Assistant Professor

Dr. Tatinati Sivanagaraja

Department of Electronics & Communication Engineering


  1. Artificial Intelligence/Machine learning
  2. Predictive analytics
  3. Sequential data mining



RVR&JC college of Engineering, Guntur


Kyungpook National University, Daegu,
South Korea


  • 04/01/2017- 16/08/2020 – Research fellow – Nanayang Technological University
  • 05/01/2016 – 31/12/2016 – Post doctoral research fellow – Kyungpook National University

Research Interest

  • 1. Natural Language Processing:
    a. Developed variants for hierarchical attention networks to mimic the human-like understanding of text and thus to classify the quality (relativity and specificity to a given context) of user-generated text.
    b. Developed variants of sequence-to-sequence models coupled with auxiliary information for generating questions automatically for Question-Answering systems. The auxiliary information is learnt with graph based network to extract the information pertinent to the structure of the question.
  • 2. Predictive Analytics:
    a. Developed random convolution nodes (RCNs) based regression network to forecast the time-series data with applications to model renewable energy sources and bio-medical signals
    b. Developed multi-dimensional modelling with extreme learning machines for modelling and then predicting the physiological signals.
  • 3. Learning Analytics:
    a. Developed a data model for retrieving of learning activities data to be capable of facilitating just-in-time feedback
    b. Developed deep learning techniques for question generation, question classification, and quantifying the quality of the questions for e-learning platforms.
    c. Developed sequential datamining techniques for understanding the learner behaviour and then identify the learners-at-risk and early drop-out prediction

Awards & Fellowships

  • 2016 – QUALCOMM Innovation award – Qualcomm and Kyungpook National University
  • 2016 – Top 10 PhD thesis award - Kyungpook National University
  • 2010-2016 – KNU Honours Scholarship - Kyungpook National University
  • 2010 – Merit award – RVR&JC college of engineering


  • IEEE Member
  • APSIPA member
  • IEEE BME member


  • Y. Wang, Zhibin Yu, S. Tatinati, and K. C. Veluvolu, Fast and Accurate Online Sequential Learning For Respiratory Motion Tracking Based on Random Convolution Nodes For Radiotherapy Applications, Applied Soft Computing, Accepted (In Press), 2020. [SCI, I.F: 5.47]
  • Y. Wang, S. Tatinati, K. Adhikar, L.Huang, K. Nazarpour, W. T. Ang, and K. C. Veluvolu, Quaternion Variant of Extreme Learning Machines for Physiological Tremor Prediction in Hand-held Microsurgical Robotic Instruments, IEEE Access, DOI: 10.1109/ACCESS.2017.DOI2018, 2018. [SCI, I.F: 4.098]
  • S. Tatinati, K. C. Veluvolu, K. Nazarpour, and W. T. Ang, Multi-dimensional Modeling of Physiological Tremor for Active Compensation in Hand-held Surgical Robotics, IEEE Transactions on Industrial Electronics (Rank #1 Impact factor], Vol. 64, pp. 1645 - 1655, 2017. [SCI, I.F: 7.53]
  • K. Adhikari, S. Tatinati, K. C. Veluvolu, W. T. Ang, and K. Nazarpour, A Quaternion Weighted Fourier Linear Combiner for Modeling Physiological Tremor, IEEE Transactions on Biomedical Engineering}, Vol. 63, pp. 2336 - 2346, 2016. [SCI, I.F: 4.49]
  • S. Tatinati, K. C. Veluvolu, W. T. Ang, and K. Nazarpour, Ensemble Framework Based Real-time Respiratory Motion Prediction for Adaptive Radiotherapy Applications, Medical Engineering & Physics, Vol. 38, pp. 749 - 757, 2016. [SCI, I.F: 1.92]
  • G. Shafiq, S. Tatinati, W. T. Ang, and K. C. Veluvolu, Automatic Identification of Systolic Time Intervals in Seismocardiogram, Nature Scientific Reports, Vol. 6, 2016. [SCI, I.F: 4.12]
  • S. Tatinati, K. C. Veluvolu, and W. T. Ang, Multi-step Prediction of Physiological Tremor Based on Machine Learning For Robotics Assisted Microsurgery, IEEE Transactions on Cybernetics (Rank \#1 Impact factor journal)}}, Vol. 45, pp. 328 - 339, 2015. [SCI, {\bf I.F: 11.07}]
  • S. Tatinati, K. C. Veluvolu, A hybrid Approach For Short - Term Forecasting of Wind Speed}, The Scientific World Journal, Vol. 2013, Article ID 548370, 2013.
  • S. Tatinati, K. C. Veluvolu, S.-M. Hong, W. T. Latt and W. T. Ang, Physiological tremor estimation with Autoregressive (AR) model and Kalman filter (KF) for robotics applications, IEEE Sensors Journal, Vol. 13, pp. 4977 - 4985, 2013. [SCI, I.F: 2.62]
  • K. C. Veluvolu, S. Tatinati, S. M. Hong and W. T. Ang, Multi-step Prediction of Physiological Tremor for Surgical Robotics Applications, IEEE Transactions on Biomedical Engineering, Vol. 60, pp 3074 - 3082, 2013. [SCI, I.F: 4.49]

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