People

Prospective Students

I currently have opening positions for undergraduate, Master's and PhD students. Partial financial support is available from the School of Computer Science and the Faculty of Science/Graduate Studies, in terms of scholarships and teaching assistantships. Research assistatnships are currently available for outstanding PhD students only. Prospective students at all levels are encouraged to contact me about my short and long-term research projects in shallow and deep machine learning, graph representation learning and dimensionality reduciton at the fundamental level and with applications to transcriptomics, single-cell RNA-seq, integrative genome-wide analysis, multi-omics integration and identification of cancer biomarkers. More information for prospective students can be found in the Prospective Students page.

I also run some collaborative projects in cybersecurity, including anti-social engineering, awareness, mitigation and training. If you contact me regarding these projects, add a note in the email subject.

Current Students and Fellows

Postdoctoral Fellows

• None at present

PhD Students

• Mustafa Mohammadi Gharasuie (Since Sep 2022)
  mohamm6m@uwindsor.ca

  Graph Representation Learning



• Danial Ebrat (Since Sep 2022)
  ebrat@uwindsor.ca

  Deep Reinforcement Learning



• Mahshad Hashemi (Since Sep 2021)
  hashem91-at-uwindsor.ca

  Graph Neural Networks



• Akram Vasighizaker (Since Jan 2020)
  vasighi-at-uwindsor.ca

  Manifold Learning - Single Cell RNA-seq Data Analysis

  Single-cell sequencing (scRNA-seq) is an emerging technology used to capture cell-level information and by which individual cells can be analyzed separately. Identifying underlying heterogeneous cell populations is one of the main scRNA-seq analytical challenges that currently we are working on. We focus on the identification of different cell types using manifold learning, Dimensionality reduciton techniques, and clustering techniques on scRNA-Seq data. Cell subgroups identified from such analyses can often be matched to known cell types via previously established marker genes. Identifying of new marker gene, Cluster annotation, Discovery of novel cell subtypes, Classifying of tumor subpopulations, and Detecting cell states variation within a homogenous population, such as differences in cell cycle stage or differential signaling responses to an outside stimulus, are some of the applications in this area.
  There are some other epigenetics challenges and emerging directions in single-cell analysis beyond cell type identification including Differential Expression, Compositional Analysis, and Trajectory Inference.
  

• Sudipta Modak* (Electrical and Computer Engineering Department)
  modak-at-uwindsor.ca

  Lung Tumor Classification using Graph Neural Network

Master's Students

• Lian Duan
  duan12-at-uwindsor.ca

  Graph Representation Learning

  
  

• Shanu Kumar
  kumar34-at-uwindsor.ca

  Reinforcement Learning

  
  

• Karan Kashyap
  kashyapk-at-uwindsor.ca

  Prediciton of cell-to-cell communication in scRNA-seq Data

  
  

• Mohammed Farhan Baluch
  baluchm-at-uwindsor.ca

  Medical Image Segmentation

  
  

Undergraduate Students

• Nitin Ramesh - rames11a-at-uwindsor.ca
• Jose Guillen Santos - guille11-at-uwindsor.ca

Past Students and Fellows

Postdoctoral Fellows

• Ashraf Abu Tabl -
• Abed Alkhateeb - currently Lecturer at the University of Windsor
• Mina Maleki - currently at the University of Detroit Mercy
• Iman Rezaeian - currently at Quicken Loans

PhD Students

• Forough Firoozbakht -
• Osama Hamzeh - currently at St. Clair College
• Pham Quang Huy* - currently at University of Dalat
• Abed Alkhateeb - currently Lecturer at the University of Windsor
• Mina Maleki - currently at the University of Detroit Mercy
• Iman Rezaeian - currently at Quicken Loans
• Yifeng Li* - currenlty Canada Research Chair at Brock University

Master's Students

• Li Zhou
• Yash Trivedi
• Sheena Hora
• Saiteja Danda
• Noor Kammona
• Nachiket Bhide
• Alex Filip
• Ashraf Neisari
• Musab Naik
• Nazia Fatima
• Susha Suresh*
• Sowndarya Krishnamoorthy
• Emamuzo Ogemuno
• Naveen Mangalakumar
• Sheikh Jubair*
• Wenxiao Xu*
• Behzad Rezaei*
• Yixun Li*
• Manal Alshehri
• Mrinalini Pandit
• Siva Reddy
• Ahmad Tavakoli
• Manish Pandit
• Gokul Vasudev
• Navid Shakibapour
• Muhammad Aziz
• Sridip Banerjee
• Priyanka Trivedi*
• Numanul Subhani
• Dario Rojas
• Juan Carlos Rojas
• Tatiana Gutierrez-Bunster
• Semsettin Ilyas
• Wei Yang
• Archana Balagondar*
• Yuanquan Zhang
• Leon French*
• Li Qin
• Vidya Vidyadharan