Venkittaraman Pallipuram Krishnamani

Professor
Stockton
Office:
Anderson 223
Email Address:
vpallipuramkrishnamani@pacific.edu
Phone Number:
209.946.3072

BIOGRAPHIC SKETCH

I am a full professor in the Electrical and Computer Engineering department and serve as the Program Chair for Electrical Engineering, Computer Engineering and Engineering Physics. My teaching interests bridge engineering and computer science. Some of my favorite undergraduate courses include Advanced Digital Design, Random Signals, and Computer Systems Architecture. At the graduate level, I enjoy teaching Machine Learning (ML) with GPUs, High-Performance Computing, Statistical ML and Image Processing.

My current research focuses on Machine Learning, Natural Language Processing and Generative AI for health sciences. Our prominent projects include PowerCatChat, Pacific’s medical risk assessment chatbot for training dental students, and an AI-enabled Virtual Reality platform for training health sciences students to manage acute care patients. My past research includes the A2Cloud series, which used machine learning to help scientists select Cloud computing resources.

I am always looking for undergraduate and graduate students interested in working at the intersection of AI, Machine Learning and Generative AI, particularly on applications for health sciences education and professionals. If this interests you, I invite you to join our research group.

Education

PhD, Computer Engineering, Clemson University, Clemson, SC, 2013

MS Computer Engineering, Clemson University, Clemson, SC, 2010

Bachelor of Technology, National Institute of Technology, Tiruchirapalli, TN India, 2008

Teaching Interests
  • Computer Systems and Networks
  • High-Performance Computing
  • Random Signals

 

Research Focus
  • Machine learning
  • Natural Language Processing
  • High-Performance Computing


SELECTED PUBLICATIONS

  1. Brittany Ho, Ta’Rhonda Mayberry, Khanh Linh Nguyen, Manohar Dhulipala, Vivek Krishnamani Pallipuram, ChatReview: A ChatGPT-enabled natural language processing framework to study domain-specific user reviews, Machine Learning with Applications, Volume 15, 2024, 100522, ISSN 2666-8270, https://doi.org/10.1016/j.mlwa.2023.100522
     
  2. K.L. Nguyen, T. Mayberry, M. Dhulipala, Y. Liu, M. Khine, and V.K. Pallipuram (2023). An evaluation of tiered machine learning framework to predict science achievement among Singapore students. Accepted in: The 2023 International Conference on Computational Science and Computational Intelligence (CSCI) 2023, Las Vegas NV.
  3. Cearley, J., Pallipuram, V.K. (2023). True-Ed Select Enters Social Computing: A Machine Learning Based University Selection Framework. In: Arai, K. (eds) Proceedings of the Future Technologies Conference (FTC) 2022, Volume 3. FTC 2022 2022. Lecture Notes in Networks and Systems, vol 561. Springer, Cham. https://doi.org/10.1007/978-3-031-18344-7_7
  4. Emani VR, Pallipuram VK, Goswami KK, Maddula KR, Reddy R, Nakka AS, et al. (2022) Increasing SARS-Cov2 Cases, Hospitalizations, and Deaths among the Vaccinated Populations during the Omicron (B.1.1.529) Variant Surge in UK. J Vaccines Vaccin. S21:001.
  5. D. Samuel, S. Khan, C.J. Balos, Z. Abuelhaj, A.D. Dutoi, C. Kari, D. Mueller, and V.K. Pallipuram (2020), A2Cloud-RF:A Random Forest based statistical framework to guide resource selection for high-performance scientific computing on the Cloud. In: Concurrency and Computation: Practice and Experience. 
  6. C. Kari, S. Chen, S. Amir-Mohammadian, and V.K. Pallipuram (2019). Data Migration in Large Scale Heterogeneous Storage Systems with Nodes to Spare. In: International Conference on Computing, Networking, and Communications (ICNC 2019), Honolulu, February 18 - February 21, 2019.
  7. D. Mueller, E. Basha, and V.K. Pallipuram (2018). Incorporating Research in the Undergraduate Experience at a Private Teaching-Centric Institution. In: The 5th Annual Conference on Computational Science and Computational Intelligence, Las Vegas, December 13 - December 15, 2018
  8. C. Balos, D. De La Vega, Z. Abuelhaj, C. Kari, D. Mueller, and V.K. Pallipuram (2018). A2Cloud: An Analytical Model for Application-to-Cloud Matching to Empower Scientific Computing. In: IEEE CLOUD 2018, San Francisco, July 2 - July 8, 2018

View Dr. Pallipuram's Google Scholar profile.