Corgnit Research

Brief Introduction

Corgnit Research is a pioneering think tank dedicated to advanced research in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Computational Theory, and other emerging fields in computer science. We aim to drive forward novel applications of these technologies through interdisciplinary research, creating scalable solutions that advance the state-of-the-art.

Our focus includes both theoretical foundations and practical implementations, and we are particularly interested in enhancing the interpretability, efficiency, and ethical considerations of AI systems. Our research leverages both established techniques and cutting-edge innovations to address challenges in real-world applications, ranging from AI-driven healthcare solutions to intelligent autonomous systems.

Our Areas of Work

• Artificial Intelligence (AI) - Conducting research on intelligent systems capable of performing tasks typically requiring human cognition, including reasoning, problem-solving, and decision-making. We explore both symbolic AI and subsymbolic methods, with particular attention to explainable AI (XAI) frameworks.
• Machine Learning (ML) - Developing advanced algorithms to enable machines to learn from data, including supervised, unsupervised, and reinforcement learning techniques. Our work focuses on scalability and generalization, incorporating methods such as transfer learning, meta-learning, and few-shot learning.
• Deep Learning (DL) - We push the boundaries of neural network architectures, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), and explore innovations in generative adversarial networks (GANs) and transformer models like BERT and GPT. A key focus is improving model efficiency and reducing training costs through techniques like pruning and quantization.
• Natural Language Processing (NLP) - Our research in NLP spans various techniques for processing and analyzing human language, such as sentiment analysis, named entity recognition (NER), and machine translation. We delve into advanced models such as transformers and attention mechanisms, aiming to improve language model understanding and reduce bias in NLP systems.
• Computational Theory - Investigating the theoretical underpinnings of computation, including computational complexity, cryptography, algorithms, and formal languages. We work on problems related to NP-completeness, parameterized complexity, and probabilistic algorithms. Additionally, our research involves developing new models of computation, including quantum computing and quantum algorithms.

Publications

Our team publishes regularly in peer-reviewed journals, conferences, and workshops. Below are some of our recent technical papers and articles:

• Adhikari, Tapomoy. "Investigating the Use of Natural Language Processing for Automated Code Generation." Available at SSRN 4419501 (2023).
• Adhikari, Tapomoy. "Advancing Zero Trust Network Authentication: Innovations in Privacy-Preserving Authentication Mechanisms." (2024).
• Adhikari, Tapomoy. "The Impact of Positive Reinforcement on AI Decision-Making Processes." (2024).
• Adhikari, Tapomoy, et. al. "Privacy-Preserving Data Aggregation in Federated Learning for Secure IoT Applications."
• Adhikari, Tapomoy. "MeloHarmony: Exploring Emotion in Crafting AI-Generated Music with Generative Adversarial Network Powered Harmony." Available at SSRN 4575257 (2023).
• Adhikari, Tapomoy. "Parameterized Complexity in Large-Scale Network Problems." (2024).

Collaborations & Partnerships

Corgnit Research actively seeks collaborations with universities, research institutions, governmental bodies, and industry leaders. Our interdisciplinary approach allows us to bridge the gap between theoretical research and practical, real-world applications of advanced computational technologies. We work with partners on projects that explore the ethical and societal implications of AI, as well as on cutting-edge hardware research, including neuromorphic computing and quantum computing.

Collaborative Publications

We are open to collaboration with institutions at any stage to work on areas beyond Computer Science. Special consideration is given to proposals in System Research, Ethics in AI, and Quantum Computing. For research collaboration inquiries, please email us at [email protected].

Our Team

• Tapomoy Adhikari, Chairman & Head of Research
  [email protected] | Homepage

Contact Us

If you are interested in learning more about our research, or wish to connect with us for any other queries, feel free to contact us:

Email: [email protected]