Raja Sunkara

Raja Sunkara

PhD Candidate

I am a second year PhD student in the Computer Science department at Missouri S&T, advised by Prof. Ardhendu Tripathy. Additionally, I am a member of the Statistical Machine Learning Lab. My research interests broadly include machine learning, signal processing, and optimization. Currently, I am working on developing sequential decision making algorithms for multi-armed bandits and black-box optimization.

Previously, I obtained my Master’s thesis from Missouri S&T under the guidance of Prof. Thomas Tie Luo. I earned my Bachelor’s degree in Aerospace Engineering from the Indian Institute of Technology, Madras, where my thesis project was supervised by Prof. Ranjith Mohan. In industry, I worked as a Data Analyst, Data Scientist, Research Engineer, and R&D Data Scientist at Enfrien Innovations, Agrometrics, Matdun Labs, and Alcon, respectively.

Publications

  • Computer Vision in Adverse Conditions: Small Objects, Low-Resolution Images, and Edge Deployment.
    Raja Sunkara, MS Thesis

  • No more strided convolutions or pooling: a new CNN building block for low-resolution images and small objects.
    Raja Sunkara, Tie Luo
    [ Paper ] European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), September 2022.

  • YOGA: Deep object detection in the wild with lightweight feature learning and multiscale attention
    Raja Sunkara, Tie Luo
    [ Paper ] Pattern Recognition, July 2023.

  • Extraction of Key Features and Enhanced Prediction Framework of Breast Cancer Occurrence
    Praveen Sahu, Pragatheiswar Giri, Raja Sunkara, Raji Sundararajan
    [ Paper] International Conference on Trends in Electronics and Informatics (ICOEI), 2022.

Events

  1. I attended the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) virtually in September 2022.
  2. I attended the International Conference on Machine Learning (ICML) virtually in July 2024.

Courses

High-Dimensional Statistics, Functional Analysis I, Mathematics of Medical Imaging, Theory of Reinforcement Learning, Machine Learning in Computer Vision, Advanced topics in AI, Analysis of Algorithms, Convex Optimization, Applied Time-Series Analysis, Probability, Statistics and Stochastic Process, Numerical Analysis, Process Optimization, Multivariate Data Analysis for Process Modeling

Teaching

Professional Service

Reviewer for International Conference on Artificial Intelligence and Statistics (AISTATS)(2024) Reviewer for Neural Information Processing Systems (NeurIPS 2024)