11 citations · 31 across the 16 of their papers we have counts for
19 papers
Understanding Behavioral Dark Patterns of High BMI Individuals
Manjeet Yadav, Prasenjit Karmakar, Suchetana Chakraborty
Understanding how everyday behaviors influence body weight is essential for designing effective and personalized health interventions. Existing studies largely rely on self-reporte…
PoHAR: Understanding Hyperlocal Human Activities with Pollution Sensor Networks
Prasenjit Karmakar, Karthik Reddy, Sandip Chakraborty
Low-cost air quality sensors are becoming ubiquitous in our daily lives as public awareness of air pollution continues to grow, and people take measures to monitor and improve the…
From Invisible to Actionable: Augmented Reality Interactions with Indoor CO2
Prasenjit Karmakar, Manjeet Yadav, Swayanshu Rout +2
Indoor carbon dioxide (CO2) can rapidly accumulate to form invisible pollution hotspots, posing significant health risks due to its odorless and colorless nature. Despite growing i…
Exploiting Air Quality Monitors to Perform Indoor Surveillance: Academic Setting
Prasenjit Karmakar, Swadhin Pradhan, Sandip Chakraborty
Changing public perceptions and government regulations have led to the widespread use of low-cost air quality monitors in modern indoor spaces. Typically, these monitors detect air…
Exploring Indoor Air Quality Dynamics in Developing Nations: A Perspective from India
Prasenjit Karmakar, Swadhin Pradhan, Sandip Chakraborty
Indoor air pollution is a major issue in developing countries such as India and Bangladesh, exacerbated by factors like traditional cooking methods, insufficient ventilation, and c…
Indoor Air Quality Dataset with Activities of Daily Living in Low to Middle-income Communities
Prasenjit Karmakar, Swadhin Pradhan, Sandip Chakraborty
In recent years, indoor air pollution has posed a significant threat to our society, claiming over 3.2 million lives annually. Developing nations, such as India, are most affected…
Exploring Indoor Health: An In-depth Field Study on the Indoor Air Quality Dynamics
Prasenjit Karmakar, Swadhin Pradhan, Sandip Chakraborty
Indoor air pollution, a significant driver of respiratory and cardiovascular diseases, claims 3.2 million lives yearly, according to the World Health Organization, highlighting the…
mmDrive: mmWave Sensing for Live Monitoring and On-Device Inference of Dangerous Driving
Argha Sen, Avijit Mandal, Prasenjit Karmakar +2
Detecting dangerous driving has been of critical interest for the past few years. However, a practical yet minimally intrusive solution remains challenging as existing technologies…
AQuaMoHo: Localized Low-Cost Outdoor Air Quality Sensing over a Thermo-Hygrometer
Prithviraj Pramanik, Prasenjit Karmakar, Praveen Kumar Sharma +7
Efficient air quality sensing serves as one of the essential services provided in any recent smart city. Mostly facilitated by sparsely deployed Air Quality Monitoring Stations (AQ…
A Practical AoI Scheduler in IoT Networks with Relays
Biplav Choudhury, Prasenjit Karmakar, Vijay K. Shah +1
Internet of Things (IoT) networks have become ubiquitous as autonomous computing, communication and collaboration among devices become popular for accomplishing various tasks. The…
Exploiting Multi-modal Contextual Sensing for City-bus's Stay Location Characterization: Towards Sub-60 Seconds Accurate Arrival Time Prediction
Ratna Mandal, Prasenjit Karmakar, Soumyajit Chatterjee +5
Intelligent city transportation systems are one of the core infrastructures of a smart city. The true ingenuity of such an infrastructure lies in providing the commuters with real-…
Stochastic Approximation with Markov Noise: Analysis and applications in reinforcement learning
Prasenjit Karmakar
We present for the first time an asymptotic convergence analysis of two time-scale stochastic approximation driven by "controlled" Markov noise. In particular, the faster and slowe…
Customer-server population dynamics in heavy traffic
Rami Atar, Prasenjit Karmakar, David Lipshutz
We study a many-server queueing model with server vacations, where the population size dynamics of servers and customers are coupled: a server may leave for vacation only when no c…
On the function approximation error for risk-sensitive reinforcement learning
Prasenjit Karmakar, Shalabh Bhatnagar
In this paper we obtain several informative error bounds on function approximation for the policy evaluation algorithm proposed by Basu et al. when the aim is to find the risk-sens…
On a convergent off -policy temporal difference learning algorithm in on-line learning environment
Prasenjit Karmakar, Rajkumar Maity, Shalabh Bhatnagar
In this paper we provide a rigorous convergence analysis of a "off"-policy temporal difference learning algorithm with linear function approximation and per time-step linear comput…
Dynamics of stochastic approximation with iterate-dependent Markov noise under verifiable conditions in compact state space with the stability of iterates not ensured
Prasenjit Karmakar, Shalabh Bhatnagar
This paper compiles several aspects of the dynamics of stochastic approximation algorithms with Markov iterate-dependent noise when the iterates are not known to be stable beforeha…
Scalable Reliability Modelling of RAID Storage Subsystems
Prasenjit Karmakar, K. Gopinath
Reliability modelling of RAID storage systems with its various components such as RAID controllers, enclosures, expanders, interconnects and disks is important from a storage syste…
Are Markov Models Effective for Storage Reliability Modelling?
Prasenjit Karmakar, K. Gopinath
Continuous Time Markov Chains (CTMC) have been used extensively to model reliability of storage systems. While the exponentially distributed sojourn time of Markov models is widely…
Two Timescale Stochastic Approximation with Controlled Markov noise and Off-policy temporal difference learning
Prasenjit Karmakar, Shalabh Bhatnagar
We present for the first time an asymptotic convergence analysis of two time-scale stochastic approximation driven by `controlled' Markov noise. In particular, both the faster and…