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Prof. M.S. Smitha Rao

Program Chair
B.Tech (Hons) - Computer Science
and Engineering (Data Science)
Professor of Data Science, School of
Computational and Data Sciences
Mail| smitha-Rao Vidyashilp University Faculty


Biography
Professional Education
Teaching Courses
Research Interests
Selected Publications
Ongoing Research
Projects
Research Supervisor to
Biography

Prof. M.S. Smitha Rao is a distinguished researcher and an award-winning academician with over 28 years of experience. With a deep understanding of AI, Machine Learning, Deep learning, Natural Language Processing and related technologies, she is at the forefront of cutting-edge advancements. She holds a Ph.D. in Intelligent Agents. During her academic journey, Prof. M.S. Smitha Rao has held leadership positions as Director, Program Chair, HOD etc. at well-known Universities in India and abroad. She has been invited as an international speaker at Massachusetts Institute of Technology, MIT, Boston and as Guest speaker and Session chair at several International Conferences. Prof. M.S. Smitha Rao is a firm believer in interdisciplinary research and has published over 23 research papers in reputed journals and conferences. Her expertise extends beyond academia, as she actively takes up consultancy services for companies seeking to harness the power of AI. She is renowned for her ability to translate complex technical concepts into actionable insights for businesses. She collaborates with companies across various industries, helping them leverage data-driven strategies to optimize operations, enhance decision-making and drive innovation. With a deep passion for sharing knowledge, Prof. M.S. Smitha Rao continues to inspire and educate future data scientists through her engaging teaching methods and mentorship.

Professional Education
  • Doctor of Philosophy (Ph.D.)
    Bharati Vidyapeeth University, Pune, India
  • Master of Computer Application (M.C.A)
    Osmania University, Hyderabad, India
  • Bachelor of Science (BSc.) Osmania University, Hyderabad, India Specialization: Computer Science, Statistics, Mathematics

Teaching Courses
  • Deep Learning
  • Machine Learning
  • Natural Language Understanding
  • Predictive Analytics
  • Data Visualization and Storytelling
  • Probabilistic Graph Models

Research Interests
  • Deep Learning Modelling for Business Applications
  • Natural Language Understanding
  • Multi Modal Learning
  • Bayesian Learning

Selected Publications
  • Smitha Rao, Nagesh Poojary, J.F.Thomas,“Technology Assisted Contextualized Collaborative Learning Environment (TACCLE)”, Learning International Networks Consortium (LINC),MIT, Cambridge,USA, May 2010.
  • Smitha Rao, Pratima Bhat, “Evaluation of Lossless Compression Techniques”,4thIEEE International Conference on Communication and Signal Processing-ICCSP115, ISBN 978-1-4799-8080-2,IEEE Xplore,Melmaruvathur, Tamilnadu, India, April 2-4, 2015.
  • Smitha Rao, Srivatsala V, Suneetha V, “Optimizing Technical Eco-System of Digital Marketing”, Joint International Conference on Communication, Computing and Power Technologies – ICCCPT 2015 Artificial Intelligence and Evolutionary Computation in Engineering Systems – ICAIECES 2015, Springer AISC Series, Chennai, India April 2015
  • Smitha Rao M S, Pallavi M and Geetha N, “Conceptual Machine Learning Framework for Initial Data Analysis”, Second International Research Symposium on Computing and Network Sustainability (IRSCNS 2018), Springer LNNS Series. ISSN: 2367-3370, Goa, India, August 30-31, 2018
  • Bansal, M., Hans, A.S.A., Rao, S., Lakkavalli, V. (2022).“ Hybrid Approach for Deep Noise Suppression Using Deep Neural Networks”,Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies, vol 116. Springer, Singapore. Read More
  • Arnold Sachith A Hans and Smitha Rao,“Analysis Of AI Based Face Detection Techniques”, Journal of Engineering Sciences, ISSN NO:0377-9254, Vol 10, Issue 12, pp 815 – 821, Dec 2019
  • Saahil Afaq, Smitha Rao, “Significance of epochs on Training a Neural Network”, International Journal Of Scientific & Technology Research, ISSN 2277-8616, vol. 9, Issue 06, pp. 485- 488, Jun 2020
  • Subhadeep Guchhait, Smitha Rao, “Analyzing the Impact of Mini-Batch Size in Optimizing the performance of Deep Neural Networks ”, IJAST, ISSN 22076360 vol. 29, no. 05, pp. 13074-13081, Jun. 2020
  • Mitali Halder, Smitha Rao, “RNN Power to incorporate Discourse in Natural Language Generation”, Journal of Technology, ISSN No: 1012-3407 Volume: 35, Issue: 03, pp. 180-185, Sep 2020.

Ongoing Research Projects
  • JurisTech: AI enabled Jurisprudence
  • Sonic Assurance: Elevating Interview Precision Through Voice Confidence Analysis
  • IndiVoiceVigil: Redefining Security through Precision Speaker Identification
  • VeritasVigil: Predicting Deception in online Interviews
  • Pixel to Person (Multi-Modal Learning)
  • Classroom Insight (Multi-Modal Learning)
  • Evaluating Multimodal Proficiency in Online Interviewee Rating

Research Supervisor to
  • Mr. Amit Sharma
  • Mr. Mohit Bansal
  • Mr. Subhadeep Guchhait
  • Ms. Sneha (Co-Supervisor)

Prof. M.S. Smitha Rao is a distinguished researcher and an award-winning academician with over 28 years of experience. With a deep understanding of AI, Machine Learning, Deep learning, Natural Language Processing and related technologies, she is at the forefront of cutting-edge advancements. She holds a Ph.D. in Intelligent Agents. During her academic journey, Prof. M.S. Smitha Rao has held leadership positions as Director, Program Chair, HOD etc. at well-known Universities in India and abroad. She has been invited as an international speaker at Massachusetts Institute of Technology, MIT, Boston and as Guest speaker and Session chair at several International Conferences. Prof. M.S. Smitha Rao is a firm believer in interdisciplinary research and has published over 23 research papers in reputed journals and conferences. Her expertise extends beyond academia, as she actively takes up consultancy services for companies seeking to harness the power of AI. She is renowned for her ability to translate complex technical concepts into actionable insights for businesses. She collaborates with companies across various industries, helping them leverage data-driven strategies to optimize operations, enhance decision-making and drive innovation. With a deep passion for sharing knowledge, Prof. M.S. Smitha Rao continues to inspire and educate future data scientists through her engaging teaching methods and mentorship.

  • Doctor of Philosophy (Ph.D.)
    Bharati Vidyapeeth University, Pune, India
  • Master of Computer Application (M.C.A)
    Osmania University, Hyderabad, India
  • Bachelor of Science (BSc.) Osmania University, Hyderabad, India Specialization: Computer Science, Statistics, Mathematics
  • Deep Learning
  • Machine Learning
  • Natural Language Understanding
  • Predictive Analytics
  • Data Visualization and Storytelling
  • Probabilistic Graph Models
  • Deep Learning Modelling for Business Applications
  • Natural Language Understanding
  • Multi Modal Learning
  • Bayesian Learning
  • Smitha Rao, Nagesh Poojary, J.F.Thomas,“Technology Assisted Contextualized Collaborative Learning Environment (TACCLE)”, Learning International Networks Consortium (LINC),MIT, Cambridge,USA, May 2010.
  • Smitha Rao, Pratima Bhat, “Evaluation of Lossless Compression Techniques”,4thIEEE International Conference on Communication and Signal Processing-ICCSP115, ISBN 978-1-4799-8080-2,IEEE Xplore,Melmaruvathur, Tamilnadu, India, April 2-4, 2015.
  • Smitha Rao, Srivatsala V, Suneetha V, “Optimizing Technical Eco-System of Digital Marketing”, Joint International Conference on Communication, Computing and Power Technologies – ICCCPT 2015 Artificial Intelligence and Evolutionary Computation in Engineering Systems – ICAIECES 2015, Springer AISC Series, Chennai, India April 2015
  • Smitha Rao M S, Pallavi M and Geetha N, “Conceptual Machine Learning Framework for Initial Data Analysis”, Second International Research Symposium on Computing and Network Sustainability (IRSCNS 2018), Springer LNNS Series. ISSN: 2367-3370, Goa, India, August 30-31, 2018
  • Bansal, M., Hans, A.S.A., Rao, S., Lakkavalli, V. (2022).“ Hybrid Approach for Deep Noise Suppression Using Deep Neural Networks”,Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies, vol 116. Springer, Singapore. Read More
  • Arnold Sachith A Hans and Smitha Rao,“Analysis Of AI Based Face Detection Techniques”, Journal of Engineering Sciences, ISSN NO:0377-9254, Vol 10, Issue 12, pp 815 – 821, Dec 2019
  • Saahil Afaq, Smitha Rao, “Significance of epochs on Training a Neural Network”, International Journal Of Scientific & Technology Research, ISSN 2277-8616, vol. 9, Issue 06, pp. 485- 488, Jun 2020
  • Subhadeep Guchhait, Smitha Rao, “Analyzing the Impact of Mini-Batch Size in Optimizing the performance of Deep Neural Networks ”, IJAST, ISSN 22076360 vol. 29, no. 05, pp. 13074-13081, Jun. 2020
  • Mitali Halder, Smitha Rao, “RNN Power to incorporate Discourse in Natural Language Generation”, Journal of Technology, ISSN No: 1012-3407 Volume: 35, Issue: 03, pp. 180-185, Sep 2020.
  • JurisTech: AI enabled Jurisprudence
  • Sonic Assurance: Elevating Interview Precision Through Voice Confidence Analysis
  • IndiVoiceVigil: Redefining Security through Precision Speaker Identification
  • VeritasVigil: Predicting Deception in online Interviews
  • Pixel to Person (Multi-Modal Learning)
  • Classroom Insight (Multi-Modal Learning)
  • Evaluating Multimodal Proficiency in Online Interviewee Rating
    • Mr. Amit Sharma
    • Mr. Mohit Bansal
    • Mr. Subhadeep Guchhait
    • Ms. Sneha (Co-Supervisor)
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