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|Biography||Ashish's research interests includes the use of Case-Based Reasoning (CBR) and Deep Learning (DL) in NLP, especially finding ways to develop effective NLP systems for business processes with minimal labelled data.
He has a first class Bachelor's in Technology (BTech) degree majoring in Computer Science and Engineering (CSE) from International Institute of Information Technology, Naya Raipur (IIIT-NR), India. Before starting the PhD, he also worked as an intern at RGU during his BTech final semester under the supervision of Dr. Stewart Massie. In that internship, he worked on a project of Information Extraction and Requirement Mapping from Regulatory Documents which was also his bachelor’s thesis.
|Research Interests||Ashish aims to develop hybrid techniques using CBR and DL for Natural Language Generation (NLG) with a focus on data-to-text generation tasks. He is also interested in the reverse engineering aspect of data-to-text generation task, where using different Information Extraction (IE) techniques we need to develop an initial knowledge base of a structured representation extracted from unlabelled texts/documents.
Natural Language Processing and Generation; Case-Based Reasoning; Deep Learning; and Evolutionary Computing.
|Teaching and Learning||Demonstration: Concurrent Programming (CM3113)|