Prof. Akhilesh Tiwari
Department of ASAreas of contribution:Quantun Photonics, Plasmonics, Metamaterials, Space Habitat Modeling, and Process Engineering
M.Tech. in Quantum Information & Technologies (QIT)
Indian Institute of Information Technology Allahabad
The M.Tech. in Quantum Information & Technologies (QIT) program draws on expertise across the Departments of Applied Sciences (AS), Information Technology (IT) and Electronics and Communication Engineering (ECE).
Areas of contribution:Quantun Photonics, Plasmonics, Metamaterials, Space Habitat Modeling, and Process Engineering
Areas of contribution: Machine Learning, Quantum Machine Learning (QML).
Areas of contribution: Big Data Analytics, Machine Learning, Quantum Machine Learning (QML).
Areas of contribution: Neural Networks, Machine Learning.
Areas of contribution: Thin Films, Nanostructures, 2-D Topological Quantum Materials, Photodetectors, Spintronic and Magnetic Devices.
Areas of contribution: Secured Communication (Classical and Quantum).
Areas of contribution: Density Functional Theory (DFT), Nanoelectronic Devices.
Areas of contribution: Machine Learning, Deep Learning.
Areas of contribution: Machine Learning, Hybrid Algorithms.
Areas of contribution: Cyber Security.
Areas of contribution: Classical and Quantum Communication.
Areas of contribution: Analog and Digital VLSI Design.
Areas of contribution: Machine Learning.
Areas of contribution: VLSI System Design, Memory Design.
Areas of contribution: Not specified in the supplied list.
Areas of contribution: Quantum and Post-Quantum Cryptography.
Areas of contribution: Quantum Field Theory, Quantum Information and Computing, Classical and Quantum Gravity, Machine Learning, and Population Modeling.
Areas of contribution: Machine Learning/AI for Wireless Communications, Quantum Information.
Areas of contribution: Quantum materials, Experimental Condensed Matter Physics, DFT, Ceramic Materials, Supercapacitors, Li-ion and Solid-State Batteries.
Areas of contribution: Classical and Quantum Communications, Machine Learning.