S
Sandip Kundu
Researcher at University of Massachusetts Amherst
Publications - 297
Citations - 4950
Sandip Kundu is an academic researcher from University of Massachusetts Amherst. The author has contributed to research in topics: Automatic test pattern generation & CMOS. The author has an hindex of 35, co-authored 283 publications receiving 4580 citations. Previous affiliations of Sandip Kundu include Intel & Indian Council of Agricultural Research.
Papers
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Journal ArticleDOI
The potential of cropping systems and soil amendments for carbon sequestration in soils under long‐term experiments in subtropical India
Biswapati Mandal,Bidisha Majumder,P. K. Bandyopadhyay,Gora Chand Hazra,A. Gangopadhyay,R. N. Samantaray,A. K. Mishra,Jaladhi Chaudhury,M. N. Saha,Sandip Kundu +9 more
TL;DR: In this paper, the authors evaluated the long-term role of crop residue C inputs to soil in SOC sequestration and also the critical value of C inputs for maintenance of soil organic C (SOC) at a level critical for upkeeping soil health and also for restraining global warming.
Journal ArticleDOI
Potential of double-cropped rice ecology to conserve organic carbon under subtropical climate
Biswapati Mandal,Bidisha Majumder,Tapan Kumar Adhya,P. K. Bandyopadhyay,A. Gangopadhyay,Dibyendu Sarkar,Manik Chandra Kundu,Shreyasi Gupta Choudhury,Gora Chand Hazra,Sandip Kundu,R. N. Samantaray,A. K. Misra +11 more
TL;DR: In this paper, the authors investigated the impact of long-term intensive rice-rice cropping system with different managements on the organic carbon (SOC) stock and established a mechanistic pathway of stabilization of the SOC into different pools, with a tentative C budgeting.
Proceedings ArticleDOI
Statistical Yield Modeling for Sub-wavelength Lithography
A. Sreedhar,Sandip Kundu +1 more
TL;DR: A yield modeling technique for a given layout, based on a statistical model for process variability, is presented, which shows that yield sensitivity increases at smaller feature sizes.
Proceedings ArticleDOI
Fast statistical timing analysis by probabilistic event propagation
TL;DR: A new statistical timing analysis algorithm, which produces arrival-time random variables for all internal signals and primary outputs for cell-based designs with all cell delays modeled as random variables, is proposed.
Proceedings ArticleDOI
On-chip compression of output responses with unknown values using lfsr reseeding
TL;DR: The procedure is based on reseeding of the LFSR to mask unknown output values while allowing fault effects to propagate, and to determine the seeds, the output response of the circuit is partitioned into a minimal number of fragments.