Sajal K. Das
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View article: FedFusion: Federated Learning with Diversity- and Cluster-Aware Encoders for Robust Adaptation under Label Scarcity
FedFusion: Federated Learning with Diversity- and Cluster-Aware Encoders for Robust Adaptation under Label Scarcity Open
Federated learning in practice must contend with heterogeneous feature spaces, severe non-IID data, and scarce labels across clients. We present FedFusion, a federated transfer-learning framework that unifies domain adaptation and frugal l…
View article: FedFiTS: Fitness-Selected, Slotted Client Scheduling for Trustworthy Federated Learning in Healthcare AI
FedFiTS: Fitness-Selected, Slotted Client Scheduling for Trustworthy Federated Learning in Healthcare AI Open
Federated Learning (FL) has emerged as a powerful paradigm for privacy-preserving model training, yet deployments in sensitive domains such as healthcare face persistent challenges from non-IID data, client unreliability, and adversarial m…
View article: Energy-Efficient Split Learning for Resource-Constrained Environments: A Smart Farming Solution
Energy-Efficient Split Learning for Resource-Constrained Environments: A Smart Farming Solution Open
Smart farming systems encounter significant challenges, including limited resources, the need for data privacy, and poor connectivity in rural areas. To address these issues, we present eEnergy-Split, an energy-efficient framework that uti…
View article: A Parallel Algorithm for Finding Robust Spanners in Large Social Networks
A Parallel Algorithm for Finding Robust Spanners in Large Social Networks Open
Social networks, characterized by community structures, often rely on nodes called structural hole spanners to facilitate inter-community information dissemination. However, the dynamic nature of these networks, where spanner nodes may be …
View article: CARGO: A Co-Optimization Framework for EV Charging and Routing in Goods Delivery Logistics
CARGO: A Co-Optimization Framework for EV Charging and Routing in Goods Delivery Logistics Open
With growing interest in sustainable logistics, electric vehicle (EV)-based deliveries offer a promising alternative for urban distribution. However, EVs face challenges due to their limited battery capacity, requiring careful planning for…
View article: Enhancing Federated Survival Analysis through Peer-Driven Client Reputation in Healthcare
Enhancing Federated Survival Analysis through Peer-Driven Client Reputation in Healthcare Open
Federated Learning (FL) holds great promise for digital health by enabling collaborative model training without compromising patient data privacy. However, heterogeneity across institutions, lack of sustained reputation, and unreliable con…
View article: DATAMUt: Deterministic Algorithms for Time-Delay Attack Detection in Multi-Hop UAV Networks
DATAMUt: Deterministic Algorithms for Time-Delay Attack Detection in Multi-Hop UAV Networks Open
Unmanned Aerial Vehicles (UAVs), also known as drones, have gained popularity in various fields such as agriculture, emergency response, and search and rescue operations. UAV networks are susceptible to several security threats, such as wo…
View article: Iterative Recommendations based on Monte Carlo Sampling and Trust Estimation in Multi-Stage Vehicular Traffic Routing Games
Iterative Recommendations based on Monte Carlo Sampling and Trust Estimation in Multi-Stage Vehicular Traffic Routing Games Open
The shortest-time route recommendations offered by modern navigation systems fuel selfish routing in urban vehicular traffic networks and are therefore one of the main reasons for the growth of congestion. In contrast, intelligent transpor…
View article: When Federated Learning Meets Quantum Computing: Survey and Research Opportunities
When Federated Learning Meets Quantum Computing: Survey and Research Opportunities Open
Quantum Federated Learning (QFL) is an emerging field that harnesses advances in Quantum Computing (QC) to improve the scalability and efficiency of decentralized Federated Learning (FL) models. This paper provides a systematic and compreh…
View article: Non-Convex Optimization in Federated Learning via Variance Reduction and Adaptive Learning
Non-Convex Optimization in Federated Learning via Variance Reduction and Adaptive Learning Open
This paper proposes a novel federated algorithm that leverages momentum-based variance reduction with adaptive learning to address non-convex settings across heterogeneous data. We intend to minimize communication and computation overhead,…
View article: Persistent monitoring of insect-pests on sticky traps through hierarchical transfer learning and slicing-aided hyper inference
Persistent monitoring of insect-pests on sticky traps through hierarchical transfer learning and slicing-aided hyper inference Open
Introduction Effective monitoring of insect-pests is vital for safeguarding agricultural yields and ensuring food security. Recent advances in computer vision and machine learning have opened up significant possibilities of automated persi…
View article: Collision-free Exploration by Mobile Agents Using Pebbles
Collision-free Exploration by Mobile Agents Using Pebbles Open
In this paper, we study collision-free graph exploration in an anonymous pot labeled network. Two identical mobile agents, starting from different nodes in $G$ have to explore the nodes of $G$ in such a way that for every node $v$ in $G$, …
View article: Next generation power inverter for grid resilience: Technology review
Next generation power inverter for grid resilience: Technology review Open
Distributed generation (DG) systems are becoming more popular due to several benefits such as clean energy, decentralization, and cost effectiveness. Because the majority of renewable energy sources provide DC power, power electronic inver…
View article: Tackling Selfish Clients in Federated Learning
Tackling Selfish Clients in Federated Learning Open
Federated Learning (FL) is a distributed machine learning paradigm facilitating participants to collaboratively train a model without revealing their local data. However, when FL is deployed into the wild, some intelligent clients can deli…
View article: CTG-KrEW: Generating Synthetic Structured Contextually Correlated Content by Conditional Tabular GAN with K-Means Clustering and Efficient Word Embedding
CTG-KrEW: Generating Synthetic Structured Contextually Correlated Content by Conditional Tabular GAN with K-Means Clustering and Efficient Word Embedding Open
Conditional Tabular Generative Adversarial Networks (CTGAN) and their various derivatives are attractive for their ability to efficiently and flexibly create synthetic tabular data, showcasing strong performance and adaptability. However, …
View article: Smart connected farms and networked farmers to improve crop production, sustainability and profitability
Smart connected farms and networked farmers to improve crop production, sustainability and profitability Open
To meet the grand challenges of agricultural production including climate change impacts on crop production, a tight integration of social science, technology and agriculture experts including farmers are needed. Rapid advances in informat…
View article: Tackling Selfish Clients in Federated Learning
Tackling Selfish Clients in Federated Learning Open
Federated Learning (FL) is a distributed machine learning paradigm facilitating participants to collaboratively train a model without revealing their local data. However, when FL is deployed into the wild, some intelligent clients can deli…
View article: Addressing Data Heterogeneity in Federated Learning of Cox Proportional Hazards Models
Addressing Data Heterogeneity in Federated Learning of Cox Proportional Hazards Models Open
The diversity in disease profiles and therapeutic approaches between hospitals and health professionals underscores the need for patient-centric personalized strategies in healthcare. Alongside this, similarities in disease progression acr…
View article: Towards net zero: A technological review on the potential of space-based solar power and wireless power transmission
Towards net zero: A technological review on the potential of space-based solar power and wireless power transmission Open
The global need for energy is increasing at a high rate and is expected to double or increase by 50%, according to some studies, in 30 years. As a result, it is essential to look into alternative methods of producing power. Solar photovolt…
View article: A Human-Centered Power Conservation Framework Based on Reverse Auction Theory and Machine Learning
A Human-Centered Power Conservation Framework Based on Reverse Auction Theory and Machine Learning Open
Extreme outside temperatures resulting from heat waves, winter storms, and similar weather-related events trigger the Heating Ventilation and Air Conditioning (HVAC) systems, resulting in challenging, and potentially catastrophic, peak loa…
View article: TASR: A Novel Trust-Aware Stackelberg Routing Algorithm to Mitigate Traffic Congestion
TASR: A Novel Trust-Aware Stackelberg Routing Algorithm to Mitigate Traffic Congestion Open
Stackelberg routing platforms (SRP) reduce congestion in one-shot traffic networks by proposing optimal route recommendations to selfish travelers. Traditionally, Stackelberg routing is cast as a partial control problem where a fraction of…
View article: Drone-Based Bug Detection in Orchards with Nets: A Novel Orienteering Approach
Drone-Based Bug Detection in Orchards with Nets: A Novel Orienteering Approach Open
The use of drones for collecting information and detecting bugs in orchards covered by nets is a challenging problem. The nets help in reducing pest damage, but they also constrain the drone’s flight path, making it longer and more complex…
View article: A Comprehensive Survey of Data-Driven Solutions for LoRaWAN: Challenges & Future Directions
A Comprehensive Survey of Data-Driven Solutions for LoRaWAN: Challenges & Future Directions Open
Long-range Wide-area Network (LoRaWAN) is an innovative and prominent communication protocol in the domain of Low-power Wide-area Networks (LPWAN), known for its ability to provide long-range communication with low energy consumption. Howe…
View article: Mobility Management in TSCH-Based Industrial Wireless Networks
Mobility Management in TSCH-Based Industrial Wireless Networks Open
Wireless Sensor and Actuator Networks (WSANs) are an effective technology for improving the efficiency and productivity in many industrial domains, and are also the building blocks for the Industrial Internet of Things (IIoT). To support t…
View article: LASA-R: Location-Aware Scheduling Algorithm With Rescheduling for Industrial IoT Networks With Mobile Nodes
LASA-R: Location-Aware Scheduling Algorithm With Rescheduling for Industrial IoT Networks With Mobile Nodes Open
The synchronized single-hop multiple gateway (SHMG) framework has been recently proposed to support mobility in 6TiSCH, the network architecture defined by the IETF for the Industrial Internet of Things (IIoT). SHMG includes a scheduling p…