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MS in Applied Information Technology from George Mason University


Contact Details

Skills

SQL

DML, DDL, Joins, Subqueries, Aggregate Functions, Database Design

Python

Pandas, NumPy, Matplotlib, Seaborn, Good understanding of Object Oriented Programming

AI/ML

Scikit-Learn, PyTorch, Tensorflow, PySpark, Keras, Probability, Statistics

Information Vizualization Tools

Excel, Tableau, Power BI, Orange

Version control

Git

Other Skills

Linux, Presentation, Problem solving, Analytical thinking, Teamwork and communication

Education

Masters in Applied Information Technology with concentration in Data Analytics and Intelligence Methods
Few relevant graduate courses I have taken

Information Representation, Processing, and Vizualization

AIT 664
  • DIKW: Data, Information, Knowledge, and Wisdom
  • Data Analysis: Ask, prepare, process, analyse, share, and act
  • Machine Learning concepts, Vizualization tools like Tableau, Orange

Database Management System

AIT 524
  • Databse Design and ER diagrams
  • Database Normalization
  • SQL DDL, DML, Joining Data, Single Row and Group Functions
  • Subqueries, Database objects and Views
  • Introduction to Research

CS 580

Artificial Intelligence
  • Problem Solving as Search
  • Logic and Ontologies
  • Resolution and Prolog
  • ML/DL Basics
  • Evidence based Reasoning

AIT 636

Interpretable Machine Learning
  • Bayesian classifier, Linear/Non-linear classifier
  • Accuracy metrics, Hyperparameters, Evaluation methods
  • Feature selction, Feature generation
  • Clustering algorithms, Evaluating clusters

AIT 736

Applied Machine Learning
  • Learning and Probability Theory, Linear Algebra
  • Supervised and Unsupervised Learning
  • Decision Tree Learning, Bias and Variance Trade-Offs
  • Logistic Regression, SVM, Kernal SVM, Ensemble Classifiers
  • Generative Adversarial Networks
  • PCA, Reinforcement Learning, Markov Models, Deep Learning

Big Data Essentials

AIT 614
  • Big Data analytics, NoSQL Databases
  • Databricks (Microsoft Azure, AWS, Google Cloud)
  • Databricks SQL to query data and visualize queries in dashboard
  • Python for statistical analysis
  • Hadoop, HDFS, MapReduce Programming Paradigm
  • Spark, PySpark

AIT 512

Algorithms and Data Structures Essentials
  • Bags, Queues, Stacks, Linked List
  • Elementary Sorts, Merge Sort, Quick Sort
  • Binary Search Trees, Balanced Searched Trees
  • Directed, Undirected Graphs, Minimum Spanning Trees
  • Analysis of Algorithms

AIT 724

Data Analytics in Social Media
  • Structured representation of unstructured data
  • Analze technical concepts of communitiy detection, recommendation, and behavior analysis in social media
  • Apply computational methods from Data mining, NLP, and related areas to discover patterns in text and network data in social media

Projects

Facial Expression Detection Using Deep Learning Techniques

Implemented CNN, VGGNet, ResNet, and FaceNet models capable of real-time facial expression classification

Python TensorFlow NumPy Scikit-learn Matplotlib Seaborn

Netflix Data Analysis

Analyzed Netflix data to dive deep into steps involved in data analysis process.

Python R NumPy Qgis Orange Excel Matplotlib Jekyll

Understanding Spatial-temporal and demographic factors associated with crime in New York

Analyzed New York city crime dataset to gain insights useful to control crimes in NY.

Python Scikit-learn Excel NumPy Matplotlib

Social Media Data Analysis

Performed sentiment analysis and inter-annotator agreement evaluation on dataset fetched from Twitter (now X).

NLP Python Scikit-learn NumPy Matplotlib

Experience

Graduate Research Assistant

George Mason University
August 2022 - August-2024 Fairfax, VA
  • Implemented a 5G testbed comprising three Software Defined Radios (SDR) based 5G Base Stations (gNBs) and 1 User Equipment (UE) for positioning based on downlink positioning reference signal (PRS) using open source 4G/5G stack software written in C/C++ langauage called Open Air Interface.

  • Implemented automation pipeline using python to collect downlink data from 3 gNBs at UE, enabling the collection of massive amounts of data over-the-air opening the door for AI-enabled positioning with real positioning prototype in future.

  • Designed and constructed a comprehensive 5G end‑to‑end Open‑RAN testbed using open‑source cellular software, specifically srsRAN and SDRs. Additionally, I implemented a near‑real‑time RAN intelligent controller (Near‑RT-RIC) on a docker environment, enabling the efficient deployment of xApps for real‑time control and monitoring of the 5G gNBs. The testbed is used to deploy AI-based xApps in several use cases to optimize RANs.

Python C/C++ Docker 5G/LTE Linux MATLAB Automation Hands-on testbed building AI/ML

Software Engineer

Bitsbit Pvt. Ltd.
Jan 2019 - July 2021 Kathmandu, Nepal
  • Architected and implemented key features for multiple large-scale web applications using React.js and Node.js, serving 100K+ monthly active users.

  • Led and mentored a team of 3 software engineering interns, focusing on React.js best practices and modern web development workflows.

React JavaScript NodeJS MongoDB Linux

Honors and Publication

Publication

Experimental Validation of a 3GPP Compliant 5G‑Based Positioning System.

Certification

Machine Learning by Andrew Ng

Stanford

Contact Details

Call Me

+1 (703) 638-9907

Location

Fairfax, VA, USA