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Dr. Gowri Srinivasa

Professor
  • Teaching

About

Gowri Srinivasa graduated with a bachelors in Computer Science from PES Institute of Technology, Bangalore in 2004 and then worked with Prof. Jelena Kovacevic, obtaining her PhD in Biomedical Engineering from Carnegie Mellon University in 2008. Since September 2008, she has been a Professor at PES, heading the Center for Pattern Recognition. She has worked with over a hundred students at the undergraduate and graduate levels on various projects focusing primarily on the application areas of Biomedicine/ healthcare and Education and has designed and taught courses related to Data Science, such as data analytics, image and video processing and analysis, machine learning and natural language processing during the semester and over the summer. Gowri has been a Member of the IEEE since 2005 (Senior Member since 2014), an Associate Member of the TC of BISP during 2009-2013 and elected a Member of the TC for two consecutive terms: 2014-2016 and 2017-2019. She holds a patent from the USPTO (2014) for a multimodal communication assist device that helps people who are blind communicate with deaf-mute persons.

Education

  • PhD - Biomedical Engg., Carnegie Mellon University

  • BE - Computer Sc. and Engg, PES Inst of Tech (VTU)

Additional Information

  • DOJ: Oct 24, 2017

  • Experience: Teaching: 9 years 2 months (PESIT South Campus), 4 years 2 months (PESU), Research: 4 years (CMU), 13 years (PES)

Teaching

  • Data Analytics Aug - Dec 2016 - 2022

  • Digital Image Processing and Computer Vision Jan - May 2016, Jan - May 2022

  • Reinforcement Learning Aug - Dec 2019, Jan-May 2021

  • Past courses (VTU) Pattern Recognition, Machine Learning (MTech), Data Mining, Digital Image Processing (CSE), Image Processing (ECE), Computer Concepts and C Programming, Information and Network Security, Software Engineering

Responsibilities

  • Coordinator, International Research Internships in Science and Engineering (iRISE)

  • Guiding of PhD candidates (3 scholars have been awarded degrees by VTU)

  • Consultant (next generation of learning assessments and analytics) for PESU Academy

Research Interest

  • Focused primarily in the application areas of Biomedicine, Healthcare and Education

  • Automated detection of retinopathy of prematurity based on retinal images (with Narayana Nethralaya)

  • Application of AI to predict novel binding of small molecules to oncological targets for drug discovery (with CubeBio)

  • Automated generation of questions and automated assessment strategies (for PESU Academy)

Books

  • G. Srinivasa, "Active Mask Framework for the Segmentation of Fluorescence Microscope Images", PhD Dissertation (2008), Carnegie Mellon University, ISBN. 9781468 149357, July 2012.

Conferences

  • D. Honnavalli, K. Varma and G. Srinivasa, "VIRTECS: Virtual Screening Of Therapeutic Classes Using Encodings of Chemical Structures", Proc. of IEEE Fifth International Conference on Research in Computational Intelligence and Communication Networks, Bengaluru Nov. 26-27, 2020.

  • S. B. Hathwar and G. Srinivasa, "Automated grading of diabetic retinopathy in retinal fundus images using deep learning", Proc. IEEE Intl. Conf. on Signal and Image Processing Applications, Kuala Lumpur, Sep. 17-18, 2019.

  • T. D. Prakash, D. Rajashekar and G. Srinivasa, "Comparison of Algorithms for the Segmentation of Blood Vessels in Fundus Images", Proc. of IEEE International Conference on Applied and Theoretical Computing and Communication Technology (iCATccT), Bengaluru, July 21-23, 2016.

  • A. Kashi, S. Shastri, A. R. Deshpande, J. Doreswamy and G. Srinivasa, "A Score Recommendation System Towards Automating Assessment in Professional Courses", Proc. of the 8th International Conference on Technology for Education (T4E), IIT-Bombay, Mumbai, Dec. 2-4, 2016.

  • T. Dharamsi, R. Jawahar, K. Mahesh and G. Srinivasa, "Stringing Subtitles in Sign Language", Proc. of the 8th International Conference on Technology for Education (T4E), IIT-Bombay, Mumbai, Dec. 2-4, 2016.

  • N. Akash, M. Sood and G. Srinivasa, "Automated Answer Scoring", IEEE International Conference on Advanced Learning Technologies (ICALT), Mumbai, 9-13 July, 2018.

  • H.V. Kumar, J. Nagaraj, M. Irfan, N. Maheshwari, P. Balusani, P. Chatterjee and G. Srinivasa, "PESUBot: An empathetic goal-oriented chatbot", Proc. NLP-2018, IEEE ICACCI, September 2018.

  • M. S. Shushmita, G. Srinivasa, "PoP: Panorama of the Past - A Visual Summary of High School History", Proc. IEEE International Conference on Technology for Education (T4E), Chennai, December 2018.

  • V. N. Rao, S. Suresh, G. Srinivasa, "Gamification of a Visual Question Answer System", Proc. IEEE International Conference on Technology for Education (T4E), Chennai, December 2018.

  • Manish Shetty, Soumya Mary Alex, Merlin Moni, Fabia Edathadathil, Preetha Prasanna, Veena Menon, Vidya P Menon, Prashanth Athri, Gowri Srinivasa, "A Machine Learning Understanding of Sepsis", Proc. of the Intl Conf. of the IEEE Engineering in Biology and Medicine Society (EMBC), Oct. 31-Nov. 4, 2021.

  • P. R. Patnala, S. Saha and G. Srinivasa, "Solving the N-Queens and Golomb Ruler Problems Using DQN and An Approximation of the Convergence", Proc. of the 28th Intl. Conf. on Neural Information Processing (ICONIP) 2021, Bali, Indonesia, Dec. 8-12, 2021.

Journals

  • D. Rajashekar, G. Srinivasa and A. Vinekar, "Comprehensive Retinal Image Analysis For Aggressive Posterior Retinopathy Of Prematurity", PLOS One, 11 (10), e0163923, October, 2016.

  • B. J. Sandesh, G. Srinivasa, "Text-Mining based Localization of Player-Specific Events from a Game-Log of Cricket", International Journal of Computer Applications in Technology, vol. 55(3), 2017.

  • B. J. Sandesh, G. Srinivasa, "A framework for the automated generation of paradigm adaptive summaries", International Journal of Computer Applications in Technology, vol. 55(4), pp. 276-288, Aug. 2017.

  • Sandesh B. J., A. Anthony, G. Abhilasha, N. Shaik, G. Srinivasa, "A Team Recommendation System and Outcome Prediction for the Game of Cricket", Journal of Sports Analytics, IOS press, pp. 1-14, Apr. 2018.

  • S. Shankar, I. Bhandari, D. T. Okou, G. Srinivasa, P. Athri, "Predicting adverse drug reactions of two‐drug combinations using structural and transcriptomic drug representations to train an artificial neural network", Chemical Biology and Drug Design, 97(3), 665-673, 2021.

  • V. Murali, Y. M. Pradyumna, C. Konigs, M. Nair, S. Madhu, P. Nedungadi, G. Srinivasa and P. Athri, "Predicting Clinical Trial Outcomes Using Drug Bioactivities through Graph Database Integration and Machine Learning", Chemical Biology and Drug Design, May 2022.

  • N. Suresh, N. C. A. Kumar, S. Subramanian and G. Srinivasa, "Memory Augmented Recurrent Neural Networks For De-novo Drug Design", Plos One, vol. 17(6), e0269461, June 2022.

Others

  • Patent title: Adpative Multimodal Communication Assist System US PTO - Application Number - 13/330,712 (Patent filed Dec 20, 2011; patent granted July 29, 2014)

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