IIIT Allahabad · Department of IT
MLO Lab
Machine Learning & Optimization
Research in |
70+Publications
15+Researchers
5Research Areas
IIIT Allahabad campus view.
Machine Learning & Optimization
Research in |
The Machine Learning and Optimization Lab (MLO Lab), Department of Information Technology at the Indian Institute of Information Technology Allahabad (IIIT Allahabad) is a research-driven laboratory dedicated to advancing the foundations and applications of modern Artificial Intelligence, Machine Learning, and Optimization.
Our research focuses on developing intelligent, reliable, and secure AI systems capable of addressing real-world challenges across diverse domains. The lab actively explores cutting-edge areas including Safe AI, Adversarial Attacks and Defenses, Continual Learning, Federated Learning, Trustworthy AI, and Security in Machine Learning.
Through interdisciplinary collaboration, rigorous experimentation, and a strong commitment to scientific excellence, the Machine Learning and Optimization Lab strives to contribute to the development of next-generation AI technologies that are secure, resilient, and beneficial to society.
Exploring the foundations of Safe AI through adversarial robustness, security, continual learning, and privacy-preserving machine learning.
Developing trustworthy, reliable, and interpretable artificial intelligence systems that can operate safely in real-world environments. Our research focuses on robustness, fairness, transparency, uncertainty estimation, and alignment to ensure AI systems make dependable decisions while minimizing risks and unintended consequences.
Investigating the vulnerabilities of machine learning models to adversarial manipulations and designing effective defense mechanisms. We study adversarial examples, evasion attacks, poisoning attacks, and robust training strategies to improve the resilience and security of AI systems against malicious threats.
Building intelligent systems that can continuously learn from new data and tasks without forgetting previously acquired knowledge. We develop algorithms that enable adaptive learning, knowledge retention, and efficient model updates, allowing AI systems to evolve in dynamic and changing environments.
Designing privacy-preserving distributed learning frameworks that enable multiple devices or organizations to collaboratively train machine learning models without sharing raw data. Our research addresses challenges related to communication efficiency, security, personalization, robustness, and privacy protection in decentralized environments.
Exploring security challenges throughout the machine learning lifecycle, including data integrity, model confidentiality, privacy preservation, and trustworthy deployment. Our work aims to identify emerging threats such as backdoor attacks, model extraction, and data leakage while developing secure learning frameworks.
Stay informed about our latest research achievements, publications, collaborations, workshops, and academic activities.
We are looking for highly motivated Ph.D. students. If you are interested in joining our research group, please send your CV, academic transcripts, and a brief statement of research interests to kpsingh@iiita.ac.in.
Glimpses of life at the MLO Lab — research activities, events, workshops, and celebrations.