Drexel University

Doctor of Philosophy - Ph.D., Computer Science

2017 – 2023

Thesis area: Machine learning, Sequential Data, Neuro-inspired Neural Networks, Anomaly Detection

Thesis title: Respresentation Learning on Sequential and Temporal Data Manifolds

University of Tehran

Master's degree, Computer Science

2013 – 2016

Thesis area: Image Classification, Computational Neuroscience, Spiking Neural Networks, Convolutional Neural Networks

Thesis title: Utilizing deep architecture in spiking neural networks for object recognition based on the visual cortex

University of Tehran

Bachelor's degree, Computer Science

2008 – 2013

Machine learning research intern

Robust and Safe Deep Learning, BOSCH AI

Jun 2022 – Sep 2022 (3 mos)

Research area:

During my internship, I designed and implemented a machine learning model for manufacturing time series data prediction. In doing so, I used state-of-the-art multimodal constrastive-based attention models.

Machine learning research intern

Department of Biomedical and Health Informatics, CHOP

Jun 2021 – Dec 2021 (6 mos)

Research area:

My research focused on designing efficient machine learning methods to find patients' similarities with the ultimate goal of providing better treatments. In doing so, I used natural language processing algorithms as well as graph representation learning.

Graduate Research Assistant

Sparse Coding Lab, Drexel University

Sep 2020 – May 2023 (3 yrs 9 mos)

Research area: 

Studying neuro-inspired solutions to computer vision problems such as face recognition and image colorization using neuromorphic software, e.g., sparse coding, and hardware concepts.

Graduate Teaching Assistant

Computer Science Department, Drexel University

Sep 2018 – Sep 2020 (2 yrs)

• Deep Learning (CS615, 2020) 

• Developing User Interfaces (CS530, 2020) 

• Introduction to Artificial Intelligence (CS30, CS510, 2018, 2019)

•  High-Performance Computing (CS540, 2019)

• Advanced Programming techniques (CS571, 2019) 

Instructor at Robot Springboard Technology Camp

College of Computing & Informatics, Drexel University

Aug 2019

• Robot Springboard Technology Camp is designed for middle school girls to learn basic programming concepts.  

• The CCI curriculum included an introduction to robotics, block programming techniques, and circuitry hands-on experiences.

Research Assistant

Computer Vision Lab, Computer Science Department, Drexel University

Sep 2017 – Sep 2018 (1 yr)

Worked on a project for classification observed or imagined objects using fMRI recorded data from human subjects by applying deep neural networks (Python, PyTorch).

System and Quality Assurance Analyst 

System Group | همكاران سيستم

Jun 2013 – Aug 2017 (4 yrs 3 mos)

• Worked both in the Quality Assurance department and R&D department, mostly on Sale and Retail domains.

•  Created and maintained Use Case, Business Requirement, Functional and System Requirements Documents, and integrated Test Cases, the total count increased by 80%. 

• Created automatic testing scripts using Microsoft Testing Manager which resulted in more secure and comprehensive testing in a short amount of time

Research Assistant

Computational Neuroscience Research Lab, University of Tehran

Sep 2013 – Aug 2016 (3 yrs)

Designed and implemented a deep spiking neural network for object recognition and face identification, in an unsupervised manner based on the human visual cortex (C++, CUDA, CARLsim).

• The designed model could be trained on all sorts of images without needing any labels, which expands the area of its applications.

• Also, the model created human-understandable mid-layer features over the neural network hierarchy.

Volunteer Research Assistant

Institute for Research in Fundamental Sciences (IPM)

Sep 2012 – Dec 2013 (1 yr 4 mos)

• Studied individuals reaction time while performing primary object recognition tasks both in children and adults and modeled the outcomes, in order to investigate the neural pathways used in each category of subjects. (MATLAB, Psych toolbox)

•  Modeled the decision-making process in the fast categorization psycho-task using biologically plausible models such as HMAX and compared the results with human psycho tasks. (MATLAB)