About Me

I am currently a Data Scientist at Nokia. I've done my PhD at the University of Warwick at Signal and Information Processing (SIP) Lab supervised by Prof. Tanaya Guha and Victor Sanchez. She is the best supervisor I've ever seen. She showed me the magnificent and fruitful possibilities of a PhD life. My research is applying graph convolution networks to machine learning task (mainly multi-modal) on different applications such as affect learning. During my PhD, I joined DeepMirror and Intel AI lab as an intern. In DeepMirror, I applied graph-based models on life-science data such as chemical, proteins, and RNA data to name a few. For more info, you can check the projects here. I also have collaboration with Google Research and Intel AI Lab. ​

Prior to Warwick, I studied MSC and BSC at the University of Tehran in the ECE Department, Iran. In master, I worked on using deep learning models to predict the stock's price. However, thorough my master, I've implemented and designed many deep learning models for different tasks.

I received my diploma in Physics and Mathematics discipline from Shahid Beheshti, under the supervision of NODET(National Organization for Developing Exceptional Talents).

I was born in a beautiful city, Shahrekord in Iran (you can see some photos here). I’ve spent 25 years of my life in Iran which has imparted great skills and memories.

View My Resume (PDF)

Work Experience

Data Scientist (Nov 2022 - Present)

Nokia, Reading, UK

Machine Learning Engineer (Dec 2021 - Sep 2022)

DeepMirror, Cambrige, UK

  • Designed and helped to develop a small data pipeline for image classification. This approach can be used in wide variety of data types. You can check the details here.
  • Researched and trained Graph Neural Network (GNN) models for task-oriented life-science data. Given the drug structure, I developed GNNs models with huge marginal gains in case of low number of validated samples. You can check the details here.
  • Getting Smart grant 2022 approved by UK Research and Innovation (UKRI) For applying Graph-based solutions on RNA data. You can check the details here.

Reseach Intern (Jan 2020 - March 2020)

Intel AI Lab, San Diego California

  • Created a model-agnostic framework for emotion recognition in video, audio, and sensory data. The model is trained on a large dataset of human emotions and is able to recognize the emotions of a person. You can check the details here.

Publications

Visually-aware Acoustic Event Detection using Heterogeneous Graphs

Interspeech 2022
Collaboration with Google Research
[Paper] [Code] [Video]

Future Image Prediction of Plantar Pressure During Gait Using Spatio-temporal Transformer

IEEE EMBC 2022

Self-Supervised Graphs for Audio Representation Learning with Limited Labeled Data

IEEE Journal of Selected Topics in Signal Processing 2022
Collaboration with Google Research
[Paper] [Code]

Dynamic Emotion Modeling with Learnable Graphs and Graph Inception Network

IEEE Transactions on Multimedia (TMM) 2021
Collaboration with Intel AI Lab
[Paper] [Code]

Compact Graph Architecture for Speech Emotion Recognition

IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2021)
[Paper] [Code]

Education

PhD. in Computer Science

Department of Computer Science, University of Warwick, Coventry, UK, graduated on Nov, 2022.

M.Sc. in Electrical Engineering (GPA: 3.54/4)

School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran, 2018.

  • Highlight: Worked on deep learning
  • Related coursework: Machine Learning, Pattern Recognition, Neural Network & Deep Learining, Game Theory
  • Supervisors: Prof. Ahmad Kalhor and Prof. Babak N Araabi
  • Thesis: ”Prediction in Temporal Systems Based on Online Spectral Image Generating and Using Deep Learning Neural Networks”, you can download article version of my thesis here.

B.Sc. in Electrical Engineering (GPA: 3.48/4)

School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran, 2016.

  • Highlight: Applied smart control method to process of anesthesia
  • Related coursework: Algorithms, C/C++ Programming, Introduction to Artificial Intelligence, Linear Algebra
  • Supervisor: Prof. Fariba Bahrami
  • Thesis: ”Simultaneous control of anesthesia and analgesia In the process of anesthesia during surgery ”

Research Interests

Machine Learning

Graph Machine Learning

Multi-modal Learning

Affect Computing

Teaching Experience

University of Warwick

  • CS345: Sensor Networks and Mobile Data Communications
  • CS342: Machine Learning
  • CS355: Digital Forensics
  • CS416: Optimisation Methods

University of Tehran

  • Neural Network & Deep Learning
  • Pattern Recognition
  • Filter and Circuit Synthesis
  • Engineering Mathematics
  • Microprocessors

Technical Skills

Programming Languages

  • Python (6+ years), C++, MATLAB

Machine Learning and Deep Learning Libraries

  • Scikit-learn, Pytorch, Tensorflow

Numerical Analysis and Optimization Libraries

  • NumPy, SciPy, hyperopt

Cloud Computing Platforms

  • AWS (EC2, S3, Lambda), Microsoft Azure (ML)

Software Development Tools

  • Git, Docker

Honors and awards

  • Smart grant of 2022 approved by UK Research and Innovation (UKRI).
  • Warwick Computer Science PhD students scholarship.
  • Ranked as top 0.15 % (442th) among around 270,000 participants in Iran’s National University Entrance exam in 2011.
  • Ranked as top 10 % in Cumulative GPA among all students of Electrical Engineering in 2014.
  • Accepted in the first stage nationwide competition to select national Mathematics Olympiad team.

Personal Interests

  • Swimming, Football and Rugby.
  • Playing video games and watching movies!
  • Reading about AI topics and trying to find out a new way to incorporate AI into daily life!