Hi, my name is

Saiyam Sakhuja.

I superpose quantum and computing.

I'm a Quantum Application Engineer specializing in quantum algorithms, machine learning, and their applications in weather forecasting and brain-wave analysis.

View My Work Get In Touch

About Me

Hello! I'm Saiyam, a Quantum Application Engineer with a passion for developing quantum algorithms that tackle real-world challenges in weather forecasting, image processing, and neuroscience.

With a strong foundation in physics from my M.Sc. at NIT Tiruchirappalli and B.Sc. from University of Delhi, I bridge the gap between theoretical quantum mechanics and practical quantum computing applications.

My work focuses on Quantum Machine Learning models, particularly QNNs, QLSTMs, and QGRUs, as well as quantum techniques for data representation and analysis. I'm particularly interested in how quantum computing can enhance AI models for time-series forecasting and signal processing.

Here are a few technologies I've been working with recently:

  • Qiskit
  • PennyLane
  • Cirq
  • PyTorch
  • Quantum Neural Networks
  • QLSTMs/QGRUs
  • Digital-Analog Quantum Computing
  • Quantum Fourier Transform
Saiyam Sakhuja

Where I've Worked

Sept. 2024 - Present

Quantum Application Engineer

Centre for Development of Advanced Computing, Noida

  • Developed quantum algorithms for weather forecasting using QNNs, QLSTMs, and QGRUs
  • Explored quantum techniques for image representation to enhance feature extraction
  • Developed unitary and statevector simulator for FPGA-based acceleration

May 2024 - Aug. 2024

Research Intern

Naxon Labs, Uruguay

  • Researched Digital-Analog Quantum Computing (DAQC) for Quantum Fourier Transform on brain-wave data
  • Converted conventional quantum circuits into DAQC circuits to reduce circuit depth
  • Applied DAQC techniques to neuroscientific data analysis

March 2024 - Aug. 2024

Project Associate

Centre for Development of Advanced Computing, Delhi

  • Focused on Quantum Machine Learning (QML) for EEG data analysis
  • Applied Quantum Fourier Transform (QFT) and Quantum Haar Wavelet Transform (QHWT)
  • Developed quantum models to classify focused versus unfocused cognitive states with 80% accuracy

Dec. 2023 - Aug. 2024

Junior Quantum Data Analyst

The Quantum Insider (TQI), Canada

  • Managed a global database of news and research related to different quantum entities
  • Developed backend code to enable user-friendly data exploration

My Publications

Quantum-Assisted Machine Learning Models for Enhanced Weather Prediction

Saiyam Sakhuja, Abhishek Tiwari

Research on quantum machine learning approaches for weather prediction using advanced quantum neural networks.

View Publication

Benchmarking Quantum Image Representations Algorithms for Hybrid-Quantum applications

Saiyam Sakhuja, Abhishek Tiwari

Comprehensive benchmarking of quantum algorithms for image representation in hybrid quantum-classical applications.

View Publication

Quantum-Enhanced Secure Approval Voting Protocol

Saiyam Sakhuja, Dr. Balakrishnan S.

Novel quantum protocol for secure electronic voting systems with enhanced privacy and security guarantees.

View Publication

Lead-free Sb-modified potassium sodium niobate ceramics for enhanced energy harvesting

Saiyam Sakhuja, Dr. Annapureddy V.

Development of lead-free piezoelectric ceramics for ultrasonic inspection and energy harvesting applications.

View Publication

Education

M.Sc. - Physics

National Institute of Technology Tiruchirappalli

2021 - 2023

CGPA: 8.85/10.0 | Rank 3

Key courses: Quantum Information Theory, Quantum Algorithms, Quantum Mechanics, Solid State Physics, Atomic and Molecular Physics

B.Sc.(Hons.) - Physics

University of Delhi

2018 - 2021

CGPA: 8.14/10.0

Qualified Joint Entrance Test for Masters (IIT-JAM) Physics with All India Rank 544

Some Things I've Built

Quantum Neural Networks for Weather Forecasting

Nov. 2024 - Feb. 2025

Developed Quantum Gated Recurrent Units (QGRU) and Quantum Long Short-Term Memory (QLSTM) models for weather time series analysis. Achieved accuracy comparable to classical models, demonstrating quantum approaches' potential for forecasting.

  • PyTorch
  • Qiskit
  • Pennylane
  • QML

Quantum-Enhanced Water Potability Prediction

June 2024 - Aug. 2024

Developed a hybrid Quantum+AI model for water potability prediction, utilizing LightGBM, XGBoost, and Quantum PCA. Achieved 70.9% accuracy using Quantum PCA-enhanced LightGBM, highlighting quantum computing's role in environmental analysis.

  • Quantum PCA
  • QAOA
  • QSVM
  • LightGBM

Molecular Dynamics Simulation

Jan. 2022 - April 2022

Simulated particles arranged on a 2-D rectangular lattice in motion while interacting via Lennard-Jones Potential. Verified the Maxwell-Boltzmann Distribution curve and Conservation of Energy principles.

  • Python
  • NumPy
  • Matplotlib
  • Physics Simulation

Digital-Analog Quantum Computing for Brain Data

May 2024 - Aug. 2024

Explored Digital-Analog Quantum Computing for implementing Quantum Fourier Transform on brain-wave data, reducing circuit depth and improving analysis efficiency in neuroscientific applications.

  • DAQC
  • QFT
  • Qiskit
  • EEG Analysis

My Blogs

Sharing my thoughts and insights on quantum computing and its applications in solving real-world problems.

What's Next?

Get In Touch

I'm currently open to new opportunities in quantum computing research and application development. Whether you have a question or just want to say hi, I'll do my best to get back to you!

Say Hello