I am a Postdoctoral Research Scientist in the group of Prof. Dame Molly Stevens at the University of Oxford, working on deep learning approaches for analytical chemistry, label-free biophotonics and drug discovery.
Interests
- Deep learning
- Label-free biophotonics
- Analytical chemistry
- Chemometrics
- Drug discovery
- AI for science
Education
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PhD in AI & ML
Imperial College London, UK
Oct 2021 - Oct 2025
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MMath in Mathematics
University of Southampton, UK
Sep 2017 - Jul 2021
Recent highlights
2025:
- 🎉 Postdoctoral Research Scientist at University of Oxford
- ✅ Submitted my PhD thesis
- 📝 New preprint is out
- Attended ICML'25
- 🎤 Oral presentation at AI4X
- RamanSPy #7 most-read article in Analytical Chemistry in the past year
- 🪧 Poster presentation at CAI4H'25
- Attended AISTATS'25
- 🪧 Poster presentation at the LMRL workshop at ICLR'25
Oct:
September:
Title: Label-free biochemical imaging and timepoint analysis of neural organoids via deep learning-enhanced Raman microspectroscopy
July:
📍Vancouver, Canada
Title: Hyperspectral Unmixing for Raman Spectroscopy via Physics-Constrained Autoencoders
📍Singapore
June:
May:
📍York, UK
📍Phuket, Thailand
April:
Title: Label-free biochemical imaging and timepoint analysis of neural organoids via deep learning-enhanced Raman microspectroscopy
📍Singapore
2024:
- 🪧 Poster presentation at RamanFest2024 - won the Best PhD Poster award
- 📄 Paper published in PNAS
- 🎤 Oral presentation at BioMedEng24
- 🪧 Poster presentation at BioMedEng24
- 🎤 Oral presentation at the AI4Science workshop at ICML'24
- 🪧 Poster presentation at the AI4Science workshop at ICML'24
- 🪧 Poster presentation at the ML4LMS workshop at ICML'24
- 🪧 Poster presentation at the ML4LMS workshop at ICML'24
- 🪧 Poster presentation at MoML'24
- 🏫 Participated in the ML for Drug Discovery Summer School
- 📄 Paper published in Analytical Chemistry
- 🪧 Poster presentation at CAI4H'24
- 🏛️ Joined University of Oxford as Academic Visitor
- 📝 New preprint is out
November:
Title: Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders
📍Paris, France
October:
Title: Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders
September:
Title: Hyperspectral Unmixing for Raman Spectroscopy via Physics-Constrained Autoencoders
📍London, UK
Title: RamanSPy: An Open-Source Python Package for Raman Spectroscopy Data Analysis
📍London, UK
July:
Title: Hyperspectral Unmixing for Raman Spectroscopy via Physics-Constrained Autoencoders
📍Vienna, Austria
Title: RamanSPy: Augmenting Raman spectroscopy data analysis with AI
📍Vienna, Austria
Title: Hyperspectral Unmixing for Raman Spectroscopy via Physics-Constrained Autoencoders
📍Vienna, Austria
Title: RamanSPy: Augmenting Raman spectroscopy data analysis with AI
📍Vienna, Austria
June:
Title: Accelerating Molecular Graph Neural Networks via Knowledge Distillation
📍Montreal, Canada
📍Montreal, Canada
May:
Title: RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis
Title: Hyperspectral Unmixing for Raman Spectroscopy via Physics-Constrained Autoencoders
📍Edinburgh, UK
March:
📍Oxford, UK
Title: Hyperspectral Unmixing for Raman Spectroscopy via Physics-Constrained Autoencoders
2023:
- 🪧 Poster presentation at NeurIPS'23
- 🎤 Oral presentation at LoG'23
- 📄 Paper accepted to NeurIPS'23
- 🪧 Poster presentation at the SynS&ML workshop at ICML'23
- 📝 New preprint is out
- 💻 New Python package called RamanSPy
- 📝 New preprint is out
- 🪧 Poster presentation at CAI4H'23
December:
Title: Accelerating Molecular Graph Neural Networks via Knowledge Distillation
📍New Orleans, USA
November:
Title: Accelerating Molecular Graph Neural Networks via Knowledge Distillation
📍virtual
September:
Title: Accelerating Molecular Graph Neural Networks via Knowledge Distillation
July:
Title: Accelerating Molecular Graph Neural Networks via Knowledge Distillation
📍Hawaii, USA
Title: RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis
June:
Scope: Raman spectroscopy data analytics
Title: Accelerating Molecular Graph Neural Networks via Knowledge Distillation
May:
Title: Cell phenotyping via hyperspectral unmixing autoencoders
📍York, UK
Selected publications
 | Label-free biochemical imaging and timepoint analysis of neural organoids via deep learning-enhanced Raman microspectroscopy Dimitar Georgiev, Ruoxiao Xie, Daniel Reumann, Xiaoyu Zhao, Álvaro Fernández-Galiana, Mauricio Barahona, Molly M. Stevens. (under review). Preprint available on bioRxiv: 10.1101/2025.09.29.679057, 2025.  This work has also been presented or is scheduled to be presented at:
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 | Hyperspectral unmixing for Raman spectroscopy via physics-constrained autoencoders Dimitar Georgiev, Álvaro Fernández-Galiana, Simon Vilms Pedersen, Georgios Papadopoulos, Ruoxiao Xie, Molly M. Stevens, Mauricio Barahona Proceedings of the National Academy of Sciences of the United States of America (PNAS), 2024   Code This work has also been presented at:
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 | RamanSPy: An open-source Python package for integrative Raman spectroscopy data analysis Dimitar Georgiev, Simon Vilms Pedersen, Ruoxiao Xie, Álvaro Fernández-Galiana, Molly M. Stevens, Mauricio Barahona Analytical Chemistry, 2024   Code Star  This work has also been presented at:
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 | Accelerating Molecular Graph Neural Networks via Knowledge Distillation Filip Ekström Kelvinius*, Dimitar Georgiev*, Artur Petrov Toshev*, Johannes Gasteiger *Equal contribution. Order was determined by rolling a dice. Conference on Neural Information Processing Systems (NeurIPS), 2023 CodeThis work has also been presented at:
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My complete, up-to-date publication record is available on Google Scholar.