Siddalingappa, Rashmi

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Contact

profile_image:

Name:

Siddalingappa, Rashmi

Email:

r.siddalingappa@yorksj.ac.uk

Department:

Data and Computer Science

Organisation:

York St John University

Address:

6th Floor, Export Building, 1 Clove Cres, London E14 2BA

Country:

United Kingdom

Biography

Expertise:

Machine Learning, Artificial Intelligence, Natural Language Processing, Bioinformatics, Space Weather, Deep Neural Networks, Data Science, LLMs

Job title:

Lecturer in Department of Data and Computer Science

Biography:

I am Dr. Rashmi Siddalingappa. I work at the intersection of machine learning, natural language processing, biomedical informatics, and space sciences, and I am currently a Lecturer in Computer & Data Science at York St John University, UK (since August 2024). I earned my Ph.D. in Computer Science from Bangalore University in 2018, where my thesis focused on phonetic and semantic analysis for NLP. After my doctorate I was awarded a National Postdoctoral Fellowship from the Science & Engineering Research Board (DST, India) and conducted postdoctoral research at the Indian Institute of Science (IISc),the top research institute in India, where I received 35,00,000 INR. I then joined West Virginia University as a postdoctoral fellow (Sep 2022–Jul 2024), where I contributed to NASA’s Living With a Star and NSF’s ANSWERS projects. These projects were a part of 2 major awards LWA from NASA and ANSWERS from NSF. I have secured external funding and awards (including a Physics-funded research award and national fellowship funding), participated in multi-institutional grants, and helped prepare competitive proposals. My work spans precision medicine and cancer genomics, speech and phonetics for NLP, and predictive modeling in space weather. I have authored over 30 peer-reviewed journal papers and more than 24 conference papers, contributed book chapters, and have several manuscripts in-press or under review. In teaching and academic leadership I have been a Module Director, supervised undergraduate and postgraduate dissertations, and designed curriculum and labs for undergraduate and postgraduate courses. I bring strong technical skills—including Python, TensorFlow/Keras, scikit-learn, NLTK, PRAAT and experience with speech and genomic datasets—and I combine rigorous research with student mentorship and curriculum development. I am passionate about translating AI and interdisciplinary research into real-world impact and mentoring the next generation of computer scientists.

Qualifications:

BSc in Computer Science MSc in Computer Science PhD in COmputer Science (Natural Language Processing) Postdoc at IISc, India Postdoc at WVU, USA

My Latest

I, Priya Stella Mary ORCID: https://orcid.org/0009-0001-5878-1116, Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436, M, Vinay, S, Deepa, P, Margaret Savitha and M, Kannan (2025) Enhancing image compression through a novel Structural Fidelity Weighted Ensemble (SFWE) model. MethodsX, 15. p. 103695.
Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436, Gornale, Shivanand, Kumar, Sathish and Mane, Arjun (2022) Gender Classification Based on Online Signature Features using Machine Learning Techniques. International Journal of Intelligent Systems and Applications in Engineering (IJISAE), 10 (2). pp. 260-268.
Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436 and S, Deepa (2025) Enhancing Image Classification Performance through Hybrid Self-Supervised Learning Strategies. International Journal of Electronics and Communication Engineering, 12 (7). pp. 90-101.
Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436, P., Prakash, Gornale, Shivanand S. and Kumar, Satish (2024) A Knowledge Based Grade Prediction System using Machine Learning for Higher Education Institutions. Nanotechnology Perceptions, 20 (S14).
Gornale, Shivanand, Kamat, Priyanka, Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436 and Kumar, Sathish (2024) Deep Learning Techniques for a Comprehensive Analysis of Fetal Biometric Parameters Across Trimesters. Transactions on Machine Learning and Artificial Intelligence, 12 (3). pp. 18-45.
Cruz, Alfredo A, Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436, Mehta, Piyush M. ORCID: https://orcid.org/0000-0002-5240-2322, Morley, Steven K. ORCID: https://orcid.org/0000-0001-8520-0199, Godinez, Humberto C. ORCID: https://orcid.org/0000-0001-7138-3481 and Jordanova, Vania K. ORCID: https://orcid.org/0000-0003-0475-8743 (2024) Reduced‐Order Probabilistic Emulation of Physics‐Based Ring Current Models: Application to RAM‐SCB Particle Flux. Space Weather, 22 (6).
Maurya, Vikas Kumar, Kanagaraj, Sekar ORCID: https://orcid.org/0000-0002-9755-862X, Sanjeevi, Madhumathi, Rahul, Chandrasekar Narayanan, Mohan, Ajitha, Dhanalakshmi, Ramachandran,, Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436, Roshan, Roshan and Kanagaraj, Sekar (2024) Finding identical sequence repeats in multiple protein sequences: An algorithm. Journal of Biosciences, 49 (41).
Gornale, Shivanand, Kumar, Sathish, Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436 and Hiremath, Prakash S. (2022) Survey on Handwritten Signature Biometric Data Analysis for Assessment of Neurological Disorder using Machine Learning Techniques. Transactions on Machine Learning and Artificial Intelligence, 10 (2). pp. 27-60.
Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436 and Kanagaraj, Sekar (2021) Anomaly Detection on Medical Images using Autoencoder and Convolutional Neural Network. International Journal of Advanced Computer Science and Applications, 12 (7). pp. 148-156.
Siddalingappa, Rashmi ORCID: https://orcid.org/0000-0001-9786-8436, Hanumanthappa, M. and Gopala, B. (2018) Training Based Noise Removal Technique for a Speech-to-Text Representation Model. Journal of Physics: Conference Series.

My Most Viewed

#	Item title
1	A Hybrid Ensemble of Denoising Autoencoders and Deep Learning Models for Fetal Image Analysis	65	36
2	Survey on Handwritten Signature Biometric Data Analysis for Assessment of Neurological Disorder using Machine Learning Techniques	14	7
3	The Role of the National Assessment and Accreditation Council in Ensuring Quality Education in the Indian Education System: An Analysis of Its Accreditation Standards and Grading Practices	14	6
4	A Novel ML Approach for Computing Missing Sift, Provean, and Mutassessor Scores in Tp53 Mutation Pathogenicity Prediction	13	5
5	“Part of speech tagging – A corpus based approach”	13	1
6	Reduced‐Order Probabilistic Emulation of Physics‐Based Ring Current Models: Application to RAM‐SCB Particle Flux	12	3
7	A Knowledge Based Grade Prediction System using Machine Learning for Higher Education Institutions	12	2
8	Anomaly Detection on Medical Images using Autoencoder and Convolutional Neural Network	9	6
9	Bi-directional long short term memory using recurrent neural network for biological entity recognition	9	4
10	K-nearest-neighbor algorithm to predict the survival time and classification of various stages of oral cancer: a machine learning approach	9	4