1. Dr. Upasna Joshi

Designation: Head Of Department, AI

Research Specialization: Deep Learning, Reinforcement Learning

    Projects Undertaken:

  • Automatic Exam Paper Generation using Dynamic Structured Databases
  • Deep Learning in Ultrasound-Guided Regional Anesthesia
  • MERN-Based Real-Time Video Conferencing Systems
  • Copy-Move Forgery Detection with Deep Learning and DCT

Publications In:

  • Scopus Indexed Journals
  • IEEE International Conference Proceedings

Selected Publications:

  1. “Automatic Exam Paper Generator Using Dynamic Structured and Intelligent Database”
    Scopus Indexed Journal
  2. “Ultrasound-Guided Deep Learning for Regional Nerve Block Anesthesia in Scapular Fracture”
    IEEE Conference Proceedings
  3. “A Videoconferencing Framework for Real-Time Applications Based on MERN Architecture”
    Scopus Indexed Journal
  4. “An Intellectual Copy-Move Forgery Detection System Using Deep Learning with Discrete Cosine Transform and Block-Based Features”
    Scopus Indexed Journal

2. Dr. Preeti Raj Verma

Designation: Assistant Professor, Dept Of AI

Research Specialization: Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Agricultural Intelligence

Projects Undertaken:

  • DynLeafNet for Plant Disease Detection
  • Transfer Learning in Plant Disease Detection
  • Survey on Neural Network Evolution
  • Interactive Deep Neural Architectures
  • Rice Leaf Disease Detection using Grad-CAM
  • Agritech Solutions Using Dynamic Networks

Publications In:

  • SCI (Science Citation Index) Journals – 4 Publications
  • Scopus Indexed Journals – 2 Publications

Selected Publications:

  • “DynLeafNet: A Novel Dynamic Approach for Plant Disease Classification Using Dynamic Residual Network with Explainable Artificial Intelligence”
    SCI Indexed Journal
  • “Plant Disease Detection with Transfer Learning: Evaluating the Impact of Various Loss Functions and Explainable AI”
    SCI Indexed Journal
  • “Neural Network Developments: A Detailed Survey from Static to Dynamic Models”
    Scopus Indexed Journal
  • “Unleashing the Power of Deep Neural Networks: An Interactive Exploration of Static and Dynamic Architectures”
    SCI Indexed Journal
  • “A Novel Framework for Rice Leaf Disease Detection using Mixed Precision and Grad-CAM”
    SCI Indexed Journal
  • “The Future of Agritech: Implementing Dynamic Neural Network for Early Detection of Plant Diseases”
    Scopus Indexed Journal

3. Ms. Sudha Bhatia

Designation: Assistant Professor, Dept Of AI

Research Specialization: Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL)

Projects Undertaken:

  • AI-Enabled IoT Solutions in Healthcare
  • Graphics Rendering Pipeline Optimization
  • Data Forecasting through Ensemble ML Techniques

Publications In:

  • Scopus Indexed Journals
  • IEEE Conference Proceedings

Selected Publications:

  1. “AI-enabled IoT for Healthcare Acceptability and Implementation Challenges”
    Scopus Indexed Journal
  2. “Emerging Trends and Technologies in Graphics Rendering Pipeline”
    Scopus Indexed Journal

“An Ensemble Approach for Data Forecasting using Machine Learning Techniques and Learning from Knowledge Assimilation”
IEEE Conference Proceedings

4. Ms. Neha Sehgal

Designation: Assistant Professor, Dept Of AI

Research Specialization: Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL)

Projects Undertaken:

  • AI-Driven IoT Solutions for Healthcare
  • Data Forecasting with Ensemble Machine Learning
  • Pretraining and Control in Image Synthesis
  • Advancements in Graphics Rendering Technologies

Publications In:

  • IEEE Conference Proceedings
  • Scopus Indexed Journals

Selected Publications:

  1. “AI-enabled IoT for Healthcare Acceptability and Implementation Challenges”
    Scopus Indexed Journal
  2. “An Ensemble Approach for Data Forecasting using Machine Learning Techniques and Learning from Knowledge Assimilation”
    IEEE Conference Proceedings
  3. “Advancements in Image Synthesis: A Survey of Pretraining, Control Mechanisms”
    IEEE Conference Proceedings

“Emerging Trends and Technologies in Graphics Rendering Pipeline”
Scopus Indexed Journala

5. Ms. Muntaha Rouf

Designation: AI Engineer, Dept. Of AI

Research Specialization: Generative Artificial Intelligence (GenAI), Deep Learning (DL), Machine Learning (ML), Sign Language Processing, Natural Language Processing (NLP), Speech Synthesis

Projects Undertaken:

  • RF-Controlled Solar-Based Robotic Drone
    Engineered an AI-powered, solar-based drone system with RF communication, achieving improved operational efficiency, terrain adaptability, and real-time image processing.
  • Sign Language Translation Using Generative AI
    Developed a multi-modal translation system integrating Tacotron and WaveNet architectures for real-time sign language-to-speech translation, significantly enhancing accessibility.
  • Advanced Text-to-Speech Using Generative AI
    Created a high-fidelity text-to-speech engine using Tacotron 2 and WaveNet, delivering human-like synthesized speech with low latency and high user satisfaction.
  • Unified Generative AI System for TTS and Sign Language
    Designed an integrated platform combining speech synthesis and gesture recognition for real-time, cloud-based deployment—achieving high scalability and 95% accuracy.

Publications In:

  • IEEE Conference Proceedings
  • Springer Journals
  • Scopus Indexed Journals

Selected Publications:

  1. “RF-Controlled Solar-Based Robotic Drone with AI-based Vision System”
    Published in Scopus Indexed Journal
  2. “Sign Language Translation Using Generative AI and Speech Integration”
    Published in IEEE Conference Proceedings
  3. “Tacotron-based Text-to-Speech System Enhanced with WaveNet for Realistic Voice Generation”
    Published in Springer Journal

“Generative AI Framework for Multimodal Accessibility: TTS and Sign Language Translation”
Published in IEEE Conference Proceedings

6. Ms. Maroofa Yaseen

Designation: AI Engineer, Dept Of AI

Research Specialization: Artificial Intelligence (AI), Deep Learning (DL), Machine Learning (ML), Generative AI, Time-Series Analysis

Projects Undertaken:

  • Image Recognition and Classification using Convolutional Neural Networks (CNNs)
  • Bitcoin Price Prediction Using Generative AI

Publications In:

  • IEEE Conference Proceedings
  • Springer Journals

Selected Publications:

  • “Image Recognition and Classification using CNN: A Review”
    Published in IEEE Conference Proceedings

“Time Series Demand Prediction of Bitcoin Prices Using Generative AI”
Published in Springer Journal

7. Mr. Dibyanarayan Hazra

Designation: Assistant Professor, Dept Of AI

Research Specialization: Artificial Intelligence (AI), Deep Learning (DL), Internet of Things (IoT), Federated Learning (FL)

Projects Undertaken:

  • Federated Learning Framework for Brain Tumor Detection
  • Breast Cancer Classification on Low-Power IoT Devices
  • IoT-Enabled Indian Food Classification Using Deep Learning.
  • Sports Image Data Classification via Federated Learning
  • Potato Leaf Disease Classification Using Federated Learning.

Publications In:

  • IEEE Conference Proceedings
  • SCIE (Science Citation Index Expanded) Journals
  • Springer Journals

Selected Publications:

  • “Generalized Framework Using Federated Learning for Brain Tumor Detection from Medical Images”
    IEEE Conference Proceedings
  • “The Efficient Classification of Breast Cancer on Low-Power IoT Devices: A Study on Genetically Evolved U-Net”
    Published in SCIE Journal
  • “Development of IoT Enabled Deep Learning Model for Indian Food Classification: An Approach Based on Differential Evaluation”
    Published in Springer Journal
  • “Enhancing Sports Image Data Classification in Federated Learning through Genetic Algorithm-Based Optimization”
    IEEE Conference Proceedings
  • “Potato Leaf Disease Classification Using Federated Learning”
    Published in SCIE Journal