Programming Languages: Python, MATLAB, Fortran
Emilie Ismailova
Interdisciplinary Researcher In Machine Learning, Signal Processing, And Computational Modeling
Stuttgart
Summary
Dynamic research professional with over five years of experience in interdisciplinary research combining engineering, medicine, and data science, specializing in machine learning, computational modeling, and advanced data analysis. Adept at applying critical thinking and robust project planning skills, demonstrated through successful development and validation of analytical frameworks. Proven ability to effectively collaborate on multidisciplinary projects, translating complex data into actionable predictive models.
Overview
7
7
years of professional experience
3
3
Certifications
2
2
Languages
Work History
Research Assistant
University of Stuttgart
01.2020 - Current
- Integrated multidisciplinary expertise in engineering, computational mechanics, and machine learning to develop innovative clinical methods and applications.
- Designed and validated AI-driven diagnostic frameworks utilizing advanced signal processing techniques for diagnostic decision-making.
- Analyzed biomedical data, formulated and tested hypotheses to uncover the underlying mechanisms of physiological processes.
- Collaborated with medical doctors in Europe and participated in experimental studies involving electromyography.
- Extended the developed AI methodologies to diverse clinical datasets, establishing international collaborations with research partners from the USA and Australia.
- Significantly contributed to the preparation and successful submission of a DFG-funded research proposal.
Visiting Research Fellow
Neuroscience Research Australia
09.2024 - 12.2024
- Developed and tested hypotheses linking multi-channel sleep study measurements to the anatomical mechanisms underlying the effectiveness of a treatment device.
- Extracted, processed, and analyzed sleep study data to create robust feature sets for machine learning applications.
- Evaluated and benchmarked multiple data processing and machine learning pipelines, identifying optimal analytical methods.
- Formulated practical recommendations to improve future data collection and measurement quality for enhanced predictive accuracy.
Academic Assistant
University of Stuttgart
01.2019 - 09.2019
- Designed an advanced fracture response model within a multi-scale framework for polymer materials, incorporating statistical mechanics approaches.
- Analyzed mathematical limitations of multi-scale models for polymers when integrated within the phase-field fracture framework.
- Developed a robust mathematical formulation for simulating fracture in nearly incompressible materials, incorporating a specialized degradation function that ensures numerical stability.
- Derived and implemented finite elements for fracture in rubbery materials.
- Developed custom computational software routines for material behavior modeling, executed fracture simulations, and performed curve-fitting analyses to validate and calibrate model predictions against experimental data.
Academic Assistant
University of Stuttgart
06.2018 - 01.2019
- Formulated computational models of protein networks derived from segmented imaging data.
- Performed image segmentation to extract protein network structures from 3D microscopy images.
- Executed finite element simulations to analyze the mechanical behavior of protein networks.
- Analyzed simulation results, linking structural characteristics of protein networks.
Education
Dr.-Ing. (PhD Equivalent) Candidate - Interdisciplinary Engineering
University of Stuttgart
Stuttgart 04.2001 -
Master of Science - Computational Mechanics
University of Stuttgart
Stuttgart 04.2001 -
Bachelor of Science - Civil Engineering
Tashkent Institute of Civil Engineering
Tashkent 04.2001 -
Skills
Machine Learning and Predictive Analytics
Statistical and Quantitative Analysis
Numerical Modeling and Simulation
Interdisciplinary Teamwork
Project Management and Planning
Technical Communication
Affiliations
Virtual Physiological Human Institute Member
Software
Machine Learning Libraries: scikit-learn, TensorFlow, PyTorch, XGBoost
Data Manipulation & Visualization: Pandas, NumPy, Matplotlib, Seaborn
Simulation & Modelling Software: FEAP, LS-DYNA
Image Processing & Segmentation: Amira
Certification
Knowledge-Driven Machine Learning and Its Applications, 1st International SimTech Summer School
Timeline
Visiting Research Fellow
Neuroscience Research Australia
09.2024 - 12.2024
Knowledge-Driven Machine Learning and Its Applications, 1st International SimTech Summer School
07-2022
Software Carpentry Workshop: Programming in Python
04-2021
Academic Writing for Science and Engineering for PhD Students
11-2020
Research Assistant
University of Stuttgart
01.2020 - Current
Academic Assistant
University of Stuttgart
01.2019 - 09.2019
Academic Assistant
University of Stuttgart
06.2018 - 01.2019
Dr.-Ing. (PhD Equivalent) Candidate - Interdisciplinary Engineering
University of Stuttgart
04.2001 -
Master of Science - Computational Mechanics
University of Stuttgart
04.2001 -
Bachelor of Science - Civil Engineering
Tashkent Institute of Civil Engineering
04.2001 -
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