Dara Varam

MS Machine Learning @ AUS. I did my undergrad here in Computer Engineering and Mathematics with a minor in Data Science. I'm Iranian and I'm 23 years old.

I'm currently a visiting student @ MIT Senseable City Lab. I also work as a research & teaching assistant with the Department of Computer Science & Engineering @ AUS.

My research focuses mainly on model compression, optimization and quantization for neural networks and LLMs. I have also done studies in training optimization, computer vision, and eXplainable AI.

The picture on the right isn't what I look like now. I just wanted to put it up there so you know I've always been cool 👺

b00081313@aus.edu | varam@mit.edu

LinkedIn | GitHub | ResearchGate | Scholar

Academic Qualifications

Previous: BSc. Computer Engineering, BSc. Mathematics | American University of Sharjah
Current: MSc. Machine Learning | American University of Sharjah

Completed Graduate Courses

MLR570 | Advanced Machine Learning
MLR555 | Advanced Artificial Intelligence
MLR510 | Generative Deep Learning
MLR503 | Data Mining & Knowledge Discovery
MLR511 | Mobile Application Development With Machine Learning
COE69404 | Cyberphysical System Security

Current Graduate Courses

Machine Learning Thesis

Hyperspherical Quantization: A Geometry-Aware Deep Quanization Framework (Advised by: M. I. AlHajri)

I work on optimizing quantization for deep neural networks using a geometry-aware approach. I mainly focus on using non-Euclidean geometric structures (hyperspherical manifolds) to encode spatial information into the quantization scheme.

Publications

These are papers that have already been published, as reflected on my Google Scholar page (and other venues).

	Cognitive Radio Spectrum Sensing on the Edge: A Quantization-Aware Deep Learning Approach H. A. Abushahla, D. Varam, M. I. AlHajri IEEE Communications Letters, 2025 [ code] [ paper] We study the effect of quantization-aware-training (QAT) on two SOTA spectrum sensing models - DeepSense and ParallelCNN. Models are deployed on a Sony Spresense for hardware evaluation.
	Estimating Nitrogen Dioxide Levels Using Open Data and Machine Learning: A Comparative Modeling Study Dara Varam, Rohan Mitra, Furzeen Kamran, Diaa A. Abuhani, Hana Sulieman, Imran Zualkernan International Society for Photogrammetry and Remote Sensing (ISPRS), 2025 [ paper] We study trends in NO2 levels through publicly available geospatial data, specifically in the Lombardy region of Italy.
	On-Edge Deployment of Vision Transformers for Medical Diagnostics Using the Kvasir-Capsule Dataset Dara Varam, Lujain Khalil, Tamer Shanableh MDPI Applied Sciences, 2024 [ code] [ paper] Applying quantization and optimization techniques to a publicly available wireless capsule endoscopy dataset. Paired with a mobile application for deployment.
	Variable Selection in Data Analysis: A Synthetic Data Toolkit Rohan Mitra, Eyad Ali, D. Varam, Hana Sulieman, Firuz Kamalov MDPI Mathematics, 2024 [ code] [ paper] Follow-up study on developing synthetic datasets algorithmically for variable / feature selection algorithms.
	Wireless Capsule Endoscopy Image Classification: An Explainable AI Approach Dara Varam, Rohan Mitra, Meriam Mkadmi, Radi Aman Riyas, Diaa A. Abuhani, Salam Dhou, and Ayman Alzaatreh IEEE Access, Vol. 11 (IEEE Engineering in Medicine and Biology Society Section), 2023 [ paper] We explore eXplainable AI techniques on a Wireless Capsule Endoscopy dataset (publicly available) to better understand model decision-making and classification.
	Construction of Multiplicative Groups of Polynomials with Non-Zero Identities in Z_p[x] Dara Varam, Ayman Badawi American University of Sharjah Mathematics Theses, 2023 [ code] [ paper] Explorinig construction of multiplicative groups of polynomials with non-zero identities.
	A Hybrid Rolling and Flying Robot for Pipeline Fault Detection Using Deep Learning Megan Ghaly, Rohan Mitra, Abdullah Al Rayess, Assem Ahmed, D. Varam, Mohammad A. Jaradat, Michel Pasquier, Ahmed Khalil [IEEE] Advances in Science and Engineering Technology International Conferences (ASET), 2023 [ paper] Designed, built and programmed a hybrid drone designed for detecting faults on the bodies of oil and gas pipelines.
	Lumerical Simulation of Surface-illuminated Silicon PIN Photodiodes for Datacenter Interconnects S. Ghandiparsi, D. B. Hamadou, D. Varam, A. Soufi, T. Landolsi, A. F. Elrefaie, A. S. Mayet, C. B. Perez, E. P. Devine, S. Y. Wang, T. Yamada, M. S. Islam [IEEE] International Conference on Communications, Signal Processing, and their Applications (ICCSPA), 2022 [ paper] Studying different characteristics of two novel silicon photodiode (SiPD) devices at small- and large-scale.
	Development of Synthetic Data Benchmarks for Evaluating Feature Selection Algorithms Rohan Mitra, Dara Varam, Eyad Ali, Hana Sulieman, Firuz Kamalov [IEEE] International Seminar on Machine Learning, Optimization, and Data Science (ISMODE), 2022 [ paper] Developing synthetic datasets for benchmarking the performance of feature selection algorithms. First of two works that explores the field.

Accepted Papers

These are papers that have been accepted for publication, but are not yet up.

Image-Scaling Attack Prevention in Industrial Cyber Physical Systems

D. Varam, A. Bayoumy, D. A. Abuhani, M. Zulkernine
[IEEE] International Conference on Communication, Computing, Networking, and Control in Cyber-Phyisical Systems (CCNCPS'25), 2025
[ paper]

We propose a novel methodology for detecting and preventing image-scaling attacks for industrial cyber-physical systems using open data.

Submitted Papers

These are papers that have been submitted for publication, but have not yet been released.

Class Separation Dynamics in Vision Transformers: An Empirical Study

D. Varam, L. Khalil, M. Darwish, M. I. AlHajri
IEEE Access, 2025
[ code]

We study the class separation dynamics of Vision Transformers (ViTs) as they train for classification tasks, empirically deriving two “laws” that are always followed as a function of training. These two laws have implications that can strongly guide the training strategy and model optimization for transformer-based learning.

Exploring Cultural Biases of Arabic-Speaking Large Language Models: A Word Embedding Perspective

L. Khalil, A. Bayoumy, D. Varam, A. Aklson
IEEE Access, 2025
[ code]

We study the existence of quantitative bias in Arabic-speaking LLMs. This is done through a word-embedding perspective, specifically looking at the way words are represented in models in terms of sentiment / association and clustering.

Research Projects

This includes other projects that I am currently working on, which have not yet been submitted or published anywhere.

Presentations, Features

Includes presentations conducted online and in-person, and other miscellaneous academic things I've been featured in.

UAE: How AI is a 'game changer' in academics and industry; educators urge 'honest' use

Dara Varam
Khaleej Times, 2025
[ paper]

I was featured on an article regarding AI and its uses in academia. Feel free to take a read based on the website provided.

eXplainable AI for Image Classification Tasks in Medicine

Dara Varam
Google I/O Extended, 2024

Spoke at the Google I/O Extended UAE 2024 keynote, organized through Google Developer Groups Sharjah.

Miscellanea

Peer Reviewed Articles

Nature – Scientific Reports – 2 papers
Nature – BioData Mining – 1 paper
Nature – Signal, Image and Video Processing – 1 paper

Teaching Assistantships

Software: CMP120 / CMP220 / CMP305 / CMP320 – Programming I & II, Data Structures & Algorithms, Database Systems
Hardware: COE242 / COE251 – Microcontrollers & Embedded Systems, Intro. to Computer Systems
Networks: COE271 – Computer Networks I
Mathematics: MTH103 / MTH104 / MTH203 / MTH205 / MTH221 – Calculus I, II & III, Differential Equations, Linear Algebra

Awards & Honors

1st place at the AI-City Quest Hackathon.
2nd place at the Planet-X Mars Rover Mission challenge.
Member of the IEEE-Eta Kappu Nu Honors Society.
Member of the AUS Engineering Honors Society.

Visitor Map

Design and source code from Leonid Keselman's Jekyll fork of Jon Barron's website.

Dara Varam

Academic Qualifications

Completed Graduate Courses

Current Graduate Courses

Machine Learning Thesis

Hyperspherical Quantization: A Geometry-Aware Deep Quanization Framework (Advised by: M. I. AlHajri)

Publications

Cognitive Radio Spectrum Sensing on the Edge: A Quantization-Aware Deep Learning Approach

Estimating Nitrogen Dioxide Levels Using Open Data and Machine Learning: A Comparative Modeling Study

On-Edge Deployment of Vision Transformers for Medical Diagnostics Using the Kvasir-Capsule Dataset

Variable Selection in Data Analysis: A Synthetic Data Toolkit

Wireless Capsule Endoscopy Image Classification: An Explainable AI Approach

Construction of Multiplicative Groups of Polynomials with Non-Zero Identities in Z_p[x]

A Hybrid Rolling and Flying Robot for Pipeline Fault Detection Using Deep Learning

Lumerical Simulation of Surface-illuminated Silicon PIN Photodiodes for Datacenter Interconnects

Development of Synthetic Data Benchmarks for Evaluating Feature Selection Algorithms