Saim Mehmood

Data Scientist | Python | Quantum Computing nerd

Email: saim.mehmood.gul(at)

Phone: +92 323 4156407

About Me

A recent graduate of MSc in computer science with 2 plus years of applied research experience working at the Data Mining Lab @ Lassonde School of Engineering, York University Toronto. I did my bachelor’s in software engineering from University of the Punjab, Lahore.

I have experience working with Geo-Spatial Data sets for which I used PostgreSQL & PostGIS and Python to extract insights. I typically visualize data sets along the way to understand the pipelines and models I’m creating.

I conducted research as an Erasmus Scholar @ the Department of Information Technology, Uppsala University, Sweden in the area of Cloud Computing.

During my graduate studies at York University, I was working under the supervision of Prof. Manos Papagelis.

Interests: data mining, graph mining, trajectory data mining, machine learning, big data analytics, data science

Skills: Python (pandas, numpy, scikit-learn, networkx, seaborn, matplotlib), NLP (node2vec, word2vec, graph embeddings), PostgreSQL, PostGIS, MATLAB, GCP (Places & Directions APIs), Java, C#, TensorFlow, Spark, Colab, LaTeX

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aggregate intellect

Research Fellow

June 2021 to date

Out-sourcing permium NLP packages


Data Science Fellow

June 2019 to date

COVID-19 - Risk of Geographical Areas being infected - - Python, PostgreSQL - PostGIS

Using my existing research in trajectory data mining, developed a method to identify areas that are at a high risk of being infected by COVID-19 in the NYC Manhattan region.

Calculating Zakat using Python - - Python, PyPDF2

Data Mining Lab, Lassonde School of Engineering, York University

Graduate Research Assistant

January 2018 - April 2020

The research was related to trajectory data mining, machine learning, and statistical inference.

We developed a method that utilizes trajectories to learn low-dimensional representations of geographical areas that the trajectories span in an embedded space. The method relies on random-walk based approaches for learning node representation of a graph and is able to reveal latent relationships of geographical areas, effectively defining semantic relationships between them.

These latent semantic relationships can improve our understanding of how space is perceived by individuals (through their trajectories) and inform better decisions of urban planning etc.

We published the research titled Learning Semantic Relationships of Geographical Areas based on Trajectories at the IEEE MDM 2020 Conference and received Best Paper Award.

EECS, Lassonde School of Engineering, York University

Graduate Teaching Assistant

January 2018 - April 2021

I have been TAing multiple courses at the Electrical Engineering and Computer Science (EECS) department.

Courses: Programming for Mobile Computing EECS 1022 - Introduction to Database Systems EECS 3412 - Object Oriented Programming from Sensors to Actuators - EECS 1021 - Software Design - EECS 3311

Tasks include: directing tutorials, exam invigilation, final and midterm exam review sessions, grading assignments/exams, office hour duties. OOP, Java, Android Studio, IntelliJ

Swedish National Infrastructure for Computing, Uppsala University

Erasmus Scholar

August 2015 - to January 2016

Designed a framework inside SNIC using Apache Spark, SparkR & Jupyter Notebook to simplify computations of highly parallel scientific applications.

Our project enabled researchers to seamlessly deploy their applications on the spark server and scale it to multiple worker nodes as needed.

Notable Projects

Learning Semantic Relationships of Geographical Areas based on Trajectories

Python (networkx, pandas, numpy, seaborn, matplotlib), PostgreSQL, PostGIS, MATLAB, Google Cloud (Places & Directions) API

• Developed a framework to understand semantic relationships between geographical areas based on object movement paths i.e., trajectories. (Best Paper Award for IEEE Conference on Mobile Data Management 2020)

Expert Developer Recommendation Using Very Large Datasets

SQL, Google BigQuery, Elasticsearch

• Built a search engine to find expert developers by utilizing GitHub datasets. • Reduced 3TB of data into merely 600 MB by keeping developer specific information such as (number of commits, first and last commit, average time between commits etc.)

Cloud Computing, OpenStack, Apache Spark, Jupyter Notebook

• Cloud computing provides usability, scalability and on demand availability of computational and storage resources, remotely. These are the characteristics required by scientific applications and that’s why we used it. The project had two dimensions. First one addresses the benefits of cloud infrastructure for end users. In the second portion, we tried to do performance analysis.

PostgreSQL, PostGIS, Python (numpy, pandas)

• This experimental project was done as a use-case to predict COVID-19 infection hotspots for a probable second wave of cases in Manhattan area.


York University

MSc Computer Science

Jan 2018 - June 2020

York University is a public research university in Toronto, Ontario, Canada. It is Canada's third-largest university, and it has approximately 55,700 students, 7000 faculty and staff, and over 315,000 alumni worldwide.

My studies at York University were focused on extensive research. I accumulated a wealth of knowledge in the area of Data Mining, Big Data, Data Science and Machine Learning. I published research track paper with my supervisor Manos Papagelis, titled Learning Semantic Relationships of Geographical Areas Based on Trajectories for The 21st IEEE International Conference on Mobile Data Management 2020. Our paper received Best Paper Award.

Notable Courses: Data Mining, Mining Software Engineering Data

University of the Punjab

Bachelor of Sciences in Software Engineering

Sep 2012 - Jul 2016

University of the Punjab is a public research university located in Lahore, Punjab, Pakistan. It is the oldest public university in Pakistan.

Four years of undergrad at University of the Punjab helped shaped my understanding of cloud computing, software development, and its requirements engineering. During the course of my studies, I earned an Erasmus Mundus scholarship to spend an exchange semester at Uppsala University.

Notable Courses: Applied Cloud Computing, Software Requirements Engineering, Database Systems


 Building and Deploying Deep Learning Applications with TensorFlow

Certificate Id: AWicQXDaNcUPhvLn1tuwN_zDxNAo

 Introduction to Quantum Computing

Certificate No: AY7IBy3zoehD_C4j4fc-gqdE_brr

Honors and Awards

Alongside my interests in data mining and software engineering I earned some awards:

  • Awarded York University Graduate Fellowship for the entire duration of M.Sc. Computer Science, January 2018
  • Represented Pakistani youth in China, Pakistan Youth Delegation, August 2016
  • Won Erasmus Mundus Exchange Scholarship to spend an exchange semester at Uppsala University, May 2015
  • Winner 17th In-House Speed Programming Competition, University of the Punjab, May 2015