Tom Fearn

Tom Fearn

University College London

H-index: 48

Europe-United Kingdom

About Tom Fearn

Tom Fearn, With an exceptional h-index of 48 and a recent h-index of 24 (since 2020), a distinguished researcher at University College London, specializes in the field of Applied Statistics, Chemometrics.

His recent articles reflect a diverse array of research interests and contributions to the field:

VALE: Ian Michael, 13 September 1957–24 April 2023

Testing differences in predictive ability: A tutorial

Farinograph characteristics of wheat flour predicted by near infrared spectroscopy with an ensemble modelling method

Optimisation of the predictive ability of NIR models to estimate nutritional parameters in elephant grass through LOCAL algorithms

Size and shape attributes of packaging remnants in former food products

NIR2023: Good vibrations, smooth contours

Comparing uncertainties—Are they really different?

Photodegradation of iron gall ink affected by oxygen, humidity and visible radiation

Tom Fearn Information

University

Position

Professor of Applied Statistics

Citations(all)

15198

Citations(since 2020)

3627

Cited By

13280

hIndex(all)

48

hIndex(since 2020)

24

i10Index(all)

129

i10Index(since 2020)

57

Email

University Profile Page

University College London

Google Scholar

View Google Scholar Profile

Tom Fearn Skills & Research Interests

Applied Statistics

Chemometrics

Top articles of Tom Fearn

Title

Journal

Author(s)

Publication Date

VALE: Ian Michael, 13 September 1957–24 April 2023

NIR news

Tom Fearn

Graeme Batten

Gerry Downey

Tony Davies

2024/2/5

Testing differences in predictive ability: A tutorial

Tom Fearn

2024

Farinograph characteristics of wheat flour predicted by near infrared spectroscopy with an ensemble modelling method

Journal of Food Engineering

Chenhao Cui

Nicola Caporaso

Jiawei Chen

Tom Fearn

2023/12/1

Optimisation of the predictive ability of NIR models to estimate nutritional parameters in elephant grass through LOCAL algorithms

Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy

Víctor M Fernández-Cabanás

Dolores C Pérez-Marín

Tom Fearn

Joadil Gonçalves de Abreu

2023/1/15

Size and shape attributes of packaging remnants in former food products

P Lin

S Mazzoleni

T Fearn

M Ottoboni

M Tretola

...

2023

NIR2023: Good vibrations, smooth contours

NIR news

Tom Fearn

2023/12

Comparing uncertainties—Are they really different?

Accreditation and Quality Assurance

Peter D Rostron

Tom Fearn

Michael H Ramsey

2022/6

Photodegradation of iron gall ink affected by oxygen, humidity and visible radiation

Dyes and Pigments

Yun Liu

Tom Fearn

Matija Strlič

2022/2/1

Insight Gained from Using Machine Learning Techniques to Predict the Discharge Capacities of Doped Spinel Cathode Materials for Lithium‐Ion Batteries Applications

Energy Technology

Guanyu Wang

Tom Fearn

Tengyao Wang

Kwang-Leong Choy

2021/5

First SensorFINT workshop held in Porto

NIR news

António Silva Ferreira

Tom Fearn

Maria Lopes

Lola Pérez-Marín

2021/12

Determination of ingredients in packaged pharmaceutical tablets by energy dispersive X‐ray diffraction and maximum likelihood principal component analysis multivariate curve …

Journal of Chemometrics

Peter S Kenny

Chiaki Crews

Tom Fearn

Robert D Speller

2021/4

Factorial experimentation on photodegradation of historical paper by polychromatic visible radiation

Heritage Science

Yun Liu

Tom Fearn

Matija Strlič

2021/12

Announcement from ICNIRS for the International Conference of NIRS 2021, Beijing, China

Mui Saranwong

Tom Fearn

2021/3

Spectral sensitivity of the discoloration of Historical rag paper

Talanta Open

Yun Liu

Tom Fearn

Matija Strlič

2021/12/1

Correction to: Confidence intervals for robust estimates of measurement uncertainty

Accreditation and Quality Assurance

Peter D Rostron

Tom Fearn

Michael H Ramsey

2021/2

Machine-learning approach for predicting the discharging capacities of doped lithium nickel–cobalt–manganese cathode materials in Li-ion batteries

ACS central science

Guanyu Wang

Tom Fearn

Tengyao Wang

Kwang-Leong Choy

2021/8/20

Probabilistic classification models for the in situ authentication of iberian pig carcasses using near infrared spectroscopy

Talanta

Dolores Pérez-Marín

Tom Fearn

Cecilia Riccioli

Emiliano De Pedro

Ana Garrido

2021/1/15

Quantitative NIR spectroscopy for determination of degree of polymerisation of historical paper

Chemometrics and Intelligent Laboratory Systems

Yun Liu

Tom Fearn

Matija Strlič

2021/7/15

Sample selection, calibration and validation of models developed from a large dataset of near infrared spectra of tree leaves

Journal of Near Infrared Spectroscopy

Jessie Au

Kara N Youngentob

William J Foley

Ben D Moore

Tom Fearn

2020/8/1

Confidence intervals for robust estimates of measurement uncertainty

Accreditation and Quality Assurance

Peter D Rostron

Tom Fearn

Michael H Ramsey

2020/4

See List of Professors in Tom Fearn University(University College London)