Dr Iti Chaturvedi ~ Lecturer, Information Technology

I focus on Sentiment detection from written text and Emotion identification from face images. My PhD was on dynamic Bayesian networks from Nanyang Technological University, Singapore. During my post-doctoral training I worked on Deep learning with application to text, audio and video. Recently, I have also worked on Recurrent neural networks and Fuzzy classifiers. 

Sentiments in written text:

Product reviews are constantly posted online on websites like Amazon. Natural language processing aims at automatic summarization and recommendation using written text. This includes identifying positive or negative sentiments and the aspect causing them. Conversation agents such as chat-bots can also be trained to discuss a certain topic. This is achieved by converting each word to a vector representation such that semantically similar words are close to each other in the vector space. 

Facial expression classification :

We can predict the emotional state of a person from his facial expression. Facial action units such as a 'smile' allow us to accurately determine the presence of emotions. Convolutional neural networks have shown high accuracy in classifying images. Recently, adversarial models are also being used for generating face emotions. This can be used for classification of YouTube reviews in new languages such as Spanish. 

Teaching

• CP1403: Design Thinking (Level 1; TSV)
• CP1405: Gamification (Level 1; TSV)
• CP1407: Introductory Machine Learning and Data Science (Level 1; TSV)
• CP2403: Information Processing and Visualisation (Level 2; TSV)
• CP2405: Collective Intelligence and Entrepreneurship (Level 2; TSV)
• CP3413: Information Processing and Visualisation (Level 3; CNS & TSV)
• CP5635: Collective Intelligence and Entrepreneurship (Level 5; TSV)
• CP5641: Design Thinking Principles (Level 5; CNS & TSV)

Experience

• 2015 to 2019 - Research Fellow, Nanyang Technological University (Singapore)
• 1998 to 2002 - B. Eng. ( Electrical and Computer ), National University of Singapore (Singapore)

Memberships

• 2020 - ARC Assessor
• 2019 - Area Chair for International Joint Conference on Neural Networks

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.

Journal Articles

• Chaturvedi I, Chit L and Welsch R (2021) Fuzzy Aggregated Topology Evolution for Cognitive Multi-tasks. Cognitive Computation, 13, pp. 96-107, DOI:10.1007/s12559-020-09807-4.
• Valdivia A, Martínez-Cámara E, Chaturvedi I, Luzón M, Cambria E, Ong Y and Herrera F (2020) What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules. Journal of Ambient Intelligence and Humanized Computing, 11, pp. 39-52, DOI:10.1007/s12652-018-1150-3.
• Yang H, Ji S, Chaturvedi I, Xia H, Wang T, Chen G, Pan L, Wan C, Qi D, Ong Y and Chen X (2020) Adhesive biocomposite electrodes on sweaty skin for long-term continuous electrophysiological monitoring. ACS Materials Letters, 2 (5), pp. 478-484, DOI:10.1021/acsmaterialslett.0c00085.
• Chaturvedi I, Satapathy R, Cavallari S and Cambria E (2019) Fuzzy commonsense reasoning for multimodal sentiment analysis. Pattern Recognition Letters, 125, pp. 264-270, DOI:10.1016/j.patrec.2019.04.024.
• Valdivia A, Hrabova E, Chaturvedi I, Luzón M, Troiano L, Cambria E and Herrera F (2019) Inconsistencies on TripAdvisor reviews: a unified index between users and Sentiment Analysis Methods. Neurocomputing, 353, pp. 3-16, DOI:10.1016/j.neucom.2018.09.096.
• Chaturvedi I, Ragusa E, Gastaldo P, Zunino R and Cambria E (2018) Bayesian network based extreme learning machine for subjectivity detection. Journal of The Franklin Institute, 355 (4), pp. 1780-1797, DOI:10.1016/j.jfranklin.2017.06.007.
• Chaturvedi I, Cambria E, Welsch R and Herrera F (2018) Distinguishing between facts and opinions for sentiment analysis: survey and challenges. Information Fusion, 44, pp. 65-77, DOI:10.1016/j.inffus.2017.12.006.

Conference Papers

• Chaturvedi I and Xiang J (2020) Constrained manifold learning for videos. Proceedings of the IEEE International Joint Conference on Neural Networks. In: IJCNN 2020: IEEE International Joint Conference on Neural Networks, 19-24 July 2020, Glasgow, UK
• Chaturvedi I, Cambria E, Cavallari S and Welsch R (2020) Genetic programming for domain adaptation in product reviews. Proceedings of the IEEE Congress on Evolutionary Computation. In: CEC 2020: IEEE Congress on Evolutionary Computation, 19-24 July 2020, Glasgow, UK
• Qian C, Chaturvedi I, Poria S, Cambria E and Malandri L (2019) Learning visual concepts in images using temporal convolutional networks. Proceedings of the 2018 IEEE Symposium Series on Computational Intelligence, SSCI 2018. In: SSCI 2018: IEEE Symposium Series on Computational Intelligence, 18-21 November 2018, Bengalaru, India
• Young T, Cambria E, Chaturvedi I, Zhou H, Biswas S and Huang M (2018) Augmenting end-to-end dialogue systems with commonsense knowledge. Proceedings of the 32nd AAAI Conference on Artificial Intelligence. In: AAAI-18: 32nd AAAI Conference on Artificial Intelligence, 2-7 February 2018, New Orleans, LA, USA
• Chaturvedi I, Cavallari S, Cambria E and Zheng V (2017) Learning word vectors in Deep Walk using convolution. Proceedings of the 30th International Florida Artificial Intelligence Research Society Conference. In: FLAIRS-30: 30th International Florida Artificial Intelligence Research Society Conference, 22-24 May 2017, Marco Island, FL, USA

More

ResearchOnline@JCU stores 24+ research outputs authored by Dr Iti Chaturvedi from 2015 onwards.

Advisory Accreditation: I can be on your Advisory Panel as a Primary or Secondary Advisor.

These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.

Current

• Development and Application of Sustainable Groundwater Management Strategy utilizing Multi-objective Planning Models to Control Saltwater Intrusion in Coastal Aquifers in Tropical Regions.;; (PhD , Secondary Advisor)

The map shows research collaborations by institution from the past 7 years.
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