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Ajay Arunachalam

Title: Researcher School/office: School of Science and Technology

Email:

Phone: +46 19 303591

Room: T1225

Ajay Arunachalam

About Ajay Arunachalam

Ajay Arunachalam is researcher at the Center for Applied Autonomous Sensors Systems (AASS), Dept. of Science and Technology, Örebro University.

He will be working on the Autonomous Precision Agriculture Robot as part of the Food & Health programme at the university. The main goal being SMART FOOD PRODUCTION & LOGISTICS supported by Artificial Intelligence. His role will be towards building an smarter sophisticated system centred around this automated hotbed prototype. 

He is working on the project titled "AI for maximizing taste and health, minimizing emission in a local food system" that dwells around wide range of computer vision problems, multi-objective optimization tasks, pattern recognition from sensor signals & olfactory data, extract insight from complex biomedical data, further building explainable models, and finally prototyping it as an all-in-one autonomous AI-based real-time solution covering all the end deliverables together. The project will generate large amount of data, requiring software pipelines for efficient data processing and modelling. He was responsible for deploying the same. He is working on building Deep Learning pipelines to tackle different research questions within the scope of the project. Few key POC done includes building Intelligent Autonomous Data Auto- Annotation / Data Auto- Labelling Platform , Novel Drug Discovery Design with Deep Reinforcement Learning. He has also integrated large pool of different sensors and developed the data acquisition software for it which is open sourced to the community. He has developed Multi-Spectral Imaging setup & the written acquisition software for it which is open-sourced to the community. Further, his work also largely involved end-to-end automation.

 

 

 

Publications

Articles in journals |  Chapters in books |  Conference papers | 

Articles in journals

Ravi, V. , Alazab, M. , Srinivasan, S. , Arunachalam, A. & Soman, K. (2021). Adversarial Defense: DGA-Based Botnets and DNS Homographs Detection Through Integrated Deep Learning. IEEE transactions on engineering management.
Arunachalam, A. , Ravi, V. , Krichen, M. , Alroobaea, R. & Alqurni, J. S. (2021). Analytical Comparison of Resource Search Algorithms in Non-DHT Mobile Peer-to-Peer Networks. Computers, Materials and Continua (CMC), 68 (1), 983-1001.
Paul, S. , Arunachalam, A. , Khodadad, D. , Andreasson, H. & Rubanenko, O. (2021). Fuzzy Tuned PID Controller for Envisioned Agricultural Manipulator. International Journal of Automation and Computing, 1-13.
Arunachalam, A. , Ravi, V. , Krichen, M. , Alroobaea, R. & Rubaiee, S. (2021). Mathematical Model Validation of Search Protocols in MP2P Networks. Computers, Materials and Continua (CMC), 68 (2), 1807-1829.
Arunachalam, A. & Sornil, O. (2017). A broadcast based random query gossip algorithm for resource search in non-DHT mobile Peer-to-Peer networks. Diànnǎo xuékān (Journal of Computers), 28 (1), 209-223.
Arunachalam, A. & Sornil, O. (2016). Minimizing Redundant Messages and Improving Search Efficiency under Highly Dynamic Mobile P2P Network. Journal of Engineering Science and Technology Review, 9 (1), 23-35.
Arunachalam, A. & Sornil, O. (2016). Reducing Routing Overhead in random walk protocol under MP2P Network. International Journal of Electrical and Computer Engineering, 6 (6), 3121-3130.
Arunachalam, A. & Sornil, O. (2015). An Analysis of the Overhead and Energy Consumption in Flooding, Random Walk and Gossip Based Resource Discovery Protocols in MP2P Networks. 2015 Fifth International Conference on Advanced Computing & Communication Technologies, 292-297.

Chapters in books

Srinivasan, S. , Vinayakumar, R. , Arunachalam, A. & Alazab, M. (2020). DURLD: Malicious URL Detection Using Deep Learning-Based Character Level Representations. In: Mark Stamp, Mamoun Alazab, Andrii Shalaginov, Malware Analysis Using Artificial Intelligence and Deep Learning (pp. 535-554). . Springer.

Conference papers

Paul, S. , Arunachalam, A. , Khodadad, D. & Rubanenko, O. (2020). Fuzzy Tuned PID Controller for Vibration Control of Agricultural Manipulator. In: HORA 2020 - 2nd International Congress on Human-Computer Interaction, Optimization and Robotic Applications Proceedings. Paper presented at 2nd International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA 2020), Ankara, Turkey, June 26-28, 2020 (pp. 166-170). IEEE.