Cohort 1 Master Thesis
Click on thesis title to open the document as published by LTU.
- Mahnoor Mehmood Malik, Context-aware contact tracing in pandemic situations
- Hien Ngo Le Huy, Cognitive System for an Autonomous Vehicle
- Yacine Rabehi, Cognitive IoT for Smart Homes
- Hanna Woldeselassie Ogbazghi, A new ICN caching strategy for IoT applications
- Fatema Mirza, IoT Workload Characterization in Next Generation Cloud Systems
- Md Abu Ahammed Babu, Notification Oriented Paradigm as a Green Technology
- Feter Akira Vedaalana Sitepu, Performance evaluation of various QUIC implementations
- Otabek Sobirov, Energy Efficient Communication Scheduling for IoT-based waterbirds monitoring: Machine Learning Strategies
- Ameer Hamza, Deep learning for smart navigation
- Ashmita Thapa, Benchmarking and energy efficiency of cloud gaming experience
- Josue Becerra Rico, The augmented worker
- Tareq B M Alqazzaz, Tensor-based data analysis for intelligent networks
- Wania Khan, Advanced Data Analytics Modelling for Evidence-based Data Center Energy Management
- Elyas Khorasani, Challenges and opportunities of Blockchain based system for energy communities
- Noah Weldeab, Cognitive System for a Smart Data Center
- Samuel Asiwaju, Energy efficiency with Cooperative transmissions
- Mohammad Newaj Jamil, Network intelligence for enhanced Multi-Access Edge Computing (MEC) in 5G
- Mohammad Messbah Uddin, Power-aware Routing, and Data forwarding protocols for Energy Harvesting FANETs
Cohort 2 Master Thesis
- Mirjalol Aminov, Adversarial Machine (Deep) Learning-based Robustification in 5G networks
- Nadia Charef, AI-based Energy Models for Polymorphic Duty-Cycling in WSN based IoT Nets
- Marianna Oleotti, Spatio-Temporal Graph Convolution Neural Networks (STG-CNN) for Semantic Understanding of Environment
- Kalyan Reddy Karnati Pavan, Cognitive Agents learning by imitating social interactions
- John Wannerkawahara, Context-aware proactive alerts for bicycle riders
- Nikita Lizbeth Punnoose, Dynamic resource allocation for Edge computing
- Noor Zisad Sharif, Evolutionary BRBES based Explainable AI to predict air pollution
- Hassan Adam Ali Manasik, Green networking using N-way data decompositions
- Md Sakibul Islam, Logging geolocation information of UEs (User Experience) in an industrial IoT setting using Blockchain based distributed ledger technology
- Chandan Singh, Machine learning trained by laser diagnostics for clean combustion modeling: an aiding tool for identification and prediction of combustion regimes
- Nadir Arfi, Mission-based Ad-Hoc Networks for UAM (Urban Air Mobility) swarm UAS (Unmanned Aerial System) using a Distributed tree algorithm
- Smritikana Maity, Public town art using mixed reality – Cloud native deployment of mixed reality publications for social interactions
- Long Do Ha, Real-time-sensors
- Muiz Olalekan Raheem, Rogue Drone detection
- Nafisah Abidemi Abdulkadir, Advanced Data Analytics Modelling for Air Quality Assessment
- Brianna Nicole Swan, Strengthening social contacts and care for older people using mixed reality and metaverse for 5G network
- Diana Mustakhova, Sustainable communicating materials
- Arsalan Ahmed, Toward Environmental Digital Twinning: IoT-based Waterbirds Monitoring Case Study
- Daniel Rene Olave Ibanez, Towards automatic deployment of IoT infrastructure for environmental monitoring
- Md Asif Mahmod T Siddique, Unsupervised learning on brain-inspired computers: Exploring Hypreseed algorithms on Intel’s Loihi neuromorphic chip
- Meshal Iqbal Shah, Using AI to generate robot disassembly planning in autonomous remanufacturing process based on slicing and CAD technologies