Heerok Banerjee

About

My research interests focus on the sustainability of distributed network architectures. I have worked at the intersection of linear and non-linear systems yielding several multi-objective, error-tolerant and efficient routing mechanism feasible for data-intensive applications. But, most of my study is on the performance of distributed systems with respect to architectural constraints. I focus on minimizing module-to-module inter-dependencies and formulate open problems that could unlock high-performance behaviors in such systems.
I am also intrigued by Applied machine learning and Machine Intelligence. Alternatively, I carry out my investigation of topological variations in sophisticated neural networks. Mostly, I focus on the interplay of network theory with soft-computing to reduce computational expenses in traditional and hybrid neural networks. My key focus is to integrate fuzzy-based learning principles to attain a degree of synchrony between dependent layers.

Employment

• Institute of Engineering and Management (IEM) Assistant Professor
  2025 - Present
• IMEC Research Associate
  2021 - 2025
• SRM Institute of Science and Technology Research Associate
  2016 - 2019

Education

• University of Antwerp Master's in Computer Science: Computer Networks & Distributed Systems
  2019 - 2021
• SRM Institute of Science and Technology Bachelor's Degree (B.Tech)
  2015 - 2019

Projects & Funding

Projects & funding information is unavailable.

Publications (14)

• Preliminary Analyses of TSCH and 6TiSCH Networks for Modelling Accurate Energy Consumption using Contiki-NG
  2025 DOI: 10.36227/techrxiv.176127388.85868511/v1
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• A COMPARATIVE ANALYSES OF NETWORK FORMATION IN LOW-POWER LOSSY NETWORKS ContikiMAC vs Orchestra-enabled TSCH
  Arxiv 2025 DOI: 10.48550/arXiv.2506.06688
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• Design and Implementation of a Domain-specific Language for Modelling Evacuation Scenarios Using Eclipse EMG/GMF Tool
  Arxiv 2025 DOI: 10.48550/arXiv.2509.06688
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• Uncertainty Modelling in Risk-averse Supply Chain Systems Using Multi-objective Pareto Optimization ...
  2020 DOI: 10.48550/arxiv.2004.13836
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• A Comparative Study on Statistical and Neural Approaches for Optimizing Supply Chain Managment (SCM) Systems
  SRM Institute of Science & Technology, Kattankulathur 2019 DOI: 10.13140/rg.2.2.19062.65601
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• Time Series Dataset for Risk Assessment in Supply Chain Networks
  2019 DOI: 10.17632/gystn6d3r4.2
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• A decentralized paradigm for resource-aware computing in wireless Ad hoc networks
  2019 DOI: 10.12928/TELKOMNIKA.v17i2
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• A decentralized paradigm for resource-aware computing in wireless Ad hoc networks
  Telkomnika Telecommunication Computing Electronics and Control 2019 DOI: 10.12928/telkomnika.v17i2.9621
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• Estimation of Control Parameter for Obtaining Discrete Time-variant Delays in Grid Networks
  2019 DOI: 10.1109/icecct.2019.8869116
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• Senior Thesis: Optimizing Risk-impact Propagation in Supply Chain Networks with Bayesian Analysis and Pareto Optimality ...
  2019 DOI: 10.13140/rg.2.2.29603.71206
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