Personal information

Pakistan, Spain, Italy, United Kingdom, Netherlands

Biography

Mr. Younas Khan attained his postgraduate degree in Computer Software Engineering from the College of Electrical and Mechanical Engineering, National University of Sciences and Technology, Islamabad in 2019. Mr. Khan’s research interests are in the areas of Data Science and Machine Learning. He has served in many organizations, i.e. as a visiting faculty at the PMAS Air Agriculture University, Rawalpindi, as an Assistant Supervisor, as a research assistant at CEME, NUST. He has five international conference publications.

Activities

Employment (3)

Universitat Rovira i Virgili: Tarragona, Catalunya, ES

2022-06-14 to 2025-06-13 | PhD Candidate (DEIM)
Employment
Source: Self-asserted source
Younas Khan

Capital University of Science and Technology: Islamabad, PK

2020-02-04 to 2022-04-06 | Lecturer (Computer Science)
Employment
Source: Self-asserted source
Younas Khan

The University of Lahore: Lahore, Punjab, PK

2019-11-04 to 2020-02-08 | Lecturer (Software Engineering)
Employment
Source: Self-asserted source
Younas Khan

Education and qualifications (1)

National University of Sciences and Technology: Islamabad, PK

2015-11-12 to 2019-03-07 | Master of Science in Computer Software Engineering (Computer & Software Engineering)
Education
Source: Self-asserted source
Younas Khan

Works (6)

Federated learning-based natural language processing: a systematic literature review

Artificial Intelligence Review
2024-10-12 | Journal article
Part of ISSN: 1573-7462
Contributors: Younas Khan; David Sánchez; Josep Domingo-Ferrer
Source: Self-asserted source
Younas Khan

Applying Feature Selection and Weight Optimization Techniques to Enhance Artificial Neural Network for Heart Disease Diagnosis

Advances in Intelligent Systems and Computing
2020 | Book chapter
Part of ISBN: 9783030295158
Part of ISBN: 9783030295165
Part of ISSN: 2194-5357
Part of ISSN: 2194-5365
Source: Self-asserted source
Younas Khan
grade
Preferred source (of 2)‎

Blood glucose level prediction using optimized neural network for virtual patients

Advances in Intelligent Systems and Computing
2020 | Book
EID:

2-s2.0-85072831066

Part of ISSN: 21945365 21945357
Contributors: Asad, M.; Khan, Y.; Qamar, U.; Bashir, S.
Source: Self-asserted source
Younas Khan via Scopus - Elsevier

Towards the Selection of the Best Machine Learning Techniques and Methods for Urinalysis

Proceedings of the 2020 12th International Conference on Machine Learning and Computing
2020-02-15 | Conference paper
Source: Self-asserted source
Younas Khan
grade
Preferred source (of 2)‎

Blood glucose level prediction with minimal inputs using feedforward neural network for diabetic type 1 patients

ACM International Conference Proceeding Series
2019 | Conference paper
EID:

2-s2.0-85066492842

Contributors: Asad, M.; Qamar, U.; Zeb, B.; Khan, A.; Khan, Y.
Source: Self-asserted source
Younas Khan via Scopus - Elsevier

Machine Learning Techniques for Heart Disease Datasets

Proceedings of the 2019 11th International Conference on Machine Learning and Computing - ICMLC '19
2019 | Conference paper
Source: Self-asserted source
Younas Khan
grade
Preferred source (of 2)‎