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PhD in Machine Learning and Robotics

• Probabilistic machine learning
• World models and model based reinforcement learning
• Thesis on hierarchical world models
• CGPA:1.0(HighestPossibleGrade)

MTech in Machine Learning and Computing

• Pattern recognition and data mining
• Reinforcement learning
• Probabilistic and statistical methods

BTech in Electrical Engineering

• CGPA 8.1 out of 10

Postdoctoral Researcher

• Bayesian methods for safe and controllable language models
• Uncertainty aware and probabilistic inference
• Developing Bayesian primitives for safe and controllable language models
• Improving steerability robustness and uncertainty using probabilistic and control methods

PhD Researcher

• Sequential and probabilistic world models
• Decision making under uncertainty
• Teaching and student supervision

Research Assistant

• Computer vision research on knowledge distillation and adversarial robustness with publications at ICML 2019 and CVPR 2019 workshops

Data Scientist

• Adversarial machine learning for security
• Anomaly detection systems
• Built probabilistic sequential world models for dynamics learning and decision making under uncertainty

Researcher and Graduate Intern

• Malware detection using deep learning
• Sparse machine learning for audio analysis
• Developed and deployed a deep neural network based dynamic malware classification system for security applications

• Magna Cum Laude with highest doctoral grade at KIT

• McAfee CEO Innovator of the Year finalist

• Department of Space fellowship

• GATE examination 98th percentile