Dr AselSagingalieva
Quantum machine learning scientist
Founder and CEO of EigenOrbit
I solve enterprise problems with quantum technologies, first at Terra Quantum and since October 2026 at EigenOrbit.
EigenOrbit
The independent decision and orchestration layer for quantum and hybrid computing.
eigenorbit.comEigenOrbit tells enterprises which problems are worth solving on quantum hardware, on which machine, and always against a classical baseline.
In the news
All newsEigenOrbit study compares 12 quantum computing backends
eigenkit: a provider‑neutral quantum computing library
Hands‑on quantum machine learning workshop
eigenkit 1.0 released under the Apache 2.0 licence
Terra Quantum
From junior researcher to Head of Quantum ML Engineering in four years.
Products I built there: QAI Hub, a no‑code quantum ML platform, and TQml, a quantum ML library.
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I architected QAI Hub, the no‑code quantum ML platform in TQ42 Studio, led R&D of the TQml library and led delivery of more than 20 paid enterprise projects in energy, healthcare, manufacturing, materials and finance, each with KPIs agreed with the client.
Results include record 99.21% accuracy on MNIST with 8× fewer parameters and hybrid physics‑informed networks with 21% higher accuracy in 3D fluid simulation.
Six products
eigenkit
Open‑source Python library, one codebase across 8 simulators and 4 hardware routes: IBM, IQM, Amazon Braket and Quandela
pip install eigenkit, Apache 2.0
Benchmarks
One workload measured across 8 simulators and priced across 14 QPUs, every number with its source
Academy
Video courses on quantum computing, from a single qubit to your first running algorithm, with quizzes and a certificate
Research
Hybrid quantum‑classical neural networks applied to industry and medicine.
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My work covers drug response prediction, liver imaging, solar forecasting, steelmaking, turbofan engines, fluid dynamics, laser processing and quantum key distribution. I have given more than 20 invited and contributed talks since 2020, including the ML & Quantum Physics Workshop in Obergurgl and the University of St. Gallen with the ACM Chapter HSG.
I referee for Physical Review Letters, Physical Review A, Physical Review Applied and Machine Learning: Science and Technology. h‑index 12.
- 360Quantum machine learning for image classification
Machine Learning: Science and Technology, 2024 - 154Hybrid quantum neural network for drug response prediction
Cancers, 2023 - 73Hybrid quantum physics‑informed neural networks for fluid dynamics
Machine Learning: Science and Technology, 2024 - 66Benchmarking simulated and physical quantum processing units
Advanced Quantum Technologies, 2023, front cover
Patents and recognition
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MIPT
Three degrees in applied mathematics and physics, admitted without entrance exams.
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Department of General and Applied Physics at the Moscow Institute of Physics and Technology. I was admitted as a national physics olympiad medalist and from 2019 to 2022 taught physics and mathematics at the Phystech International Olympiad School and university courses in informatics and Python.