What is Generative AI?
Before going into the informative details, everyone deserves to know about the history of this topic. Have you realized that the chatbots we use today for…
Recent News
Stay informed about the latest developments, achievements, and events from our lab.
2024
December
- Our paper "Outcome-Based Education: Evaluating Students' Perspectives Using Transformer" has been accepted at the 27th International Conference on Computer and Information Technology (ICCIT 2024)
2024
November
- Our paper "Predictive Analytics for Dementia: Machine Learning on Healthcare Data" got accepted in the 5th Asia Conference on Information Engineering (ACIE 2025) at Phuket, Thailand.
- Our paper “The Next Chapter in Wound Analysis: Introducing a Hybrid Model for Improved Segmentation With the help of Deep Convolutional Neural Network” got accepted in the Journal of Advanced Research in Applied Sciences and Engineering Technology (Q2).
2024
October
- Elite Lab officially launches its website.
2024
September
- Our MultiLangMemeNet paper got accepted at ICMLA 2024. Congratulations to team
- 6/6 papers accepted at 3rd International Conference on Computing Advancements - ICCA 2024. Congratulations to all team members
2024
August
- ELITE Lab was awarded a grant to support groundbreaking work in Explainable AI.
- We formed a new partnership with tech innovators to advance Generative AI solutions.
- ELITE Lab hosted its annual AI symposium, showcasing the latest in NLP and Computer Vision research.
- We launched the ExplainBot project, focusing on enhancing AI transparency and user interaction.
Core Research Areas at Elite Lab
Generative AI
Elite Lab develops models that generate new data, like text or images, expanding the creative potential of AI.
01
Explainable AI (XAI)
We create AI systems that are transparent, offering clear insights into their decisions to build trust and accountability.
02
Natural Language Processing
Our work in NLP advances the ability of machines to understand and generate human language, improving communication with technology.
03
Computer Vision
Elite Lab focuses on algorithms that enable machines to interpret visual data, driving innovation in fields like autonomous systems and healthcare.
04
Human-AI Interaction (HAX)
We design user-friendly interfaces and experiences, enhancing the way people interact with technology.
05
Ongoing Projects
Explore the innovative projects currently underway at ELITE Lab.
ExplainBot
An AI-powered chatbot that delivers clear, understandable responses and explanations for complex queries, combining the strengths of NLP and XAI to enhance user interaction.
HoloInteract
An advanced Human-Computer Interaction project that uses augmented reality (AR) to create immersive, user-friendly interfaces, enhancing experiences in education and training.
VisionX
A computer vision system that detects and classifies objects in real-time, optimized for healthcare and autonomous navigation, leveraging Explainable AI to interpret visual data.
Recent Publications
Explore the current research contributions and innovations from ELITE Lab
The Generative AI Landscape in Education: Mapping the Terrain of Opportunities, Challenges and Student Perception
by Zishan Ahmed, Shakib Sadat Shanto, Most Humayra Khanom Rime, Md. Kishor Morol, Nafiz Fahad, Jakir Hossen, Md. Abdullah-Al-Jubair | September 2024 |
DOI: 10.1109/ACCESS.2024.3461874
Generative AI (GAI) technologies like ChatGPT are transforming the educational landscape. Their integration presents significant opportunities for personalized learning and enhanced student engagement but also raises challenges related to academic integrity and the role of human educators. This study aims to provide a comprehensive review on using multiple GAI tools and their influence on academic outcomes, bridging the gap in the current literature.
A novel integrated logistic regression model enhanced with recursive feature elimination and explainable artificial intelligence for dementia prediction
by Rasel Ahmed, Nafiz Fahad, Md Saef Ullah Miah, Md. Jakir Hossen, Md. Kishor Morol, Mufti Mahmud, M. Mostafizur Rahman | December 2024 | DOI: 10.1016/j.health.2024.100362
Dementia is a major global health issue that significantly impacts millions of individuals, families, and societies worldwide, creating a substantial burden on healthcare systems. This study introduces a novel approach for predicting dementia by employing the Logistic Regression (LR) model, enhanced with Recursive Feature Elimination (RFE), applied to a unique dataset comprising 1000 patients, with 49.60% male and 50.40% female.
Leadership team
Introducing the Talented Individuals Driving Innovation at ELITE Lab
Nafiz Fahad
Research Assistant
Shakib Sadat Shanto
Research Assistant
Zishan Ahmed
Research Assistant
Md. Muzakker Hossain
Lead of NLP TeamLatest post. Don’t miss it.
Subscribe to newsletter & get company news.
