Hi, my name is

Harshdeep Singh.

Quantum Computing Researcher.

I'm a researcher specializing in quantum algorithms and quantum machine learning. Currently, I'm focused on developing innovative solutions that bridge the gap between quantum computing and practical applications.

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About Me

Hello! My name is Harsh, and I enjoy exploring different areas within quantum computation and information. I am currently working as a Postdoctoral Researcher in the Department of Microtechnology and Nanoscience at Chalmers University of Technology, Sweden (December 2025 - Present). I previously served as a Project Assistant at Chalmers in October–November 2025.

I completed my Ph.D. at the Centre for Computational and Data Sciences, Indian Institute of Technology (IIT) Kharagpur (August 2021 - November 2025), where my research focused on variational quantum algorithms and their applications in chemical systems.

Prior to this, I completed my Master’s Degree in Physics from Jadavpur University (July 2019 - July 2021), conducting research on the theoretical study of the electrical and optical properties of Nickel-doped Molybdenum Disulfide (MoS₂). I also hold a Bachelor’s Degree in Physics from Jadavpur University (July 2016 - June 2019).

I also have considerable experience in quantum machine learning and tensor networks. Throughout my academic journey, I have cultivated a strong foundation in both theoretical and computational aspects of physics, preparing me to contribute to cutting-edge research in quantum technologies.

Harshdeep Singh

Research & Publications

Journal Publications

  • Benchmarking of different optimizers in the variational quantum algorithms for applications in quantum chemistry

    H. Singh, S. Majumder, and S. Mishra

    The Journal of Chemical Physics, vol. 159, no. 4, Jul. 2023

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  • Hückel molecular orbital theory on a quantum computer: A scalable system-agnostic variational implementation with compact encoding

    H. Singh, S. Majumder, S. Mishra

    The Journal of Chemical Physics, vol. 160, no. 19, May 2024

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  • SHARC-VQE: Simplified Hamiltonian approach with refinement and correction enabled variational quantum eigensolver for molecular simulation

    H. Singh, S. Majumder, and S. Mishra

    The Journal of Chemical Physics, vol. 162, no. 11, Mar. 2025

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  • Blockwise Optimization for Projective Variational Quantum Dynamics (BLOP-VQD): Algorithm and Implementation for Lattice Systems

    H. Singh, S. Majumder, and S. Mishra

    The Journal of Chemical Physics, vol. 163, no. 12, Sep. 2025

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  • Quantum Computing for Molecular Systems: Part I: Quantum Circuit and Measurement

    H. Singh, S. Majumder, and S. Mishra

    Resonance Journal of Science Education, Volume 31, Issue 5, pp 685-699, May 2026

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  • Quantum Computing for Molecular Systems: Part II Quantum Encoding

    H. Singh, S. Majumder, and S. Mishra

    Resonance Journal of Science Education, Volume 31, Issue 6, pp 885-899, May 2026

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  • Quantum Computing for Molecular Systems: Part III: Quantum Algorithms

    H. Singh, S. Majumder, and S. Mishra

    Resonance Journal of Science Education, Volume 31, Issue 8, pp 1185-1202, May 2026

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Conference Papers

  • On the Study of Partial Qubit Hamiltonian for Efficient Molecular Simulation Using Variational Quantum Eigensolvers

    H. Singh, S. Mishra and S. Majumder

    2023 International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security (iQ-CCHESS), Kottayam, India, 2023, pp. 1–6

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  • A Survey of Classical and Quantum Sequence Models

    I.-C. Chen, H. Singh, V. L. Anukruti, B. Quanz and K. Yogaraj

    2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS), Bengaluru, India, 2024, pp. 1006–1011

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Preprints & Conference Proceedings

  • Comparing and Learning Figures of Merit for Quantum Circuit Compilation

    H. Singh, M. Richter, M. Granath, and A. Frisk Kockum

    arXiv:2607.03275v2, Jul. 03, 2026

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  • Extracting Information from Partial Hamiltonian of Simple Molecules for Designing Efficient Variational Quantum Eigensolvers

    H. Singh, S. Mishra, and S. Majumder

    Optica Quantum 2.0 Conference and Exhibition, Technical Digest Series (Optica Publishing Group, 2023), paper QTu3A.18

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  • Analytic Quantum Gradient Descent in Quantum Chemistry Simulations

    H. Singh

    Opg.optica.org, Optica Publishing Group, 13 June 2022

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Conference Presentations

  • QCOWPOST: A Quantum Compiler Based on Weighted Probability of Successful Trials

    IEEE Quantum Week 2026, Toronto, Canada

    24-28 September 2026

  • Comparing and learning figures of merit for quantum circuit compilation

    Quantum Science Generation (QSG), University of Trento, Italy

    4-8 May 2026

  • SHARC-VQE: Simplified Hamiltonian Approach with Refinement and Correction Enabled Variational Quantum Eigensolver for Molecular Simulation

    Quantum Simulation (QSim) Conference, University of Rhodes Island, US

    12-16 September 2024

  • Hückel molecular orbital theory on a quantum computer: A scalable system-agnostic variational implementation with compact encoding

    Quantum Australia, Sydney, Australia

    20-22 February 2024

  • Hybrid Classical-Quantum Algorithms for Applications in Quantum Chemistry

    Theoretical Chemistry Symposium (TCS) 2023, IIT Madras, India

    07-10 December 2023

    ACS Best Poster Award

  • On The Study Of Partial Qubit Hamiltonian For Efficient Molecular Simulation Using Variational Quantum Eigensolvers

    IEEE International Conference on Quantum Technologies, Communications, Computing, Hardware and Embedded Systems Security (iQ-CCHESS'23), IIIT Kottayam, Kerala, India

    15-16 September 2023

  • Partial Hamiltonian Analysis for Efficient Variational Quantum Eigensolvers

    International Conference on Quantum Computing and Communications (QCC2023), Punjab, India

    9-11 February 2023

  • Tensor Networks in Quantum-Inspired and Quantum Machine Learning

    International Conference on Quantum Computing and Communications (QCC2023), Punjab, India

    9-11 February 2023

  • Benchmarking of Different Optimizers in the Variational Quantum Algorithms for Applications in Quantum Chemistry

    AIP Congress 2022 (COMMAD), Adelaide, Australia

    11-16 December 2022

  • Tensor Networks assisted Quantum Computing for Applications in Machine Learning and Quantum Chemistry

    Second International Conference on AI and ML Systems, Bangalore, India

    12-15 October 2022

  • Variational Quantum Algorithms: An introduction and applications to quantum chemistry using Python

    SciPy India Conference, Bombay, India

    21-22 January 2022

  • Introduction to Quantum Computation with Qiskit

    PyCon Indonesia

    4-5 December 2021

Projects & Experience

Quantum Machine Learning for Large Datasets

QIntern Program, Imperial College London, focused on developing quantum ML approaches for large-scale datasets (July-August, 2023).

Qiskit Python Machine Learning

Hybrid Algorithm to Explore Properties of GPT in Quantum Transformer Models

Qiskit Advocate Mentorship Program (QAMP) project exploring properties of GPT in quantum transformer models (April-July, 2023).

Qiskit Python NLP

Tensor Networks for quantum-inspired and quantum machine learning

Research at Tata Consultancy Services (TCS) on tensor networks for quantum-inspired and quantum machine learning (February-April, 2022).

Tensor Networks Python Research

Random Number Generator using a Variational Quantum Circuit

First prize winning project at Qiskit Fall Fest Hackathon, Ahmadabad University Campaign (October 2021).

Qiskit Quantum Circuits Python

Get In Touch

Email

harshdeep.singh@chalmers.se

GitHub

github.com/harshdeeps036

LinkedIn

linkedin.com/in/harshdeepsingh3/

Location

Gothenburg, Sweden