Jamsheed Manja Ppallan

About

Jamsheed Manja Ppallan is a Senior Chief Engineer for Samsung R&D Institute India-Bangalore. He holds an M.Tech in Data Science and Business Analytics, which he completed in 2023 from the Indian Institute of Science (IISc), Bangalore. In 2012, he earned a B.Tech degree in Computer Science from Cochin University of Science and Technology, Kerala, India.
Jamsheed has over ten years of industry experience in software research and development. He has a dynamic skill set and is deeply passionate about cutting-edge technologies.

His diverse research interests include:
Expertise in AI/ML, Deep Learning, and Reinforcement Learning.
Ultra Wideband (UWB), NFC, and IR-UWB Radar connectivity technologies
Next-generation transport layer protocols.
Cross-layer optimization for improved network performance.
Smartphone operating system development.
Green communication solutions.

Employment

• Samsung R&D Institute India - Bangalore Senior Chief Engineer
  2015 - Present
• Huawei Technologies India Pvt. Ltd. Software Engineer
  2013 - 2015
• National Informatic Centre, Govt. of India Programmer
  2013 - 2013

Education

• Indian Institute of Science Bangalore M. Tech
  2021 - 2023
• Cochin University B. Tech
  2008 - 2012

Projects & Funding

Projects & funding information is unavailable.

Publications (20)

• SurroundSense: Event-Driven User Personalization with Ambient Context Using Ultra-Wideband Radar
  2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC) 2025 DOI: 10.1109/ccnc54725.2025.10975870
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• IR-UWB Radar-Based Situational Awareness System for Smartphone-Distracted Pedestrians
  2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC) 2025 DOI: 10.1109/ccnc54725.2025.10975959
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• Forecasting and Mitigating Interference in TDD Mobile Communication Networks Using Machine Learning: A Data-Driven Approach
  2024 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS) 2024 DOI: 10.1109/ants63515.2024.10898333
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• A Machine Learning-Based Link Quality Assistance at Transport Layer for High-Frequency Networks
  ICC 2024 - IEEE International Conference on Communications 2024 DOI: 10.1109/icc51166.2024.10622673
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• PEaF-Production Environment Analyzer Framework: Assisting Continuous Deployment of 5G Workloads Using AI/ML
  IEEE Access 2024 DOI: 10.1109/access.2024.3472498
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• A Link-Quality Assisted Transport Layer for High-Frequency Networks
  2022 IEEE Wireless Communications and Networking Conference (WCNC) 2022 DOI: 10.1109/wcnc51071.2022.9771658
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• Mobility aware Socket Layer (MaSL) for seamless connectivity in mobile networks
  2021 IEEE Wireless Communications and Networking Conference (WCNC) 2021 DOI: 10.1109/wcnc49053.2021.9417533
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• Computational and Location Aware Middleware to Enable Edge Computing in Mobile Devices
  2021 IEEE 18th Annual Consumer Communications & Networking Conference (CCNC) 2021 DOI: 10.1109/ccnc49032.2021.9369522
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• A Method for Enabling Context-Awareness at Transport Layer for Improved Quality-of-Service Control
  IEEE Access 2021 DOI: 10.1109/access.2021.3110266
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• Path Aware Transport Layer Solution for Mobile Networks
  IEEE Access 2020 DOI: 10.1109/access.2020.3026378
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