Satya Ranjan Dash
Satya Ranjan Dash
Associate Professor
Dr. Satya Ranjan Dash is a computer professional, with his research interest in machine learning, deep learning with NLP, Computational Biology, and Biomedical domain. He is currently working as an associate professor at Kalinga Institute of Industrial Technology(KIIT), Deemed to be University, India. His current research includes Natural Language Processing, particularly text summarization, topic detection and classification, tree banking, dialect classification using deep learning, machine translation for low resource languages.
Educational Qualification
PhD in Computer Science
Administrative Responsibility
Student Affair
Memberships
Indian Science Congress, ISTE
Outreach Activity
I am currently working with research faculties of Spain, USA, Taiwan and Vietnam, and also working with 10 different languages across the globe.
PhD in Computer Science
Administrative Responsibility
Student Affair
Memberships
Indian Science Congress, ISTE
Outreach Activity
I am currently working with research faculties of Spain, USA, Taiwan and Vietnam, and also working with 10 different languages across the globe.
Journals/Conferences :
Dash, S. R., & Ray, R. (2020). Predicting Seminal Quality and its Dependence on Life Style Factors Through Ensemble Learning. International Journal of E-Health and Medical Communications (IJEHMC), 11(2), 78-95.
Sahu, R., Dash, S. R., Cacha, L. A., Poznanski, R. R., & Parida, S. (2020). Epileptic seizure detection: a comparative study between deep and traditional machine learning techniques. Journal of Integrative Neuroscience, 19(1), 1-9.
Abdullah, A. A., Rijal, S., & Dash, S. R. (2019). Evaluation on Machine Learning Algorithms for Classification of Autism Spectrum Disorder (ASD). In Journal of Physics: Conference Series (Vol. 1372, No. 1, p. 012052). IOP Publishing.
Panda, D., Ray, R., & Dash, S. R.* (2020). Feature Selection: Role in Designing Smart Healthcare Models. In Smart Healthcare Analytics in IoT Enabled Environment (pp. 143-162). Springer.
Parida, S., Bojar, O., & Dash, S. R. (2019). Hindi Visual Genome: A Dataset for Multimodal English-to-Hindi Machine Translation. Computacion y Sistemas 23(4):1499–150.
Patra, A. K., Ray, R., Abdullah, A. A., & Dash, S. R. (2019). Prediction of Parkinson’s disease using Ensemble Machine Learning classification from acoustic analysis. In Journal of Physics: Conference Series (Vol. 1372, No. 1, p. 012041). IOP Publishing.
Ray, R., Mallick, D. K., & S.R.Dash* (2019). Intelligent energy-efficient healthcare models integrated with IoT and LoRa network. In Sensors for Health Monitoring (pp. 157-174). Academic Press.
Ray, R., Abdullah, A. A., Mallick, D. K., & Dash, S. R. (2019). Classification of Benign and Malignant Breast Cancer using Supervised Machine Learning Algorithms Based on Image and Numeric Datasets. In Journal of Physics: Conference Series (Vol. 1372, No. 1, p. 012062). IOP Publishing.
Abdullah, A. A., Aziz, A. N. A., Kanaya, S., & Dash, S. R. (2019). Classification of Microorganism Species Based on Volatile Metabolite Contents Similarity. In Journal of Physics: Conference Series (Vol. 1372, No. 1, p. 012061). IOP Publishing.
Parida, S., Bojar, O., & Dash, S. R. (2020). OdiEnCorp: Odia–English and Odia-Only Corpus for Machine Translation. In Smart Intelligent Computing and Applications (pp. 495-504). Springer, Singapore.
Dash, S. R., & Ray, R. (2020). Predicting Seminal Quality and its Dependence on Life Style Factors Through Ensemble Learning. International Journal of E-Health and Medical Communications (IJEHMC), 11(2), 78-95.
Sahu, R., Dash, S. R., Cacha, L. A., Poznanski, R. R., & Parida, S. (2020). Epileptic seizure detection: a comparative study between deep and traditional machine learning techniques. Journal of Integrative Neuroscience, 19(1), 1-9.
Abdullah, A. A., Rijal, S., & Dash, S. R. (2019). Evaluation on Machine Learning Algorithms for Classification of Autism Spectrum Disorder (ASD). In Journal of Physics: Conference Series (Vol. 1372, No. 1, p. 012052). IOP Publishing.
Panda, D., Ray, R., & Dash, S. R.* (2020). Feature Selection: Role in Designing Smart Healthcare Models. In Smart Healthcare Analytics in IoT Enabled Environment (pp. 143-162). Springer.
Parida, S., Bojar, O., & Dash, S. R. (2019). Hindi Visual Genome: A Dataset for Multimodal English-to-Hindi Machine Translation. Computacion y Sistemas 23(4):1499–150.
Patra, A. K., Ray, R., Abdullah, A. A., & Dash, S. R. (2019). Prediction of Parkinson’s disease using Ensemble Machine Learning classification from acoustic analysis. In Journal of Physics: Conference Series (Vol. 1372, No. 1, p. 012041). IOP Publishing.
Ray, R., Mallick, D. K., & S.R.Dash* (2019). Intelligent energy-efficient healthcare models integrated with IoT and LoRa network. In Sensors for Health Monitoring (pp. 157-174). Academic Press.
Ray, R., Abdullah, A. A., Mallick, D. K., & Dash, S. R. (2019). Classification of Benign and Malignant Breast Cancer using Supervised Machine Learning Algorithms Based on Image and Numeric Datasets. In Journal of Physics: Conference Series (Vol. 1372, No. 1, p. 012062). IOP Publishing.
Abdullah, A. A., Aziz, A. N. A., Kanaya, S., & Dash, S. R. (2019). Classification of Microorganism Species Based on Volatile Metabolite Contents Similarity. In Journal of Physics: Conference Series (Vol. 1372, No. 1, p. 012061). IOP Publishing.
Parida, S., Bojar, O., & Dash, S. R. (2020). OdiEnCorp: Odia–English and Odia-Only Corpus for Machine Translation. In Smart Intelligent Computing and Applications (pp. 495-504). Springer, Singapore.