activity
20152021
most citedUnraveling the Global Teleconnections of Indian Summer Monsoon Clouds: Expedition from CMIP5 to CMIP6

26 citations · 51 across the 7 of their papers we have counts for

collaborators

7 papers

physics.ao-ph2021★ 26 cited

Unraveling the Global Teleconnections of Indian Summer Monsoon Clouds: Expedition from CMIP5 to CMIP6

Ushnanshu Dutta, Anupam Hazra, Hemantkumar S. Chaudhari +3

We have analyzed the teleconnection of total cloud fraction (TCF) with global sea surface temperature (SST) in multi-model ensembles (MME) of the fifth and sixth Coupled Model Inte…

physics.flu-dyn2021★ 20 cited

Effect of recirculation zones on the ventilation of a public washroom

Krishnendu Sinha, Utkarsh Verma, Janani Srree Murallidharan +1

Air-borne transmission can pose a major risk of infection spread in enclosed spaces. Venting the air out using exhaust fans and ducts is a common approach to mitigate the risk. In…

math.OC2020

The Operational Impact of Registry size, Cycle length, and Blood Type Distribution in Multi-Registry Kidney Exchange Programs

Utkarsh Verma, Narayan Rangaraj, Viswanath Billa +1

Kidney exchange programs address donor recipient incompatibility by exchanging donors between incompatible pairs, but single center KEPs often suffer from limited donor pools, whic…

math.OC2020

Long term simulation analysis of deceased donor initiated chains in kidney exchange programs

Utkarsh Verma, Narayan Rangaraj

Kidney exchange programs have been developed to find compatible kidneys for recipients who have incompatible donors. On the other hand, patients who do not have a living donor depe…

math.OC2019★ 1 cited

IP Solutions for International Kidney Exchange Programmes

Péter Biró, Márton Gyetvai, Radu Stefan Mincu +2

In kidney exchange programmes patients with end-stage renal failure may exchange their willing, but incompatible living donors among each other. National kidney exchange programmes…

cs.CR2019★ 2 cited

Malware Evasion Attack and Defense

Yonghong Huang, Utkarsh Verma, Celeste Fralick +3

Machine learning (ML) classifiers are vulnerable to adversarial examples. An adversarial example is an input sample which is slightly modified to induce misclassification in an ML…

cs.HC2015★ 2 cited

On Optimizing Human-Machine Task Assignments

Andreas Veit, Michael Wilber, Rajan Vaish +48

When crowdsourcing systems are used in combination with machine inference systems in the real world, they benefit the most when the machine system is deeply integrated with the cro…