Machine Learning and NLP Transformers — The group is affiliated with the NVIDIA Deep Learning Institute, and student researchers focusing on Large Language Models (LLMs) have the opportunity to earn NVIDIA certification in Large Language Models with Prompt Engineering.

Mission Statement:

The mission is to advance the frontiers of ML and NLP through cutting-edge research, collaboration, and interdisciplinary approaches. We strive to develop robust algorithms, models, and systems that enhance human-machine interaction, automate tasks, and extract meaningful insights from vast volumes of unstructured data.

Expertise:

With a collective focus on ML and NLP, our group possesses a diverse range of expertise. From deep learning and reinforcement learning to computational linguistics and semantic analysis, we leverage state-of-the-art techniques and methodologies to tackle real-world challenges.

Research Focus Areas:

1. Natural Language Understanding: Our group investigates methods for improving machines' comprehension of human language, including tasks such as sentiment analysis, entity recognition, and text summarization.

2. Language Generation: We delve into generating human-like text, including dialogue systems, machine translation, and content creation for various applications.

3. Deep Learning Architectures: We explore novel architectures and frameworks for building efficient and scalable ML models, encompassing convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers.

4. Multimodal Learning: Our research involves the fusion of multiple modalities, such as text, images, and audio, to develop comprehensive AI systems capable of understanding and generating content across different formats.

5. Ethical AI: In alignment with ethical considerations, we study fairness, transparency, and accountability in AI systems, ensuring our research contributes to responsible AI development.

Active members of this group:

Publications

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