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Aakriti Adhikari     PhD Student, SyReX Lab Computer Science and Engineering University of South Carolina Address: 1207 Storey Innovation Center 550 Assembly St, Columbia, SC 29201 Email: aakriti@cse.sc.edu Google Scholar   CV   LinkedIn

Teaching Assistant

I have been TA for several courses :

• UofSC: CSCE240 (Advanced Programming Techniques),CSCE416 (Introduction to Computer Networks)
• UToledo: Data structure, Signals and systems,Electrical energy processing, Electric Circuits.

Some of my class/hobby projects

My primary interest lies in playing with images. However, in my free time, I like to read about different existing open-source tabular datasets and like to analyze them for predictive analysis.

• Accuracy improvement in predicting Parkinsons Disease and verifying significance of TQWT based feature. Dataset: "UCI machine learning: Parkinson's Disease Classification"(new): We explored the effectiveness of using tunable Qfactor wavelet transform (TQWT) by training machine learning models on the UCI dataset that has features taken from voice signals through an application of the TQWT technique. [project]
• Intrusion Detection using Machine Learning Algorithms. Dataset : "UNSW NB-15" : We perform explorative analysis of different feature extraction techniques to detect intrusion. [project]
• RL-PONG : Playing Pong from Pixels using Reinforcement Learning. Learning to play pong with reinforcement learning [project][code]
• Calculation of class II immunogenicity incorporating DR-DQ haplotype for donor-recipient compatibility in Kidney transplant. Dataset: "SRTR Database" Calculated Immunogenicity for class II haplotypes to find compatible donor-recipient pair for kidney transplant by using Pandas for data analysis.
• Effect of Matrix Permutation Schemes on Simulation Time for Frequency Domain Linear Circuits Circuit project using Pspice and Matlab
• Others: Autism Prediction ("IMPAC challenge: Predicting autism"), Heart Disease Prediction ("UCI Machine Learning repository :heart disease"),Implementation of IDS using Logistic Regression and Bayesian Approach ("NSL-KDD"),Mechanisms of Action (MoA) Prediction ("Kaggle Dataset"), Algorithms for Data aggregation for energy efficient wireless sensor network, Remote monitoring and control system for smart energy meter,Stereo Audio System, Path Tracking Robot etc.,