Hi! My name is Lokesh Karanam 
I am a first-year Masters student in the Department of Electrical Engineering & Computer Science at the University of Missouri. My research interests include machine learning, data science, and computer vision. I am particularly interested in research that explores how geometric learning algorithms coupled with the predictive power of deep neural networks can be used to create innovative applications in computer vision, and natural language processing. Previously, I received my Integrated Post Graduate degree in Information technology from ABV-Indian Institute of Information Technology and Management, Gwalior. (ABV-IIITM).
Python
C++
HTML5/CSS3
C
SQL
R
Research
French
• Research and develop novel geometric deep learning techniques applicable to computational biology and computer vision
• Test and design new equivariant neural networks for learning biomolecular structures
• Organize and conduct large-scale deep learning experiments in a distributed setting
• Review and annotate the latest literature on machine learning
• Design and develop end-to-end machine learning pipelines in AWS using Python and R
• Collaborate closely with business stakeholders and analysts to understand data and the problem needing to be solved
• Work with other development teams to integrate models into user applications
• Reduced miscommunication between service centers globally by engineering over 5 new Angular web applications
• Maintained the testing environments of in-house applications by writing LINQ queries and tuning up test databases
• Built more than 6 secure back end APIs with the Spring framework in an agile development setting
• Effectively contributed to a private repository for the department's NSF-funded 2019 Data Science REU
• Authored an SMS alert pipeline using TensorFlow Lite models on Raspberry Pi microcomputers
• Precisely recorded findings of the gunshot sound detection project in a LaTeX manuscript
• Successfully developed and maintained a GitHub repository of mathematical applications to synthetic biology
• Produced the open-source desktop application Variant Sampler for modeling the sample space of in vitro experiments
• Accurately documented all source code generated for the department's NSF-funded 2018 summer research project
• Assisted students in furthering their understanding of object-oriented programming and data structures
• Trained students to individualize the learning process to achieve their academic goals
• Designed and initiated a customized learning plan for each student’s success
AWARDS:
James W. and Joan M. O'Neill Graduate Fellowship in Engineering | Aug 2020 - Apr 2021
Dean's Engineering Excellence Fellowship | Aug 2020 - Apr 2021
RELEVANT COURSEWORK:
Machine Learning & Pattern Recognition, Design & Analysis of Algorithms, Computational Systems Biology, Advanced Natural Language Processing, Machine Learning Methods for Biomedical Informatics
AWARDS:
Outstanding Graduating Student Award | Apr 2020
President's Honor Roll | Aug 2016 - Apr 2020
Scholastic Key Award | Aug 2016 - Apr 2020
Floyd Tesmer/Strayer University Prize in Computer Science and Engineering | Apr 2019
Alpha Chi Region IV Scholarship | Apr 2019
MINOR:
Mathematics
RELEVANT COURSEWORK:
Data Structures, Object Oriented Applications & Program Development, Compiler Theory, Database Architecture & Concepts, Operating System Concepts, Networking & Telecommunications