Ashalatha is a doctoral student at Mälardalen University since December 2015. She has also been a memebr of the Doctoral Student Council at Mälardalen University during the period from 2016-2018.
Ashalatha's main research interests are in the following fields:
From 2015 until 2018, Ashalatha has been part of the European Union project, CAMI, where she reserached about the current trends in the existing Ambient Assisted Living Systems and proposed solutions that aids their functional integration and formal verification.
From 2019 until present, she has been part of the Health-5G project, where she has looked into details of modeling and analysis of 5G Service Orchestartion Problem, especially for critical e-health applications.
Supporting 5G Service Orchestration with Formal Verification (Mar 2023) Peter Backeman, Ashalatha Kunnappilly, Cristina Seceleanu Computer Science and Information Systems (ComSIS,10(1))
5G Service Orchestration Supported by Model Checking - A Case Study of Health Applications (Sep 2021) Ashalatha Kunnappilly, Peter Backeman, Cristina Seceleanu, Mathias Johanson MRTC Report, Mälardalen Real-Time Research Centre (MRTC 2021)
From UML Modeling to UPPAAL Model checking of 5G Dynamic Service Orchestration (May 2021) Ashalatha Kunnappilly, Peter Backeman, Cristina Seceleanu 7th international Conference on the Engineering of Computer Based Systems (ECBS 2021)
UML-based Modeling and Analysis of 5G Service Orchestration (Nov 2020) Ashalatha Kunnappilly, Peter Backeman, Cristina Seceleanu THE 27TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC 2020)
A Model-Checking-Based Framework For Analyzing Ambient Assisted Living Solutions (Nov 2019) Ashalatha Kunnappilly, Raluca Marinescu, Cristina Seceleanu Sensors Special Issue IoT Sensors in E-Health (Sensors)
Architecture Modelling and Formal Analysis of Intelligent Multi-Agent Systems (May 2019) Ashalatha Kunnappilly, Simin Cai, Cristina Seceleanu, Raluca Marinescu 14th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2019)
|CAMI - Artificially intelligent ecosystem for self-management and sustainable quality of life in AAL (Ambient Assisted Living)
|Health5G: Future eHealth powered by 5G
|Master Thesis: Implementation of a Decision Support System for an Ambient Assisted Living System