基本信息
views: 9
![](https://originalfileserver.aminer.cn/sys/aminer/icon/show-trajectory.png)
Bio
Dr Annalisa Occhipinti is an Associate Professor at Teesside University. She holds a PhD in Computer Science from the University of Cambridge, awarded in 2016.
She works at the intersection between Computer Science and Biology to develop machine learning and deep learning methodologies for cancer prediction. Her current research topics include mathematical and computational modelling of cancer, machine learning, survival analysis and statistical methods.
Dr Occhipinti has recently received several awards for her outstanding contributions in the field of machine learning, big data and cancer research, including an award by the University of Cambridge for her research contribution.
She has also experience in Big Data, Business Intelligence and machine learning applications for business. She is currently involved in several projects with industrial partners to apply machine learning techniques for gaining valuable operational insights from different data sources.
Research Interests
Papers共 20 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Nancy Alnassar,Jacek Hajto,Robin M H Rumney, Suraj Verma,Malgorzata Borczyk, Chandrika Saha,Janos Kanczler,Arthur M Butt,Annalisa Occhipinti, Joanna Pomeroy,Claudio Angione,Michal Korostynski,
Human molecular genetics (2024)
Suraj Verma, Giuseppe Magazzù, Noushin Eftekhari, Thai Lou, Alex Gilhespy,Annalisa Occhipinti,Claudio Angione
Cell reports methodspp.100817-100817, (2024)
2022 IEEE International Workshop on Metrology for Living Environment (MetroLivEn)pp.138-143, (2022)
eLife (2022)
Load More
Author Statistics
Co-Author
Co-Institution
D-Core
- 合作者
- 学生
- 导师
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn