Who am I?

I started my PhD from 2013 under Nirmalya Roy in the Mobile and Pervasive Sensing Group (MPSC) in the Information Systems Department at University of Maryland Baltimore County (UMBC). My research area is Energy Analytics and Pervasive Computing.

Contact Details

Nilavra Pathak
ITE 415,1000 Hilltop Circle,
UMBC, MD 21250 US



To know nothing

PhD. Degree in Information Systems August 2013 - onwards

My PhD is centered around energy analytics, big data analytics, signal processing and pervasive computing. My core focus is on Non-Intrusive Load Monitoring using signal processing and machine learning and optimization techniques.

To know something

M.E. Degree in Computer Science 2011 - 2013

My Masters of Engineering in Computer Science in Jadavpur University was mostly inclined towards Machine Learning Applications and my Thesis was on Ensemble Clustering Techniques.

To know everything!!

B. Tech in Computer Science 2007-2011

I graduated from St Thomas' College of Engineering & Technology under West Bengal University and Technology in 2011.



Nirmalya Roy, Nilavra Pathak, and Archan Misra. “AARPA: Combining Mobile and Power-line Sensing for Fine-grained Appliance Usage and Energy Monitoring”, in Proceedings of the IEEE International Conference on Mobile Data Management (MDM), June 2015.

Roy, Nirmalya, Nilavra Pathak, and Archan Misra. "Fine-grained appliance usage and energy monitoring through mobile and power-line sensing." Pervasive and Mobile Computing 30 (2016): 132-150.

Acoustic Based Appliance State Identifications for Fine-Grained Energy Analytics

Nilavra Pathak, Md. Abdullah Al Hafiz Khan, and Nirmalya Roy. “Acoustic based appliance state identifications for fine grained energy analytics”, in Proceedings of the IEEE International Conference on Pervasive Computing and Communications (PerCom), March 2015. [acceptance rate: 15%]

Md. Abdullah Al Hafiz Khan, Sheung Lu, Nirmalya Roy, and Nilavra Pathak. “Demo Abstract: A Microphone Sensor based System for Green Building Applications”, in Proceedings of the IEEE International Conference on Pervasive Computing and Communications Demonstrations (PerCom, March 2015.


Mohammad Arif Ul Alam, Nilavra Pathak, Nirmalya Roy, “Mobeacon: An iBeacon-Assisted smart-phone-Based Real Time Activity Recognition Framework”, 12th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, Mobiquitous 2015, Coimbra, Portugal

Iterative Disaggregation

Nilavra Pathak, Nirmalya Roy and Animikh Biswas, " Iterative Signal Separation Assisted Energy Disaggregation ", in Proceedings of the sixth International Green and Sustainable Computing Conference (IGSC, December 2015).


David Lachut, Nilavra Pathak, Nilanjan Banerjee, Nirmalya Roy, Ryan Robucci, Longitudinal Energy Waste Detection with Visualization. Buildsys 2017.

Nilavra Pathak, James Foulds, Nirmalya Roy, Nilanjan Banerjee and Ryan Robucci. “Estimating Buildings’ Parameters over Time Including Prior Knowledge”. (Pre-print under submission in ACM E-Energy 2019. https://arxiv.org/pdf/1901.07469.pdfArXiv)

Nilavra Pathak, David Lachut, Nirmalya Roy, Nilanjan Banerjee and Ryan Robucci, Non-Intrusive Air Leakage Detection in Residential Homes, ICDCN 2018.

Nilavra Pathak. PhD Forum: Scalable Energy Disaggregation: Data, Dimension and Beyond. IEEE SmartComp, 2018.

Gas Consumption Forecasting

Nilavra Pathak, Amadou Ba, Joern Ploennigs, and Nirmalya Roy. “A Study of Multivariate TimeSeries Forecasting for Non-Residential Gas Consumption”. (Under Review Pervasive and Mobile Computing)

Nilavra Pathak, Amadou Ba, Joern Ploennigs, and Nirmalya Roy. “Forecasting gas usage for big buildings using generalized additive models and deep learning.” IEEE SmartComp, 2018.

Research Interest

Being in MPSC its never enough to have focus towards only one area. My research interests are as follows sorted in the order of interest. The listed ones are the primary interests although it keeps growing with the passing of days.

  • Machine Learning Applications
  • Signal Processing
  • Energy Analytics
  • Big Data Analytics
  • Mathematical Optimization
  • Activity Recognition