World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
59
Citations
72917
World Ranking
3310
National Ranking
198

Overview

Nello Cristianini is affiliated with the University of Bath in the United Kingdom, contributing to various fields including Agricultural and Biological Sciences, Computer Science, and Biochemistry, Genetics and Molecular Biology. Their research spans multiple subfields such as Food Science, Nutrition and Dietetics, Artificial Intelligence, Biotechnology, and Animal Science and Zoology.

The scientist's recent papers cover diverse topics related to food science and technology. Notable publications include:

  • Extraction of bioactive compounds from purple corn using emerging technologies: A review (2020) published in the Journal of Food Science
  • Mango and carrot mixed juice: a new matrix for the vehicle of probiotic lactobacilli (2020) published in the Journal of Food Science and Technology
  • High pressure-assisted enzymatic hydrolysis potentiates the production of quinoa protein hydrolysates with antioxidant and ACE-inhibitory activities (2024) published in Food Chemistry
  • Morphological, thermal and mechanical properties of polyamide and ethylene vinyl alcohol multilayer flexible packaging after high-pressure processing (2020) published in the Journal of Food Engineering
  • Non-thermal emerging technologies as alternatives to chemical additives to improve the quality of wheat flour for breadmaking: a review (2021) published in Critical Reviews in Food Science and Nutrition

Among frequent co-authors, collaborators include:

  • Ludmilla de Carvalho Oliveira
  • Luís Marangoni Júnior
  • Carlos Alberto Rodrigues Anjos
  • Serafim Bakalis
  • Zhaozhen Xu

Their work is often published in journals such as:

  • Innovative Food Science & Emerging Technologies
  • Journal of Food Processing and Preservation
  • LWT
  • arXiv (Cornell University)
  • Journal of Food Science

The research topics addressed in their publications cover areas including:

  • Microbial Inactivation Methods
  • Food composition and properties
  • Meat and Animal Product Quality
  • Topic Modeling
  • Proteins in Food Systems
  • Polysaccharides Composition and Applications
  • Microbial Metabolites in Food Biotechnology

This scientist's work integrates knowledge from multiple scientific domains and applies emerging technologies to food science and biotechnology challenges, with a focus on food quality, safety, and nutritional properties.

Best Publications

  • An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

    Nello Cristianini;John Shawe-Taylor

  • Kernel Methods for Pattern Analysis

    John Shawe-Taylor;Nello Cristianini

  • An Introduction to Support Vector Machines

    Nello Cristianini;John Shawe-Taylor

  • Support vector machine classification and validation of cancer tissue samples using microarray expression data

    Terrence S. Furey;Nello Cristianini;Nigel Duffy;David W. Bednarski

  • Knowledge-based analysis of microarray gene expression data by using support vector machines

    Michael P. S. Brown;William Noble Grundy;David Lin;Nello Cristianini

  • Learning the Kernel Matrix with Semidefinite Programming

    Gert R. G. Lanckriet;Nello Cristianini;Peter Bartlett;Laurent El Ghaoui

  • Large Margin DAGs for Multiclass Classification

    John C. Platt;Nello Cristianini;John Shawe-Taylor

  • Text classification using string kernels

    Huma Lodhi;Craig Saunders;John Shawe-Taylor;Nello Cristianini

  • CAFE: a computational tool for the study of gene family evolution

    Tijl De Bie;Nello Cristianini;Jeffery P. Demuth;Matthew W. Hahn

  • On Kernel-Target Alignment

    Nello Cristianini;John Shawe-Taylor;André Elisseeff;Jaz S. Kandola

  • Controlling the Sensitivity of Support Vector Machines

    K Veropoulos;Icg Campbell;N Cristianini

  • A statistical framework for genomic data fusion

    Gert R. G. Lanckriet;Tijl De Bie;Nello Cristianini;Michael I. Jordan

  • Support vector machines

    Alessia Mammone;Marco Turchi;Nello Cristianini

  • Query Learning with Large Margin Classifiers

    Colin Campbell;Nello Cristianini;Alex J. Smola

  • Tracking the flu pandemic by monitoring the social web

    Vasileios Lampos;Nello Cristianini

  • The Kernel-Adatron Algorithm: A Fast and Simple Learning Procedure for Support Vector Machines

    Thilo-Thomas Frieß;Nello Cristianini;Colin Campbell

  • Kernel-based data fusion and its application to protein function prediction in yeast.

    Gert R. G. Lanckriet;Minghua Deng;Nello Cristianini;Michael I. Jordan

  • Latent Semantic Kernels

    Nello Cristianini;John Shawe-Taylor;Huma Lodhi

  • Text Classification using String Kernels

    Huma Lodhi;John Shawe-Taylor;Nello Cristianini;Christopher J. C. H. Watkins

  • Flu detector: tracking epidemics on twitter

    Vasileios Lampos;Tijl De Bie;Nello Cristianini

  • Large Margin DAG's for Multiclass Classification

    John Platt;Nello Cristianini;John Shawe-Taylor

  • Advances in Kernel Methods - Support Vector Learning

    Nello Cristianini;J Shawe-Taylor

  • Kernel Methods for Pattern Analysis: Pattern analysis

    John Shawe-Taylor;Nello Cristianini

Frequent Co-Authors

John Shawe-Taylor
John Shawe-Taylor University College London
Tijl De Bie
Tijl De Bie Ghent University
Matthew W. Hahn
Matthew W. Hahn Indiana University
Elisa Ricci
Elisa Ricci Fondazione Bruno Kessler
Terrence S. Furey
Terrence S. Furey University of North Carolina at Chapel Hill
Michael I. Jordan
Michael I. Jordan University of California, Berkeley
Peter A. Flach
Peter A. Flach University of Bristol
Gert R. G. Lanckriet
Gert R. G. Lanckriet University of California, San Diego
David Haussler
David Haussler University of California, Santa Cruz
Jason E. Stajich
Jason E. Stajich University of California, Riverside

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Expanding your credentials beyond traditional Computer Science can open new doors in today’s competitive job market. Many students are now exploring flexible options with online degrees that cater to specific industries and rapidly evolving skill sets.

For those interested in data-centric roles, consider online data science programs that balance affordability and advanced analytics training. Those looking to enter the construction or project management field may opt for a online construction management program to gain industry-specific expertise.

If leadership or business management is your goal, cheapest mba online programs are a cost-effective way to develop executive skills. Looking for a fast track? Explore 1 year master programs for accelerated learning and quicker entry into the workforce.

With these flexible online pathways, you can customize your education to align with your career ambitions and gain the qualifications needed for emerging roles in technology, analytics, management, and beyond.

Best Scientists Citing Nello Cristianini

Trending Scientists