|Academic Profile |
| || |
Assoc Prof Erik Cambria
Associate Professor, School of Computer Science and Engineering
Phone: +65 67904328
Office: N4 02A 27
|Erik Cambria is the Founder of SenticNet, a Singapore-based company offering B2B sentiment analysis services, and an Associate Professor at NTU, where he also holds the appointment of Provost Chair in Computer Science and Engineering. Prior to joining NTU, he worked at Microsoft Research Asia and HP Labs India and earned his PhD through a joint programme between the University of Stirling and MIT Media Lab. |
Erik is recipient of many awards, e.g., the 2018 AI's 10 to Watch and the 2019 IEEE Outstanding Early Career award, and is often featured in the news, e.g., Forbes. He is Associate Editor of several journals, e.g., NEUCOM, INFFUS, KBS, IEEE CIM and IEEE Intelligent Systems (where he manages the Department of Affective Computing and Sentiment Analysis), and is involved in many international conferences as PC member, program chair, and speaker.
natural language understanding
- Big Social Data Analysis
- Brain-Inspired Natural Language Processing for the Time-Evolving Analysis of the Singaporean Blogosphere
- Gift funds - in support of research activities
- Human-Robot Collaborative AI for Advanced Manufacturing and Engineering (AME) Programmatic Grant : Commonsense Reasoning
- MICE - A Multilingual Corpus of Emotion Expressions of Malay, Indonesian, Chinese and English
- Maritime Silk Road. Past, Present and Future. A projection mapping concept design project
- PONdER: Public Opinion of Nuclear Energy
- Provost’s Chair in Computer Science and Engineering (Erik Cambria)
- Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis
- Smart Visual Analytics of Unconventional Data
- Social Computational Analytics for Trend Discovery and Social Media Marketing
- Twittener: Twitter speech synthesis with natural language processing
- Y Ma, H Peng, E Cambria. (2018). Targeted aspect-based sentiment analysis via embedding commonsense knowledge into an attentive LSTM. AAAI (pp. 5876-5883).
- E Cambria, S Poria, D Hazarika, K Kwok. (2018). SenticNet 5: Discovering conceptual primitives for sentiment analysis by means of context embeddings. AAAI (pp. 1795-1802).
- T Young, E Cambria, I Chaturvedi, H Zhou, S Biswas, M Huang. (2018). Augmenting end-to-end dialogue systems with commonsense knowledge. AAAI (pp. 4970-4977).
- E Cambria, S Poria, A Gelbukh, M Thelwall. (2017). Sentiment analysis is a big suitcase. IEEE Intelligent Systems, 32(6), 74-80.
- Cambria E, Hussain A. (2015). Sentic Computing: A Common-Sense-Based Framework for Concept-Level Sentiment Analysis. Springer, ISBN: 978-3-319-23654-4.
« Back to Research Directory