PhD and Research Masters

• Stephen Azeez, Affinity Graph Neural Networks with Attention for IEEE 802.11 ax Wireless Local Area Networks, Principal Supervisor

• Mohammad Ibrahim, Self-supervised Graph-based Deep Learning for Service Function Chain Orchestration in Fog Computing, Principal Supervisor, Co-supervisor, Professor Brendan Jennings

• Zulfiqar Ali, Efficient Adaptive Data Rate and Multiple Access in Long Range Wide Area Networks ( LoRaWAN), Bahria University, Islamabad, PhD Co-supervisor

• Muhmmad Bilal Haider, SDN-based Mobility Management in Vehicular Ad hoc Networks: Algorithms and Architectures, PhD Co-supervisor

Completed Master's Dissertations (60+)

Masters 2022 (Completed)

• Abhilash Kumar, Irish Sign Language Recognition using Vision and Hierarchical Vision Transformer using Shifted Windows .

• Sriram Muthaiah, Threatening Object Detection for Surveillance using Videos with Mask Region-based Convolutional Neural Network.

• Sreejesh Thankappan Pillai Jayachandran Nair,A Particle Swarm Optimization Approach to Based Deep Reinforcement Learning Approach for Dynamic Pricing.

• Nishant Ranjan Verma, Inflation Forecasting using Hybrid Neural Networks with Attention in EU .

• Noel Hynes, Hybrid Prophet-deBiLSTM: Hybrid Model using Prophet and Seasonal Decomposition (STL)-based-BiLSTM Model for Stock Market Predictions.

• Aishwarya Moray, Architectural Implications of Function as a Service (FaaS) Serverless Computing on Quality of Service.

• Aswin Rajasekharan, Responsible and Explainable Adversarial Deep Learning for Malicious Domain Detection using Local Explanation.

• Fazeelat Nandgadi, Generative Adversarial Networks (GANs) based on Convolutional Neural Networks for Forgery Detention.

• Lakshya Gourav Moitra, Responsible Machine Learning for Cyber-security.

• Mallikharjuna Rao Sakhamuri , GraphImmuno: Graph Convolutional Neural Networks with Physicochemical Properties for Adaptive Immune Response.

• Miriyam Philip Venattu, Distributed Deep Learning using Spark and BigDL Orca.

• Olajide Adewale Olaniyan, Superconstrastive Learning for Vision Transformers using Patch Embeddings (Convmixer-Contrastiveloss) for Image Processing.

• Paulson Grigarichan, An Attention-based Gated Recurrent Unit Model for Recalibration of Wireless Sensor Networks for Air Pollution Monitoring.

• Oluwasei Adebeye, Cloud Services for Distributed and Scalable Deep Learning and Model Optimization

Masters Theses -2021 (completed)

• Mohammad Ibrahim, Self-supervised Learning for Graph Convolutional Neural Networks for Breast Cancer Detection.

• Juan Miguel Lopez, Explainable AI: Interpretable Convolutional Filtres, Features Maps, and Predictions in Convolutional Neural Networks.

• Rajinder Singh, T-FasterRCNN: Transfer Learning for Faster Recurrent Convolutional Neural Networks for Real-time Traffic Classification.

• Bilal Ali Saiyed, Extremist Group Identification based on Bidirectional Sequence to Sequence Deep Learning using Sentiment Analysis of Reviews and Ratings.

• Varun Sehgal, Bidirectional Long Short Term Memory with Attention (BiLSTM-with-attention) for Sentiment Analysis using Drug Reviews.

• Catherine de Andres Arceno, Homogeneous and Heterogeneous Ensemble Transfer Learning for Breast Cancer Classification .

• Pooja Prakash Awalegaonkar, Multimodal Deep Learning for Emotion Recognition.

• Nikita Ganesh Phirke, Cascaded Convolutional Neural Networks using Separable Convolution and Residual Structure in GoogleNet (CascadedCNN-GoogleNet) for Face Detection.

• Siddharth Bangera, Stacked Ensemble Approach to Deep Learning for Employee Attrition Prediction .

• Hardik Trivedi, Attention for Music: Multi-head Attention for Content-based Music Classification.

• Raghav Thakur, Attention-based-bidirectional (Attention-based-BiLSTM) Deep Learning for Weather Prediction.

Masters Theses -2019 (completed)

• Praveen David Mathew, A Self-Adaptive Approach to Security and Functional Testing (Five-Stage-DevSecOps) in CI/CD Pipeline

• Bailon Manlagnit Jr.,Double Transfer Learning Based Approach for Breast Cancer Detection

• Chitteti Vijay, Zombie Attacks Prediction and Isolation based on Machine Learning

• Aparna Reiji, A Contrast Limited Adaptive Histogram Equalization (CLAHE)-based Transfer Learning Approach for Covid-19 Detection

• Shyam Krishnan Kalliadan, Predictive Customer Relationship Management based on Graph Analytics using Deep Learning

• Saurabh Jangid, A Hybrid Deep Learning Approach for Advanced Persistent Threats Prediction

• David Agboga, Activity Prediction Based on Machine Learning Classifiers Using Talking Device

• Deepak Vikram, Enhancing the Identification of offensive speech with Machine learning techniques

• Ajay Chowdary Vemulapalli ,Deep Learning Approach to Face Mask Detection based on Real Time Video

• Tejinder Singh Ramgadiya, Denial of Service (DoS) Attack Detection based on Recurrent Neural Networks and Long Short-Term Memory

• Yaswanth Venkata Sai Charan Akkisetty, A Machine Learning-Driven Recommender System for Nutrition

• Borja Isabel, Best match question answering chatbot for sport e-commerce websites

• Veera Venkata Siva Rama Krishna Chundru , Malicious URL Prediction based on Machine Learning with Distributed Processing

• Ramisetti Vamsi Krishna, Enhancement of auto scaling techniques using machine learning for virtualized networks

• Janeesh George,Intrusion detection for IoT data using Deep Learning and Machine Learning Algorithms

• Mohammad Faraz, A Co-ordinated Policy Network-based Reinforcement Learning Approach to Virtual Network Embeddings for Virtualized Networks, Waterford Institute of Technology

2016-2020 (completed)

• A learning-based self-adaptive MAC for Wireless Body Area Networks.

• A novel wireless power transfer technique for wireless rechargeable sensor networks.

• Learning-based spectrum utilization for underlay cognitive radio networks.

• Reinforcement learning-based homogeneous coexistence Interference management in Wireless Body Area Network.

• An intelligent optimized charger deployment for rechargeable wireless sensor network based on Q-learning.

• Interference management in bonded channel wireless body area networks based on IEEE 802.15.6.

• An energy aware next hop selection algorithm for Wireless Body Area Networks.

• A novel retransmission strategy for Wireless Body Area Networks.

• A priority-based MAC Protocol for Wireless Body Area Networks.

• HE-PRMAC: Hop Extended Pipelined Routing Enhanced MAC Protocol for Wireless Sensor Networks.

• AS-PW-MAC: An Adaptive Scheduling Predictive Wake-up MAC Protocol for Wireless Sensor Networks.

• Asynchronous Hybrid Duty Cycle MAC Protocol for Wireless Sensor Networks

• Receiver-Initiated asynchronous duty cycle multi-channel MAC protocol for Wireless Sensor Networks.

• Stability Analysis of Multipath Routing under Different Mobility Models in Mobile Ad-hoc Networks.

• Asynchronous Hybrid Duty Cycle MAC Protocol for Wireless Sensor Networks

• Receiver-Initiated Asynchronous Duty Cycle Multi-Channel MAC Protocol for Wireless Sensor Networks.

• Stability Analysis of Multi-path Routing under Different Mobility Models in Mobile Ad-hoc Networks.

Masters 2022 (Progress)

Shishir Akshath Gali, Image processing with reduction of noise and image compression using Autoencoders .

James Griffiths, Sentiment Analysis of Covid-19 using NLP based on Twitter (progress).

Recent Undergraduate Projects

• Connected Fields: An Internet of Things-enabled smart agricultural system

• Connected Cows: An Internet of Things-enabled smart farm

• Virtual Art Gallery based on Augmented Reality

• Alive Learning based on Augmented Reality

• Augmented reality-based snooker world

• An Augmented view of Bahria University, Islamabad, Pakistan

• An Augmented historical view of Bahria University, Islamabad, Pakistan