Career Profile
I am an aspiring software engineer with interests in machine learning, programming language design, and distributed computing. I love learning, teaching, and solving problems.
Experience
- Contributed to the public release of AWS Kendra - a machine learning based enterprise search engine
- Implemented error detection and handling mechanisms to facilitate self healing of AWS Kendra
- Developed mechanism to automate the scaling of compute resources for AWS Kendra
- Developed and maintained in house Security Information Event Management (SIEM) system using Elasticsearch, Apache Spark, Logstash, Apache NiFi, and Ansible. System was capable of full text search across 6 petabytes of cyber security data.
- Refactored automated rules engine platform for in house SIEM which increased speeds and decreased costs by 720 times on average.
- Created an automated system for collection and ingestion of system level events across all Linux instances using Nxlog and Logstash. Resulting data was made available for cyber security analysts and automated tools through aforementioned in house SIEM.
- Re-Architected authentication and authorization layer for in build SIEM which reduced operational burden significantly and provided role based security to multiple applications through LDAP groups.
- Created automated process to rotate SSH keys across fleet of 1100 Amazon EC2 instances.
- Improved the functionality of credit eligibility system to decrease losses by over $1.2 million dollars a year
- Created an artificial neural network to be used for collections strategy of delinquent customers
- Designed and supported real-time customer care applications supporting over 50 million people annually
- Advised the creation of applications to manage fraud cases, targeted marketing offers, prevention of write-off, fee negotiation, and transactional alerts
- Created a tool to augment testing processes which increased data discovery speeds by over 30 times
- Gave weekly presentations to a team of 10 regarding the implementation of single paged applications, git version control, and various best practices
- Developed a yearly budget for internal training classes
- Implemented a single paged application to manage the security for customer care applications
- Redesigned existing security functionality improving speeds by over 60 times
- Presented to a team of 10 people regarding the implementation of the security managing application
Projects
Flang -
Designed and created programming language, compiler, and runtime environment.
Language features include closure, higher order functions, and dynamic object manipulation.
Language focused speedy execution of small programs, and is able to execute semantically equivalent Python2 and Python3 programs 4 times faster on average.
Heart Defect Detection -
Built an artificial neural network to detect early indicators of cardiovascular disease.
The resulting neural network was able to predict with 85.6% accuracy whether a given
audio file containing heartbeat sounds had an anomalous heart sound. The paper
describing these results can be found here.
Industrial Badger Application -
Collaborated with a team of 3 other individuals in a capstone project and created a mechanism to
retrieve remote files using voice commands from multiple cloud repositories for the RealWear HMT-1.
Modeled system using BPMN and UML diagrams.
Capstone sponsored by Edutechnologic LLC.
Predicting IMDB Rating -
Collaborated with a team of 2 other individuals to create a machine learning based recommendation
system for new movies. System is able to predict the IMDB rating of new movies where on average it
is 0.6 off from the true rating. Presented to a peer group of 40 individuals on our
findings and the performance of our system.
Task.me -
Created a task management application using Bootstrap & Ruby on Rails.
Users can specify tasks to complete and the application will then generate
a daily schedule for each user based on the user's tasks.
Tic Tac Toe AI -
Created a tic tac toe playing ai using Java.
The AI utilizes a minimax algorithm with alpha-beta pruning in order to maximize
search throughput to maximize expected utility.
Genetic Sudoku -
Implemented an evolutionary algorithm to solve Sudoku problems.
The program has been tweaked to have a small initial population size
with a relatively large mutation rate (35%) to combat local maxima.
Bar None -
In 24 hours, created a mobile application uses real time data to provide users
with a list of the most active events in the local area based upon user activity.
The application assigns a score to the event which is calculated based using the event's
relative popularity with respect to a local sample size. Application written using React Native to
support Android and IOS. API backend written using Ruby on Rails.
Flisp -
Implemented a Lisp dialect with support for arbitrarily precise arithmetic,
lexical closures, read-evaluate-print-loop, and a module system. Parsing done
using antlr4 with a LL grammar. Prior to execution, code is transformed into an
immutable list utilizing the javaslang library.
ASCII Game of Set -
Implemented a fully functional ASCII based game of Set in Ruby using client-server architecture.
Allows for multiple clients to connect to the server. Client-server communication is
done using a REST based API. Synchronicity issues are resolved using polling and
client-side caching.
Frank Shell -
Implemented a command line shell for *UNIX system in C.
Shell supports persistent history and re-execution from command history.
Hotel OSU -
Designed and implemented a relational schema for a mock hotel chain.
Schema consisted of 17 entities with varying degrees of relational cardinality.
Analyzed functional dependencies, and normalized schema into Boyce-Codd normal form.
Implemented normalized schema using Microsoft SQL Server.
Created a web application to demonstrate the capabilities of database and schema design using nodejs.
Multiplayer Snake -
Created a 4-player snake game with support for Xbox 360 controllers which has
two game modes allowing for difference playstyles. Employed multi-threading to allow
for responsive control and display of game.
Skills & Proficiency
Java
Javascript
Python
Ansible
Elasticsearch
Logstash
Kibana
Elastic Beats
Apache Spark
Apache NiFi
SQL
COBOL
Linux
C
C++
Extracurriculars
Machine Learning
-
Established foundations for supervised and unsupervised machine learning.
Introduced various models used for regression, classification, principal
components analysis, anomaly detection, and clustering. Taught core machine
learning topics such as separation of train, validation, and test data,
bias-variance tradeoff, and generalization.
Neural Networks for Machine Learning
-
Introduced many neural network practical ideologies and topologies
such as multi-layer perceptrons, restricted-boltzmann machines, autoencoders,
convolutional neural networks, and recurrent neural networks.
Deep Learning
-
Contributed practical foundations within deep learning using TensorFlow, introducing topics
such as word embeddings, multi-layer perceptrons, convolutional neural networks,
and recurrent neural networks.
Parallel, Concurrent, and Distributed Programming in Java - Rice University
-
Learned foundational topics within parallel programming including async/await, futures, locking,
multi-threading, and socket programming. Contributed theoretical knowledge of spans, critical paths,
Amdahl's Law, and various parallel programming situations. Finally, provided practical knowledge
of distributed systems including Apache Hadoop and Apache Spark.
Intro to Hadoop & MapReduce - Cloudera
-
Introduced the topics of Hadoop Distributed File System (HDFS), MapReduce, and MapReduce design patterns.
Analyzed server logs and purchase logs using MapReduce to answer driven questions.
Awards
The Ohio State University
August 2014 - May 2018
The Ohio State University
May 6th, 2018
The Ohio State University - College of Engineering
April 24th, 2018