The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Kunal Talwar sits on this spectrum.
This scientist: 162 publications — 32nd percentile
32% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 991 publications or more.
The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Kunal Talwar sits on this spectrum.
This scientist: 62 D-Index — 80th percentile
80% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 131 D-Index or more.
Kunal Talwar is affiliated with Apple in the United States and has contributed extensively to the field of computer science, with a focus on privacy-preserving technologies, cryptography, and optimization techniques. Their research output spans multiple subfields, including artificial intelligence, management science and operations research, statistics and probability, computer networks and communications, and computational theory and mathematics.
Their work covers a wide range of topics such as:
Talwar has published numerous papers, frequently appearing in venues like arXiv (Cornell University) and the Leibniz-Zentrum für Informatik (Schloss Dagstuhl). Among recent publications are:
Their frequent coauthors include Vitaly Feldman, Hilal Asi, Audra McMillan, Jason M. Altschuler, and Tomer Koren, highlighting collaborative research efforts across various specialized areas. Talwar's work has contributed to major publication venues such as the SIAM Journal on Computing and the SIAM Journal on Mathematics of Data Science, further emphasizing a broad engagement with theoretical and applied aspects of computer science.
Throughout their career, Talwar has focused on developing methods related to privacy amplification, stochastic gradient methods, and information-theoretic approaches to secure computation. The blend of topics and collaborations indicates a research agenda centered on enhancing data privacy and optimization in machine learning and cryptographic contexts.
Martín Abadi;Ashish Agarwal;Paul Barham;Eugene Brevdo
Martin Abadi;Andy Chu;Ian Goodfellow;H. Brendan McMahan
F. McSherry;K. Talwar
Michael Isard;Vijayan Prabhakaran;Jon Currey;Udi Wieder
D.A. Spielman
Jittat Fakcharoenphol;Satish Rao;Kunal Talwar
Alex Fabrikant;Christos Papadimitriou;Kunal Talwar
H. Brendan McMahan;Daniel Ramage;Kunal Talwar;Li Zhang
Umesh Shankar;Kunal Talwar;Jeffrey S. Foster;David Wagner
Boaz Barak;Kamalika Chaudhuri;Cynthia Dwork;Satyen Kale
Nicolas Papernot;Martín Abadi;Úlfar Erlingsson;Ian J. Goodfellow
Aaron Archer;Christos H. Papadimitriou;Kunal Talwar;Éva Tardos
Moritz Hardt;Kunal Talwar
Ludwig Schmidt;Shibani Santurkar;Dimitris Tsipras;Kunal Talwar
Ludwig Schmidt;Shibani Santurkar;Dimitris Tsipras;Kunal Talwar
Nicolas Papernot;Shuang Song;Ilya Mironov;Ananth Raghunathan
Andrew McGregor;Ilya Mironov;Toniann Pitassi;Omer Reingold
Cynthia Dwork;Kunal Talwar;Abhradeep Thakurta;Li Zhang
Kunal Talwar
Rina Panigrahy;Kunal Talwar;Lincoln Uyeda;Udi Wieder
Úlfar Erlingsson;Vitaly Feldman;Ilya Mironov;Ananth Raghunathan
Cynthia Dwork;Kunal Talwar;Abhradeep Thakurta;Li Zhang
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