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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
Future Blog Post
Published:
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Blog Post number 4
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 2
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 1
Published:
This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
projects
Astro-Turfing Review System 
- The search for applying machine learning to real world problems led me to work in the area of Astro-turfing. This is a filtering model with machine learning algorithm to filter-out the fake reviews and hence the fake reviewers from committing review frauds. I used amazon reviews data sets to built a stochastic model on top of it.
Astro-Turfing Review System
- The search for applying machine learning to real world problems led me to work in the area of Astro-turfing. This is a filtering model with machine learning algorithm to filter-out the fake reviews and hence the fake reviewers from committing review frauds. I used amazon reviews data sets to built a stochastic model on top of it.
Facial Recognition and Verification System
- Working with the accuracies and flaw removal strategies with re-implementation of Open-Face/Googles Face-Net, for improving the range of applications in the domain of Security.
- Resolved the false positive 2-D inputs by introducing more features in Stage 1 (face detection) as a.) Orientation Normalization b.) 3D surface representation.
Facial Recognition and Verification System
- Working with the accuracies and flaw removal strategies with re-implementation of Open-Face/Googles Face-Net, for improving the range of applications in the domain of Security.
- Resolved the false positive 2-D inputs by introducing more features in Stage 1 (face detection) as a.) Orientation Normalization b.) 3D surface representation.
Sequence Generative Adversarial Nets with Policy Gradient with Improvements
- Seq-GAN is a unique approach which models the data generator as a stochastic policy in reinforcement learning to solve the problem.
- The RL reward signal comes from the GAN discriminator judged on a complete sequence, and is passed back to the intermediate state-action steps using Monte Carlo search.
Sequence Generative Adversarial Nets with Policy Gradient with Improvements
- Seq-GAN is a unique approach which models the data generator as a stochastic policy in reinforcement learning to solve the problem.
- The RL reward signal comes from the GAN discriminator judged on a complete sequence, and is passed back to the intermediate state-action steps using Monte Carlo search.
Auto-encoder with Memory Defense
- Currently designing a robust auto-encoder and GAN for detecting adversarial images.
- Developed a close proximity approximation model which is also known as on manifold adversarial detectors.
- Enhanced the vanilla auto-encoder to a deep architecture with enforced learning from memory elements.
Auto-encoder with Memory Defense
- Currently designing a robust auto-encoder and GAN for detecting adversarial images.
- Developed a close proximity approximation model which is also known as on manifold adversarial detectors.
- Enhanced the vanilla auto-encoder to a deep architecture with enforced learning from memory elements.
publications
Estimating an HPC Facility’s Capacity For Accommodating Real-time Workflows (Thesis)
Published in National Energy Research Scientific Computing (NERSC), 2019
Download here
**Autoencoder with Memory Defense against Adversarial Attacks
Published in In progress for IJCAI 2021, 2021
talks
Shellshock Vulnerabilities
Published:
Ransomeware End-to-End
Published:
Rise of Deep Learning
Published:
teaching
CSE 001 - Breadth of Computing (Fall 2018)
Undergraduate Course - Teaching Assistant, Lehigh University, Department of Computer Science & Engineering, 2018
Course Description
- Instructor - Prof. Daniel Lopresti
CSE 160 - Introduction to Data Science (Spring 2019)
Undergraduate Course - Teaching Assistant, Lehigh University, Department of Computer Science & Engineering, 2019
Course Description
- Instructor - Prof. Brian D. Davison
CSE 017 - Programming and Data Structures (Fall 2019)
Undergraduate Course - Teaching Assistant, Lehigh University, Department of Computer Science & Engineering, 2019
Course Description
- Instructors -
- Prof. Arielle Carr - CSE017(010), CSE017(011)
- Prof. Houria Oudghiri - CSE017(012)
- Prof. Arielle Carr - CSE017(010), CSE017(011)
This course will cover the design and implementation of algorithms using Java. It assumes that students have had prior experience using conditional statements, loops, arrays, etc., in Java, and will build on this knowledge to develop a full understanding of proper object-oriented programming, algorithmic techniques (e.g., divide-and-conquer, recursion), and the design of data structures (e.g., queues, stacks, trees).
CSE 017 - Programming and Data Structures (Fall 2020)
Undergraduate Course - Teaching Assistant, Lehigh University, Department of Computer Science & Engineering, 2020
Course Description
- Instructors -
- Prof. Houria Oudghiri
- Prof. Houria Oudghiri
This course will cover the design and implementation of algorithms using Java. It assumes that students have had prior experience using conditional statements, loops, arrays, etc., in Java, and will build on this knowledge to develop a full understanding of proper object-oriented programming, algorithmic techniques (e.g., divide-and-conquer, recursion), and the design of data structures (e.g., queues, stacks, trees).