Venkittaraman Pallipuram Krishnamani
BIOGRAPHIC SKETCH
I am an Associate Professor in the Electrical and Computer Engineering department, and I also serve as the Program Chair of the Master of Science in Engineering program. My teaching interests are broad and bridge the gap between engineering and computer science. Some of my favorite undergraduate courses include Computer Systems and Networks, Computer Organization, Random Signals, and Advanced Digital Design. For graduate courses, I enjoy teaching High-Performance Computing (HPC), Probability and Statistics for Engineers and Computer Science, and Digital Image Processing.
My research group consists of several undergraduate and graduate students who actively investigate machine learning, natural language processing, high-performance computing, and Cloud computing. Our goal is to guide domain scientists in effectively using these technologies for their applications. To achieve this goal, we combine advanced mathematical concepts with computer programming to develop user-friendly frameworks. Our popular frameworks include the A2Cloud series, which helps domain scientists with Cloud resource selection, and ChatReview, a natural language processing framework that simplifies the analysis of large survey data. Our target domain scientists are chemists, physicists, educators, and medical professionals. If you share our goal of advancing science using computer engineering, I invite you to join us.
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
- Computer Systems and Networks
- High-Performance Computing
- Random Signals
- Machine learning
- Natural Language Processing
- High-Performance Computing
SELECTED PUBLICATIONS
- 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
- 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.
- 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
- 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.
- 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.
- 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.
- 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
- 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.
