- Built a 229M-parameter Convolutional Neural Network (CNN) from scratch in PyTorch on 680 training images; benchmarked 7 activation functions, including a custom one (56–67% test accuracy).
- Improved test accuracy from 66.7% to 80.0% (+13 pts) using transfer learning with pretrained ResNet-18/50/152; frozen backbones beat fine-tuning on deeper models (75.0% vs. 61.7%).
- Raised minority-class recall from 40% to 67% on a 4:1 imbalanced dataset using WeightedRandomSampler, evaluated with balanced accuracy and per-class precision/recall.
github.com/IFDES
University of Alberta
CS Specialization
Ali Zain Malik
Software Engineer
Edmonton, Canada · linkedin.com/in/ali-zain-malik · alizainkmalik@gmail.com
Projects
Things I have built for courses and on my own.
- Designed a modular relational data model (authors, posts, follows, inbox, interactions) supporting federated data exchange across independent nodes via REST APIs.
- Built RESTful endpoints for remote author discovery and structured inter-node data synchronization.
- Implemented data access controls (public/private visibility) and an inbox-based data delivery pipeline.
- Coordinated development across a multi-person team using GitHub Projects for task tracking and prioritization.
- Built a location-based mood map in Java using Firebase Firestore and osmdroid, showing the latest mood of each followed user within a 5 km radius, with great-circle distance filtering and real-time 30-second auto-refresh.
- Implemented end-to-end geolocation for mood creation and editing by extending the Firestore data model with coordinates and integrating Android location services and runtime permissions.
- Delivered 5 user-facing features (mood history, detail view, geotagging, follower map, dark mode), adding ~2.8K lines of code in a 6-person Agile team using Git/GitHub pull-request workflows (550+ commits).
- Wrote JUnit unit tests and Espresso UI tests for distance filtering, follow requests, and the add-mood flow, replacing placeholder tests so coverage reflected real app behaviour.
- Implemented anti-aliasing and supersampling techniques to improve rendering quality.
- Optimized memory usage and execution flow using pointer-based data structures.
- Strengthened understanding of low-level systems programming and performance optimization.
Experience
Where I have worked and taught.
Data Engineer Co-op
- Achieved 99% workforce identity reconciliation (445/449) by building a multi-source Azure Databricks ETL/ELT pipeline (Python, PySpark, Spark SQL, pandas, Delta Lake), integrating OFS, UKG, and Maximo PERSONGROUP data through hierarchical ID/name/supervisor entity resolution, deduplication, and data-quality validation.
- Modeled weekly SMRP (Society for Maintenance & Reliability Professionals) Crew Capacity for 438 active field resources using Kimball star-schema dimensional modeling at person-week/work-group grain, producing Power BI-ready fact and dimension tables for Weeks-of-Backlog KPI reporting by department, region, and work group.
- Authored complex SQL across multi-million-row Oracle (Maximo ADW) tables, streamlining ETL into the enterprise data lake (EDL) and validating 50,000+ ingested records, reducing manual extraction time by 30% and reporting discrepancies by 15%.
- Built 4 Power BI dashboards tracking SMRP metrics (Age of Available Work, Work Cycle Time, Schedule Compliance) for 10–20 senior stakeholders, reducing manual reporting turnaround time by 25%.
Teaching Assistant
- Assisted 120+ students with debugging, algorithmic thinking, and structured problem-solving.
- Reviewed assignments and provided detailed feedback to improve correctness and code quality.
Sales Associate
- Analyzed customer requirements and translated them into structured solutions using internal systems.
- Improved transaction workflows, reducing processing time by ~15%.
Volunteering
- Led a 14-member executive team and coordinated large-scale events and initiatives.
- Created local table tennis tournaments through coordination, organization, and teamwork.
Who I Am
My missionHi Everyone :), my name is Ali Zain Malik (yes you read that right, maybe I do share a similar name to a certain One Direction Member 🤔). I am a Computer Science Specialization student at the University of Alberta and an aspiring software engineer. I enjoy taking problems and solving them using creative and efficient approaches. I also am very passionate about sports and a big fan of Liverpool FC. YNWA.
- Bachelor of Science, Computer Science — Specialization
- Relevant Coursework: Machine Learning I, Machine Learning Essentials, Reinforcement Learning, Applied Statistics I & II, Algorithms I & II, File and Database Management
- Languages: Python, SQL, Java, C, JavaScript
- Data & ML Libraries: PySpark, Pandas, Scikit-learn, NumPy, Matplotlib, PyTorch
- Statistics & Machine Learning: Statistics, Regression Analysis, Classification, Model Evaluation, Reinforcement Learning
- Databases: Oracle, Microsoft SQL Server, PostgreSQL, MongoDB, Firebase Firestore
- Data Platforms: Databricks, Power BI, Tableau, Microsoft Excel
- Cloud & Tools: Microsoft Azure, Git (GitHub), Windows OS, PowerShell, IBM Maximo, ServiceNow
- Core Skills: Requirements Gathering, Problem-Solving, Communication, Time Management