Syed Mohaiminul Hoque

Who Am I

I am a curious explorer in the field of Natural Language Processing and Quantum Computing. Over the past two years, my research works spanned over text generation and classification using pretrained transformer models. I am currently a Research Intern at Center For Computational and Data Sciences Lab (https://ccds.ai/people/interns-part-time-research-assistant/). My interest is to work in several topics like Multimodal Machine Learning , Quantum Unconstrained Binary Optimization (algorithms for combinatorial optimization) and Quantum Machine Learning. Currently, I am working on Quantum Transformer Models and Quantum Machine Learning.

Trainings:

I have several learning and hands-on-experience in Quantum Computing as a beginner.

  • Graduate of The Coding School's a year long (2 semesters) initiative titled An Introduction to Quantum Computing (https://www.qubitbyqubit.org/programs)

  • Womanium Quantum + AI Scholar 2024

  • QWorld's QClass Program 2024/2025 (https://qworld.net/qclass24-25/)

  • IBM Qiskit Global Summer School 2024 : Path to Utility

  • QCenter-Pasqal Quantum Computer Program 2024

Volunteering:

Quantum High School Organization - Advisor

  • Assisting in co ordination of various workshops related to quantum computing

  • Content Management tasks using qiskit, cirq and pennylane

Quantum Africa - Contributor

  • Contributor to research papers related to quantum machine learning

Hackathon Participations

  • Qiskit Fall Fest 2024 (DoraHacks):

    • Quantum Circuit Construction: Created and manipulated Bell states, applied quantum operators (XX, ZI, ZZ), and optimized circuit performance using Qiskit’s tools.

    • Quantum States and Circuits: Developed and visualized entangled states like Singlet Bell and W-states, and executed circuits using Sampler.run.

    • VQE and Qiskit 1.0: Built parameterized ansatz circuits for variational algorithms and utilized QiskitRuntimeService for both local and remote job execution.

    • View the project here

Tools I use:

  • Statistical Analysis and Data visualization: Numpy, Pandas, Scikit-Learn, Pytorch, Tensorflow, Seaborn, Matplotlib

  • for LLMs: SentenceTransformers, Gensim, Hugging Face Transformers, FastText

  • for QC: Qiskit, Pennylane, Cirq, D-Wave Ocean SDK

Publications

BaTEClaCor: A Novel Dataset for Bangla Text Error Classification and Correction

Nabilah Oshin, Syed Hoque, Md Fahim, Amin Ahsan Ali, M Ashraful Amin, Akmmahbubur Rahman

EMNLP BLP Workshop 2023