Overview
Actively mentoring PhD students at MBZUAI on projects spanning RL for LLMs, safe decision-making, and practical applications of machine learning. Focus on developing both technical skills and research independence.
Mentorship Philosophy
I believe effective PhD mentorship goes beyond technical guidance. My approach emphasizes:
- Research Independence: Helping students develop their own research taste and direction
- Technical Depth: Building strong foundations in ML/RL theory and practice
- Communication Skills: Training in writing, presenting, and articulating research contributions
- Career Development: Supporting diverse career paths in academia and industry
Current Students
I’m privileged to work with talented PhD students on cutting-edge problems in reinforcement learning and machine learning. Projects span:
- Reinforcement learning for language model alignment
- Safe decision-making in high-stakes domains
- Transfer learning and domain adaptation
- Practical deployment of RL systems
Mentorship Activities
Regular Activities
- Weekly one-on-one meetings for project discussion and guidance
- Paper reading groups to stay current with latest research
- Practice talks and paper reviews before submissions
- Career development and networking support
Research Skills Development
- Problem formulation and research question design
- Experimental design and rigorous evaluation
- Technical writing and paper structure
- Code organization and reproducibility
Professional Development
- Conference presentation skills
- Networking at research venues
- Collaboration best practices
- Work-life balance in research
Prospective Students
I’m always interested in working with motivated students who are passionate about:
- Reinforcement learning (theory and applications)
- Safe and robust decision-making
- Real-world ML deployment
- Healthcare AI and other high-impact applications
If you’re interested in working together, please don’t hesitate to reach out with your research interests and background.
Mentorship Outcomes
Former mentees have gone on to:
- Publish at top-tier ML venues (NeurIPS, ICML, ICLR, etc.)
- Secure research internships at leading institutions
- Pursue successful careers in both academia and industry
- Continue making impactful contributions to the ML community