and Signal Processing.
Their recent papers reflect a focus on wireless communications, federated learning, and optimization techniques. Notable publications include:
Frequent coauthors collaborating with Kulkarni include Mohammad Mohammadi Amiri, H. Vincent Poor, Deniz Gündüz, Viraj Nadkarni, and Pramod Viswanath. These collaborations suggest interdisciplinary and multi-institutional research efforts.
Kulkarni's publications have appeared in a variety of venues. The most frequent venues are:
The main topics addressed in Kulkarni's research focus on privacy-preserving technologies in data, distributed sensor networks and detection algorithms, stochastic gradient optimization techniques, advanced MIMO systems optimization, network security and intrusion detection, wireless communication security techniques, and cooperative communication and network coding.
Mete Ozay;Inaki Esnaola;Fatos Tunay Yarman Vural;Sanjeev R. Kulkarni
S.R. Kulkarni;P. Viswanath
Qing Wang;S.R. Kulkarni;S. Verdu
Joel B. Predd;Sanjeev R. Kulkarni;H. Vincent Poor
Yap-Peng Tan;D.D. Saur;S.R. Kulkami;P.J. Ramadge
Pingmei Xu;Krista A. Ehinger;Yinda Zhang;Adam Finkelstein
A. Jovicic;P. Viswanath;S.R. Kulkarni
S.R. Kulkarni;G. Lugosi;S.S. Venkatesh
Qing Wang;S.R. Kulkarni;S. Verdu
Mohammad Mohammadi Amiri;Deniz Gunduz;Sanjeev R. Kulkarni;H. Vincent Poor
M. Ozay;I. Esnaola;F. T. Y. Vural;S. R. Kulkarni
Drew D. Saur;Yap-Peng Tan;Sanjeev R. Kulkarni;Peter J. Ramadge
J.B. Predd;R. Seiringer;E.H. Lieb;D.N. Osherson
M. Effros;K. Visweswariah;S.R. Kulkarni;S. Verdu
A. Reznik;S.R. Kulkarni;S. Verdu
Chih-Chun Wang;S.R. Kulkarni;H.V. Poor
J.B. Predd;S.R. Kulkarni;H.V. Poor
S.R. Kulkarni;S.E. Posner
Qing Wang;Sanjeev Kulkarni;Sergio Verdu
Peng Gao;Fei Shao;Xiaoyuan Liu;Xusheng Xiao
Mohammad Mohammadi Amiri;Deniz Gunduz;Sanjeev Kulkarni;H. Vincent Poor
If you think any of the details on this page are incorrect, let us know.
Studying Computer Science in the USA unlocks pathways to a wide range of related fields. Many students explore other STEM disciplines to broaden their skill sets and career opportunities. Affordable online programs make it easier than ever to diversify your expertise without leaving your current job or relocating.
For example, those interested in expanding their engineering knowledge may consider the cheapest online master's mechanical engineering programs, which equip graduates for advanced roles in design and manufacturing. If your interest is in foundational science, pursuing an online bachelor's degree in physics can open doors to research and analytical careers.
The tech industry is also experiencing strong demand for professionals who understand big data. Accredited data science programs offer training in statistics, programming, and machine learning, leading to data analyst or data scientist roles.
Lastly, the rise of smart technology is generating new jobs for graduates with electrical engineering expertise. Exploring the online electrical engineering career outcomes reveals strong salary potential and diverse job options across industries. These related degrees and career paths complement a Computer Science education, enhancing your employability and long-term growth.
National University of Singapore
MRC Laboratory of Molecular Biology
National Yang Ming Chiao Tung University
University of Washington
Vanderbilt University
University of Iceland
Medical University of Warsaw
Utrecht University
University of Sydney
University of Hong Kong
Yale University
University of Virginia
École Polytechnique Fédérale de Lausanne
University of Maryland, Baltimore
Gulf University for Science & Technology
University of Michigan–Ann Arbor