Portfolio
Niteya Shah
Phone +1 540-250-
E-mail niteya.56@gmail.com
niteya@vt.edu
VISA Indian Student with F1 visa
EDUCATION
M.S in Computer Science from Virginia Tech (expected) 2021-
Relevant Coursework
Numerical Analysis and Software Multiprocessor Programming
B.Eng. Computer Science from Vellore Institute of Technology 2016-
Relevant Coursework
Artificial Intelligence Machine Learning Data Mining
Parallel and Distributed Computing High-Performance Computing Data Structures and Algorithms
Business Analytics for Engineers Soft Computing Natural Language Processing
EXPERIENCE
Graduate Researcher August 2021-Present SyNeRGy Lab and SEEC Center Supervisor: Dr Wu Feng Userspace Paging Optimization
- Study the effect of tuning paging parameters on applications with different characteristics using UMAP
- Identify optimal paging parameters in the user space using autotuning.
Global Analysis of Quantum Chromodynamics(QCD)
- Profile QCD carpentry code to find critical sections and linearization points.
- Improve performance of code by parallelization, optimization, and refactoring leading to a two-fold speedup.
Data Scientist May 2020 - July 2021 Tiger Digital Advertising, Vadodara
- Analysed data to gain insights, and learn patterns and trends.
- Tested products for market feasibility and identify customer bases with exploratory campaigns by using data driven decisions.
- Translated research to standard operating procedures and create associated documentation for others to follow and extend.
INTERNSHIPS
DevOps Engineering Intern May 2019 - July 2019 Tiger Digital Advertising, Vadodara
- Executed automated desktop deployments.
- Performed ongoing performance tuning, hardware upgrades, and resource optimization.
- Monitored performance of system architecture, storage methods, and management system software leading to modifications and adjustments.
OPEN SOURCE CONTRIBUTIONS
- Contributor to CuPy, an A NumPy-compatible matrix library accelerated by CUDA
- Contributor to Mlpack, a machine learning library in C++
- Contributor to ensmallen, a flexible C++ library for efficient numerical optimization
- Contributor to Numba, a high performance Python compiler
PROJECTS
Face Recognition using Map Locking Winter 2019
Undergrad Thesis
Supervisor : Dr. Kannan A, Vellore Institute of Technology
- Designed and developed a custom loss function that better extracted information from the final feature representation
- Cleaned and pre-processed the VGGFace2 dataset with 3.3 million images
- Designed a model architecture based on MobileNet and trained the model using both offline and online learning
- Achieved an accuracy of 98.7% on the test segment
Fluid Simulation using CUDA Fall 2019
- Designed and developed a fluid simulation engine using Smoothed-particle hydrodynamics, accelerated by CUDA.
- Achieved a 40-fold speedup over a serial implementation.
- Engine can simulate 10 million particles in real time and show results via matplotlib.
Survey of Load-Balancing Algorithms used in Geometric Space Fall 2019
- Performed extensive review of Multi-Jagged, RCB and RIB load-balancing algorithms in the Zoltan package which is a part of the Trilinos project.
- Compared the performance improvements and error growth caused by spatially partitioning the datasets using the algorithms.
Gujarati Speech Recognition Winter 2018
- Developed a speech-to-text model for the Gujarati Language.
- The model architecture was composed of bidirectional gated recurrent units and used connectionist temporal classification to estimate correctness and was trained on the Microsoft Speech Recognition Dataset.
- The model achieved 85% accuracy on the test segment.