The PhD in Electrical Engineering and Computer Science at MIT integrates core engineering with pioneering advances in machine learning, computing theory, robotics, and system architecture. These research ideas span hardware-software co-design, AI, cryptography, and bio-inspired computation.
Quantum Algorithms for Accelerating NP-Hard Problems
Edge AI Chip Design for Low-Power Inference
Secure Federated Learning Architecture for Healthcare Data
Neuromorphic Hardware for Spiking Neural Networks
Explainable AI Techniques for Medical Image Diagnosis
Real-Time Multi-Robot Coordination Using Swarm Intelligence
Photonic Circuits for Optical Neural Network Acceleration
AI-Assisted Compiler Optimization for Embedded Platforms
Next-Gen Wireless Communication Protocol for IoT Devices
Emotion Recognition Using EEG and Deep Learning
Autonomous Vehicle Navigation in Unmapped Terrains
Blockchain-Based Secure Firmware Update Mechanism
Signal Processing Pipeline for Real-Time fMRI Analysis
High-Fidelity Simulation of Quantum Logic Gates
Resilient Microgrid Control Algorithms Using ML
Hardware-Aware NAS (Neural Architecture Search) Techniques
Zero-Knowledge Proof Systems for Privacy-Preserving AI
Vision-Based SLAM (Simultaneous Localization and Mapping) for Indoor Robotics
Design of AI-Powered Intrusion Detection in Smart Homes
Robust Speech Recognition System for Noisy Environments
Adaptive Control Algorithms for Bipedal Robots
Digital Twin Platform for Cyber-Physical Systems Monitoring
Fault-Tolerant Routing in Mesh Networks-on-Chip
Quantum-Safe Cryptographic Protocols for Embedded Systems
Human-AI Collaboration Framework for Decision-Support Systems
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