Hi, I am Shahnawaz
I am a Ph.D. student at the Wallenberg Centre for Quantum Technology at Chalmers University of Technology, Göteborg.
My research interest lies in the intersection of (Q)uantum information and computing and (M)achine (L)earning. I am especially interested in ML methods applied to problems in quantum information - MLQ but will also be working towards developing techniques that may potentially enhance ML using (Q)uantum systems - QML.
Previously, I worked in the the Theoretical Quantum Physics Group of Prof. Franco Nori at Riken, Japan as a master thesis student on numerical approaches to solve problems in Open Quantum Systems.
I have a mix of interests and experiences in
Quantum Information & Computing
Machine Learning
Open Source Scientific Computing
About
– Education –
Chalmers Tekniska Högskola (Göteborg, Sweden)
Doktorand, Applied Quantum Physics, Laboratory, MC2; 2018 - 2022 (expected)
Birla Institute of Technology and Science (Goa, India)
M.Sc.(Hons.) Physics; 2013 - 2018
B.E.(Hons.) Electrical & Electronics; 2013 - 2018
– Experience –
Theoretical Quantum Physics Lab, Riken, Wako, Japan
(International Program Associate, April 2018 - July 2018)
Worked on the development of numerical techniques for simulating open quantum systems for ensembles of qubits and qubits in a bath with strong and ultrastrong coupling. Developed a python package - PIQS in collaboration with Dr. Nathan Shammah as part of the work on:
Open quantum systems with local and collective incoherent processes: Efficient numerical simulations using permutational invariance Phys. Rev. A Nathan Shammah, Shahnawaz Ahmed, Neill Lambert, Simone De Liberato, and Franco Nori Accepted 6 November 2018
Theoretical Quantum Physics Lab, Riken, Wako, Japan
(Bachelor thesis, July 2017 - March 2018)
Bachelor thesis on Deep Learning Constraints - how Deep Neural Networks learn rules and functions from data with the specific case of learning the rules of Sudoku.
Next Generation Computing Lab, Ritsumeikan University
(Intern, Dec 2016 - Jan 2017)
Guide: Prof. Shigeru Yamashita, NGC Lab
Worked on the development of a pipeline for optimization of topological quantum circuits starting from the ICM representation (Paler et al., 2015 ). Developed a code for conversion of quantum circuits to the ICM representation and their visualization. QuTiP PR
Google Summer of Code 2016, Python Software Foundation
(Intern, May 2016 - Aug 2016)
Mentor: Dr. Ariel Rokem, Senior Data Scientist, University of Washington eScience Institute
Developed a python module for Magnetic Resonance Image (MRI) reconstruction based on the Intra-voxel Incoherent Motion model (Le Bihan, 84) which was released as part of Dipy - an open source Python package for computational neuroanatomy.
Quantum Information and Computing Group, HRI, Allahabad
(SRF, July 2016 - Aug 2016)
Guide: Prof. Ujjwal Sen, Associate ProfessorG, HRI, Allahabad
Indian Academy of Sciences (IAS) Summer Research Fellow. Studied Quantum Entanglement, measures of classical and quantum correlations and the application of Bell inequalities in Quantum Cryptography. In particular, analysed the E91 protocol (Arthur Ekert, 91) and use of Bell inequalities in device independent quantum cyrptography.
Computational Biology Group, Institute of Mathematical Sciences, Chennai
(Intern, Dec 2015 - Jan 2016)
Guide: Prof. Sitabhra Sinha, adjunct faculty of the National Institute of Advanced Studies (NIAS), Bangalore.
Simulated a Hodgkin Huxley inspired model for electrical signaling in bacterial bio-films using Python. Tested the ability of bacterial bio-films to behave as excitable media by extending the 1D model in the study (Prindle et al, 2015) to 2D and analysing the result of various initial conditions.