World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
8807
World Ranking
9598
National Ranking
602

Overview

Max A. Little is affiliated with the University of Birmingham in the United Kingdom. Their research spans a multidisciplinary range combining computer science and medicine, with a particular focus on artificial intelligence, signal processing, biomedical engineering, neurology, and cognitive neuroscience.

Key topics in their work include:

  • Voice and Speech Disorders
  • Parkinson's Disease Mechanisms and Treatments
  • Balance, Gait, and Falls Prevention
  • Neurological disorders and treatments
  • Music and Audio Processing
  • Wireless Body Area Networks
  • Cerebral Palsy and Movement Disorders

Among the recent papers authored or coauthored by Max A. Little are:

  • Remote smartphone monitoring of Parkinson's disease and individual response to therapy, 2021, Nature Biotechnology
  • Real-Life Gait Performance as a Digital Biomarker for Motor Fluctuations: The Parkinson@Home Validation Study, 2020, Journal of Medical Internet Research
  • Causal GraphSAGE: A robust graph method for classification based on causal sampling, 2022, Pattern Recognition
  • Deep Phenotyping of Parkinson's Disease, 2020, Journal of Parkinson s Disease
  • Remote Assessment of Parkinson's Disease Symptom Severity Using the Simulated Cellular Mobile Telephone Network, 2021, IEEE Access

The scientist frequently collaborates with several coauthors, including:

  • Yordan P. Raykov
  • Bastiaan R. Bloem
  • Luc J. W. Evers
  • Jamie Adams
  • Ruth B. Schneider

Max A. Little's publications appear repeatedly in venues such as:

  • arXiv (Cornell University)
  • Journal of Medical Internet Research
  • Journal of Parkinson s Disease
  • Sensors
  • bioRxiv (Cold Spring Harbor Laboratory)

Their body of work includes 31 publications classified under computer science and 20 under medicine. The researcher has made significant contributions to subfields including artificial intelligence with 15 publications, signal processing with 10, biomedical engineering and neurology each with 8, and cognitive neuroscience with 7.

Best Publications

  • Suitability of Dysphonia Measurements for Telemonitoring of Parkinson's Disease

    M.A. Little;P.E. McSharry;E.J. Hunter;J. Spielman

  • Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection

    Max A. Little;Patrick E. McSharry;Stephen J. Roberts;Declan A. E. Costello

  • Accurate Telemonitoring of Parkinson's Disease Progression by Noninvasive Speech Tests

    A. Tsanas;M.A. Little;P.E. McSharry;L.O. Ramig

  • Novel Speech Signal Processing Algorithms for High-Accuracy Classification of Parkinson's Disease

    A. Tsanas;M. A. Little;P. E. McSharry;J. Spielman

  • Technology in Parkinson's disease: Challenges and opportunities.

    Alberto J. Espay;Paolo Bonato;Fatta B. Nahab;Walter Maetzler

  • Genome-wide association analyses of sleep disturbance traits identify new loci and highlight shared genetics with neuropsychiatric and metabolic traits

    Jacqueline M Lane;Jingjing Liang;Irma Vlasac;Irma Vlasac;Simon G Anderson;Simon G Anderson

  • Highly comparative time-series analysis: the empirical structure of time series and their methods

    Ben D. Fulcher;Max A. Little;Nick S. Jones;Nick S. Jones

  • Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: The Mobile Parkinson Disease Score

    Andong Zhan;Srihari Mohan;Christopher Tarolli;Ruth B. Schneider

  • Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity

    Athanasios Tsanas;Max A. Little;Patrick E. McSharry;Lorraine O. Ramig

  • 2010 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING

    Thanasis Tsanas;Max A. Little;Patrick E. McSharry;Lorraine O. Ramig

  • Objective Automatic Assessment of Rehabilitative Speech Treatment in Parkinson's Disease

    Athanasios Tsanas;Max A. Little;Cynthia Fox;Lorraine O. Ramig

  • Machine learning for large-scale wearable sensor data in Parkinson's disease: Concepts, promises, pitfalls, and futures

    Ken J. Kubota;Jason A. Chen;Max A. Little

  • What to do when K-means clustering fails: A simple yet principled alternative algorithm

    Yordan P. Raykov;Alexis Boukouvalas;Fahd Baig;Max A. Little;Max A. Little

  • Freezing of gait and fall detection in Parkinson’s disease using wearable sensors: a systematic review

    Ana Lígia Silva de Lima;Ana Lígia Silva de Lima;Luc J. W. Evers;Tim Hahn;Lauren Bataille

  • Feasibility of large-scale deployment of multiple wearable sensors in Parkinson’s disease

    Ana Lígia Silva De Lima;Ana Lígia Silva De Lima;Tim Hahn;Luc J.W. Evers;Nienke M. De Vries

  • Accurate telemonitoring of Parkinson’s disease progression by non-invasive speech tests

    Athanasios Tsanas;Max A. Little;Patrick E. McSharry;Lorraine O. Ramig

  • Generalized methods and solvers for noise removal from piecewise constant signals. I. Background theory

    Max A. Little;Nick S. Jones;Nick S. Jones

  • Using and understanding cross-validation strategies. Perspectives on Saeb et al.

    Max A Little;Gael Varoquaux;Sohrab Saeb;Luca Lonini

  • Suitability of dysphonia measurements for telemonitoring of Parkinson’s disease

    Max A. Little;Patrick E. McSharry;Eric J. Hunter;Jennifer Spielman

  • Predicting room occupancy with a single passive infrared (PIR) sensor through behavior extraction

    Yordan P. Raykov;Emre Ozer;Ganesh Dasika;Alexis Boukouvalas

  • Nonlinear, Biophysically-Informed Speech Pathology Detection

    M. Little;P. McSharry;I. Moroz;S. Roberts

  • Remote smartphone monitoring of Parkinson's disease and individual response to therapy.

    Larsson Omberg;Elias Chaibub Neto;Thanneer M Perumal;Abhishek Pratap;Abhishek Pratap

  • Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder Detection

    Max A. Little;Patrick E. McSharry;Stephen A. Roberts;Declan A. E. Costello

Frequent Co-Authors

Patrick E. McSharry
Patrick E. McSharry Carnegie Mellon University
Susan Redline
Susan Redline Brigham and Women's Hospital
Shaun Purcell
Shaun Purcell Harvard Medical School
Simon D. Kyle
Simon D. Kyle University of Oxford
Debbie A. Lawlor
Debbie A. Lawlor University of Bristol
Jesper Jensen
Jesper Jensen Aalborg University
Andrew R. Wood
Andrew R. Wood University of Exeter
Richard Emsley
Richard Emsley King's College London
Timothy M. Frayling
Timothy M. Frayling University of Geneva

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

Exploring online education options can expand your opportunities in Computer Science and related fields. For those concerned about previous academic performance, there are online graduate programs that accept 2.0 gpa, making it easier for students with lower GPAs to continue their studies and advance their careers.

If you are interested in the intersection of technology and the environment, studying Computer Science can open doors to new fields. Learn more about what can you get with an environmental science degree and explore how your technical skills can be applied to pressing environmental challenges.

For those looking to complete their degree quickly, consider enrolling in one of the accelerated computer science degree online programs and jump-start your career in less time.

Alternatively, if you are interested in merging computing with sustainability, look into environmental engineering degrees online. These programs offer affordable ways to develop in-demand skills for a fast-changing job market.

Best Scientists Citing Max A. Little

Trending Scientists