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
June 2021 to date
Out-sourcing permium NLP packages
Data Science Fellow
June 2019 to date
COVID-19 - Risk of Geographical Areas being infected - https://bit.ly/33wUo7X - 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 - https://tinyurl.com/y26fepc4 - Python, PyPDF2
Data Mining Lab, Lassonde School of Engineering, York Universityhttp://dminer.eecs.yorku.ca/
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
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.
Learning Semantic Relationships of Geographical Areas based on Trajectorieshttps://github.com/saimmehmood/semantic_relationships
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 Datasetshttps://github.com/saimmehmood/ExpertDeveloperRecommendation
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.)
Towards Moving Scientific Applications in the Cloudhttps://github.com/saimmehmood/Towards-Moving-Scientific-Applications-in-the-Cloud
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.
COVID-19 - Risk of Geographical Areas being infectedhttps://towardsdatascience.com/covid-19-risk-of-geographical-areas-being-infected-a81938a5e286
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.
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 TensorFlowhttp://www.linkedin.com/learning/building-and-deploying-deep-learning-applications-with-tensorflow
Certificate Id: AWicQXDaNcUPhvLn1tuwN_zDxNAo
Introduction to Quantum Computinghttp://www.linkedin.com/learning/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