• Modeling and performance evaluation of OpenFlow switches using a MAP/PH/1/n queueing model 

  Shekhawat, Virendra Singh; Kulshrestha, Rakhee (Elsevier, 2025-07)

  Software-Defined Networking (SDN) is a paradigm shift in network architecture. It decouples the control plane from the data plane to enable centralized network management and programmability. While Software Defined Networks ...
• Use of stem cell-derived cardiomyocyte and nasal epithelium models to establish a multi-tissue model platform to validate repurposed drugs against sars-cov-2 infection 

  Agarwal, Vinti (2024-05)

  The novel coronavirus disease (COVID-19) and any future coronavirus outbreaks will require more affordable, effective and safe treatment options to complement current ones such as Paxlovid. Drug repurposing can be a promising ...
• An efficient and scalable byzantine fault tolerant consensus for vehicular networks 

  Alladi, Tejasvi (IEEE, 2025)

  Vehicular networks represent a new distributed system paradigm that requires robust fault tolerance to ensure reliable operation. As a burgeoning area of research, the scalability and optimization of consensus mechanisms ...
• Leveraging precision agriculture techniques using UAVs and emerging disruptive technologies 

  Gupta, Shashank (Elsevier, 2024-07)

  The next great innovation in Unmanned Aerial Vehicles (UAV) technology is smart UAVs, which aim to provide new possibilities in numerous applications. There is an increasing usage of UAVs in various fields of civil ...
• Optimizing quality-of-service (QOS) using semantic sensing and digital-twin in pro-dynamic internet of vehicles (IOV) 

  Gupta, Shashank (IEEE, 2024-11)

  The emerging autonomous driving industry expects real-time information to be communicated in less amount of time. Most of the extant research works on deterministic or stochastic channels, which are deemed unrealistic for ...
• Artificial intelligence inspired task offloading and resource orchestration in intelligent transportation systems 

  Gupta, Shashank (Springer, 2025)

  Internet of Vehicles (IoV) applications require the support of communication, caching, and computation (3C) resources to offload the computation-intensive tasks and for uplifting the traffic conditions in the development ...
• ST-IDS: Spatio-temporal feature-based multi-tier intrusion detection system for artificial intelligence-powered connected autonomous vehicles 

  Gupta, Shashank (Wiley, 2025-03)

  Advancements in 3GPP specifications and the extensive deployment of 5G networks have driven significant growth in the Internet of Vehicles (IoVs). This development has led to an increase in Connected and Autonomous Vehicles ...
• HS-GIoV: High-speed green internet of vehicles (IoV) edge-assisted model for low-latency inference in autonomous driving 

  Gupta, Shashank (Elsevier, 2025-08)

  Green IoV has emerged as a latent solution in the field of autonomous driving for the future Intelligent transportation system (ITS) accompanied with green wireless communication and computational intelligence. It facilitates ...
• Ensemble Gaussian mixture model-based special voice command cognitive computing intelligent system 

  Jangiti, Saikishor (Sage, 2020-08)

  Dysarthria is a speech disorder caused by stroke, Parkinson’s disease, neurological injury, or tumors that damage the nervous system and weaken the speech quality. Developing a unique voice command system for Dysarthric ...
• Leveraging dual encoders with feature disentanglement for anomaly detection in thermal videos 

  Goyal, Poonam (Springer, 2024-12)

  Anomaly detection is critical for real-time applications, e.g., monitoring elderly people or kids from a remote place; gas leakage detection, night vision surveillance, etc. Detecting anomalous behavior becomes even more ...
• AdQuestA: knowledge-guided visual question answer framework for advertisements 

  Goyal, Poonam (IEEE, 2025)

  In the rapidly evolving landscape of digital marketing, effective customer engagement through advertisements is crucial for brands. Thus, computational understanding of ads is pivotal for recommendation, authoring, and ...
• Enhanced multispectral band-to-band registration using co-occurrence scale space and spatial confined ransac guided segmented affine transformation 

  Rohil, Mukesh Kumar (IEEE, 2024-11)

  Band-to-Band Registration (BBR) is a pre-requisite image processing operation essential for specific remote sensing multispectral sensors. BBR aims to align spectral wavelength channels at sub-pixel level accuracy over ...
• Classification and study of music genres with multimodal Spectro-Lyrical Embeddings for Music (SLEM) 

  Narang, Pratik (Springer, 2024-04)

  The essence of music is inherently multi-modal – with audio and lyrics going hand in hand. However, there is very less research done to study the intricacies of the multi-modal nature of music, and its relation with genres. ...
• InFER++: real-world indian facial expression dataset 

  Challa, Jagat Sesh; Narang, Pratik (IEEE, 2024-08)

  Detecting facial expressions is a challenging task in the field of computer vision. Several datasets and algorithms have been proposed over the past two decades; however, deploying them in real-world, in-the-wild scenarios ...
• LDFaceNet: latent diffusion-based network for high-fidelity deepfake generation 

  Narang, Pratik (Springer, 2024-12)

  Over the past decade, there has been tremendous progress in the domain of synthetic media generation. This is mainly due to the powerful methods based on generative adversarial networks (GANs). Very recently, diffusion ...
• Balancing the scales: enhancing fairness in facial emotion recognition with latent alignment 

  Narang, Pratik (Springer, 2024-12)

  Automatically recognizing emotional intent using facial expression has been a thoroughly investigated topic in the realm of computer vision. Facial Expression Recognition (FER), being a supervised learning task, relies ...
• AffectSRNet: facial emotion-aware super-resolution network 

  Narang, Pratik (2025-02)

  Facial expression recognition (FER) systems in low-resolution settings face significant challenges in accurately identifying expressions due to the loss of fine-grained facial details. This limitation is especially problematic ...
• Load-aware resource scheduling in fog computing based delay-sensitive IOT networks 

  Rajya Lakshmi, L. (IEEE, 2023-08)

  Internet of Things (IoT), with its capability to connect anything, anywhere, anytime, bringing in revolutionary changes in data collection, processing and utilization. IoT networks generate a huge amount of data, which is ...
• Layered blockchain-based mobile crowdsensing architecture: exploring privacy and scalability challenges across layers 

  Bhatia, Ashutosh; Tiwari, Kamlesh (Springer, 2025-04)

  Blockchain technology has emerged as a transformative solution for addressing the limitations of traditional Mobile CrowdSensing (MCS) systems, which rely on centralized architectures. Despite its promise, the integration ...
• A layered framework for blockchain security: classification of threats and the quantum computing impact 

  Bhatia, Ashutosh; Tiwari, Kamlesh (Springer, 2025-04)

  Blockchain technology, with its transformative potential across industries, has ushered in a new era of decentralized systems. However, its widespread adoption has exposed vulnerabilities at various layers of its architecture, ...

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