Yanjia Sun

PhD in Computer Engineering

• Yanjia Sun, Hasan Ayaz, and Ali N. Akansu, "Multimodal Affective State Assessment using fNIRS + EEG and Spontaneous Facial Expression", Brain Sciences, 10, no. 2: 85, Feb. 2020.
• Akansu, Ali, Jim Cicon, Steven Ferris, and Yanjia Sun (authorship in alphabetical order), "Firm Performance in the Face of Fear: How CEO Moods Affect Firm Performance", Journal of Behavioral Finance, 2017.
• Kai Yang, Yanjia Sun, Ruilin Liu, and Jin Yang, "A Big Data Analytics Approach to Anomaly Detection in Cellular Networks", Globecom, 2016.
• Kai Yang, Ruilin Liu, Yanjia Sun, Jin Yang, and Xin Chen,"Deep Network Analyzer (DNA): A Big Data Analytics Platform for Cellular Networks", IEEE Internet of Things Journal, 4(6), pp. 2019-2027, 2016.
• Ruilin Liu, Yanjia Sun, Kai Yang, Tao Quan, and Jin Yang, "Spark-based rare association rule mining for big datasets", IEEE BigData, pp. 2734-2739, 2016.
• Yanjia Sun, Hasan Ayaz, and Ali N. Akansu, "Neural correlates of affective context in facial expression analysis: A simultaneous EEG-fNIRS study", GlobalSIP, pp. 820-824, 2015.
• Yanjia Sun, Ali N. Akansu, and James E. Cicon, "The power of fear: Facial emotion analysis of CEOs to forecast firm performance", IRI, pp. 695-702, 2014. (Second Best Paper)
• Yanjia Sun and Ali N. Akansu, "Automatic inference of mental states from spontaneous facial expressions", ICASSP, pp. 719-723 2014.
• Yanjia Sun and Ali N. Akansu, “Facial expression recognition with regional hidden Markov models,” Electronics Letters, vol. 50, no. 9, pp. 671-673, 2014.

• Kai Yang, Yanjia Sun, and Ruilin Liu, "User-level KQI anomaly detection using markov chain model", No. 10482158, 2019.
• Kai Yang, Yanjia Sun, Ruilin Liu, and Jin Yang, "Fingerprinting Root Cause Analysis in Cellular Systems, No. 10397810, 2019.
• Kai Yang, Yanjia Sun, and Ruilin Liu, "Feature Selection And Pattern Ming For KQI Prediction And Cause Analysis", No. 10332056, 2019.
• Kai Yang, Ruilin Liu, and Yanjia Sun, "System and Method for a Multi View Learning Approach to Anomaly Detection and Root Cause Analysis", No. 9961571, 2018.

• A Disgusted CEO Is A Good CEO, Says New Study (At Least For Shareholders) Forbes
• Software Detects CEO Emotions, Predicts Financial Performance WSJ
• NJIT ECE Professor and Ph.D. Student Present Paper at IEEE International Conference

• IEEE Workshop on Machine Learning and Artificial Intelligence for Multimedia Creation of International Conference on Multimedia and Expo (ICME) 2018 is calling for papers (Deadline: 03/19/2018): Potential topics include but are not limited to the following:
• Generative models for multimedia creation
• AI for multimedia creation
• Data mining techniques for multimedia creation
• Synthesis and prediction of multimedia
• Deep learning application in video and image analysis
• Multi-modal data analysis
• Medical image and signal analysis
• Content of video and image extraction, analysis and application
• Online and distributed computing for multimedia creation
• Wireless technology and demonstrations for multimedia creation
• Security, privacy and policy regulation for multimedia creation
• Machine learning on social, emotional and affective multimedia
• Augmented reality
• Multimedia applied on control system for automation
• Human-computer interaction
• Signal processing including audio, video, image processing, and coding
• Smart multimedia surveillance

• IEEE Internet of Things Journal
• IEEE Transactions on Wireless Communications
• IEEE Transactions on Vehicular Technology

• IEEE International Multimedia and Expo (ICME), San Diego, CA, USA, 2018
• Special Interest Group in AI embedded Cognitive Network, 2017
• IEEE BigData, Boston, MA, USA, 2017
• IEEE Global Conference on Signal and Information Processing (GlobalSIP), Orlando, FL, USA, 2015
• IEEE International Conference on Information Reuse and Integration (IRI), San Francisco, CA, USA, 2014