Machine Software

Reecha Khanal

**** ********* *****, *** *******, LA 70148 512-***-**** ******.******@*****.*** linkedin.com/in/reecha-khanal-36a610128 CAREER OBJECTIVE

To build a long-term career in Machine Learning, Data Science, and Software Engineering with opportunities for career growth. EDUCATION

Bachelor’s in Computer Science August 2015-May 2019 University of New Orleans

• Minor: Electrical Engineering and Mathematics

• GPA: 3.75/4.0 Major GPA: 3.91/4.0

PROFESSIONAL EXPERIENCE

Undergraduate Intern Machine Learning Lab Dec 2017 – present Prediction of RNA-Binding Protein using Machine Learning Techniques: Worked to develop a machine learning tool that can predict the protein-binding capacity of RNAs. The principle idea behind the tool is to develop a computational method that overcomes the limitations of tedious experimental methods. The development of genomics screening technique has produced plethora proteins with different sequences, many features of these proteins are yet to be discovered, our tool aims at discovering few features of these proteins regarding their compatibility with RNAs.

• Worked closely in a research team to define objectives, scope and approach for machine learning tool.

• Used various individual as well as ensemble-based machine learning approaches like SVM, GBC, Log Reg, XGBC, Random Forest, and Stacking.

• Used Advanced Java Concepts for biological data mining and data analysis. Residue-wise RNA-Protein Binding Prediction using Machine Learning Techniques: Principle idea behind this project is to develop a machine learning tool using the sequential and structural property of Amino Acids as a feature for predicting and analyzing RNA binding amino acids or residues of a protein.

• Implementation of tools and techniques in machine learning like various types of classifiers, recent machine learning techniques like the Extra Gradient Boosting Algorithm, the Genetic Algorithm, and Stacking. Undergraduate Software Engineering Intern Software Development Lab Jan 2017 – July 2017 Auto-LaTeX Enhancement Tool:

The principle idea behind the toolkit was to make the conversion between abbreviated and elaborated public venues in .bib files, used in LaTeX software, more automated. Worked to develop a JAVA GUI based automated toolkit using swing library and advanced JAVA concepts like parsing and other Input/output file operations.

• This toolkit can be used as an enhancement to the popular LaTeX software.

• The converting software user-interactive, with help of Java GUI. PUBLICATIONS

• Avdesh Mishra, Reecha Khanal, Md Tamjidul Hoque, “Prediction of RNA-binding Protein using Machine Learning Technique”, The 6th Annual Conference on Computational Biology and Bioinformatics, Louisiana, USA, 2018 [Presentation][Poster].

RELEVANT SKILLS

• Languages: JAVA, Python, SQL, HTML, C, MASM

• Software Tools: LaTeX, Multisim, Adobe Photoshop and Illustrator, Android Studio, Eclipse, GitHub

• Database Systems: Oracle, MySQL

• Operating Systems: Linux, Windows, Mac-OSX

AWARDS AND HONORS

• The 6th Annual Conference on Computational Biology and Bioinformatics, Louisiana, USA, 2018

• People’s choice award, Innovate UNO 2017 Research conference

• Privateer Undergraduate Research and Scholarly UNO Experience award recipient, 2016

• Homer L. Hitt Presidential Scholarship, Undergraduate Full Ride Award

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