Rachel Topno 🕵
Rachel Topno
(she/her)

Data Scientist

About Me

Data Scientist with a strong foundation in Computational Science and 5+ years of experience in scientific programming, modeling, and high-performance data analysis. Passionate about bridging research innovation and industrial application in complex systems, simulation, and data intelligence

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Interests
  • Computational Biology
  • Computer Vision
  • Artificial Intelligence
  • Machine Learning
  • Stochastic Simulation
  • Mathematical Modelling
  • Healthcare
  • Complex Systems
Education
  • PhD Computational Biology

    University of Montpellier

  • Post Graduate Diploma in Applied Statistics

    Indira Gandhi National Open University, New Delhi, India

  • M.Sc Physics

    Department of Astrophysics and Astronomy, University of Delhi, India

  • B.Sc Physics

    St. Stephen's College, University of Delhi, India

Programming
Python
R
C/C++
MATLAB
Data Science
Advanced Numerical methods
Data Engineering
Statistical Analysis
Model Validation
Hypothesis Testing
Computer Vision
Scikit-Image & OpenCV
Segmentation
Object detection
Object Tracking
DevOps & Tools
CI/CD tools
Git, GitLab
Docker, Jupyter
environments
pyqt, flask
ML & DL
Genetic Algorithms
PyTorch, TensorFlow
CNNs, U-Net
Bioinformatics
RNA-Seq
Microarray Analysis
ChIP-Seq
Hobbies
Cycling
Badminton
Crochet
Knitting
Epoxy Resin
📚 My Research

I’m a research scientist. I blog about Computer Vision, Image Analysis, and Crochet.

As a doctoral student, I conducted cutting-edge research in the field of transcription dynamics, applying my skills in Python, R, and MATLAB to analyze large and complex datasets. I have a master’s degree in physics and a postgraduate diploma in statistics, which give me a strong foundation in quantitative and computational methods. I have over six years of work experience in various research settings, including Institut de Génétique Moléculaire de Montpellier and Amity University, where I participated in multiple projects on topics such as gene regulation, transcriptional noise and cancer.

I am passionate about advancing our understanding of the molecular mechanisms and interactions that shape human health and disease, and I am eager to collaborate with other researchers and experts in this field. I value curiosity, innovation, and diversity, and I strive to contribute to the scientific community and society with my work.

Please reach out to collaborate 😃

Recent Publications
(2025). Cell heterogeneity contributes to the variable response of HIV-1 to latency reversing agents [under review].
(2023). BurstDECONV: a signal deconvolution method to uncover mechanisms of transcriptional bursting in live cells. Nucleic Acids Research.
(2021). Stochastic pausing at latent HIV-1 promoters generates transcriptional bursting. Nature Communications.
(2021). Integrated bioinformatic analysis identifies UBE2Q1 as a potential prognostic marker for high grade serous ovarian cancer. BMC cancer.
(2021). Integrative genome wide analysis of protein tyrosine phosphatases identifies CDC25C as prognostic and predictive marker for chemoresistance in breast cancer. Cancer Biomarkers: Section A of Disease Markers.