Personal Open-Source Project · Flickbar · Montreal, Quebec ·
Designed and built a macOS menu bar app in Swift that arranges windows with two-finger trackpad gestures on their title bars: swipe for halves, thirds and quarters, swipe up to fill the screen, down to restore or minimize, pinch for full screen or close.
Rest two fingers on a title bar to bring up a layout grid, then move and lift to snap the window into the chosen cell; hold ⌘ and swipe to send a window to another display.
Gestures on Dock icons too: show all of an app’s windows, cycle to its next window, hide or quit it, and bring back minimized windows straight into a snapped layout.
A live preview shows where the window will land and a haptic tap confirms the gesture before it runs on lift; Esc cancels, and other scrolling and zooming passes through untouched.
Every gesture is remappable, with optional keyboard shortcuts, window gaps, per-app exclusions and launch at login; signed with a Developer ID, notarized by Apple and installable with Homebrew, on macOS 14 Sonoma or later.
Personal Open-Source Project · KoolestTVLauncher · Montreal, Quebec ·
Designed and built a replacement home screen for Android TV and Google TV in Kotlin, shipped as a single 0.7 MB APK with no third-party libraries, no ads, no account and no tracking.
Liquid Glass interface in the style of iOS 26: a glass menu, a billboard that fills with the focused item’s art, and rows for Continue watching, apps, consoles and streaming services.
Reads Android TV’s Watch Next list and apps’ home-screen channels to build a Continue watching row that works across apps.
Detects consoles and devices over HDMI-CEC (PlayStation, Xbox, Switch, Apple TV and more) and switches the TV to their input in one click.
Makes the Home button open Koolest even on Google TV, where the system launcher can’t be replaced, and does the adb setup from the remote through the TV’s own network debugging.
Gallery screensaver with paintings, clock, weather and now playing; available in English, French and Persian, on any brand running Android 8 to 16.
Experimental Study of Network Flow Optimization Algorithms - Graduate Course Project · Concordia University · Montreal, Quebec ·
Implemented the Successive Shortest Path algorithm from scratch, including residual graph construction, Bellman–Ford based minimum-cost path extraction, and flow augmentation logic.
Designed and executed large-scale experimental evaluation on randomized Euclidean directed graphs across 28 configurations with varying density (𝑟), capacity bounds, and cost regimes.
Compared SSP, Capacity Scaling, Scaling-SSP, and Primal–Dual algorithms using metrics including total cost, flow value, number of augmenting paths, mean path length, and proportional path length.
Demonstrated that the Primal–Dual algorithm consistently achieves optimal minimum cost, while SSP achieves competitive performance in sparse regimes and degrades in dense graphs.
Evaluation of Scalable Training Strategies for Graph Neural Networks - Graduate Course Project · Concordia University · Montreal, Quebec ·
Designed and implemented scalable GNN-based community detection pipelines using GCN and GraphSAGE architectures with full-batch training, neighbor sampling, and graph partitioning strategies.
Conducted extensive experiments on SBM (1K, 10K), CORA, and Reddit datasets, demonstrating that neighbor sampling and graph partitioning enable training on large graphs where full-batch methods fail due to memory constraints.
Achieved up to 90% accuracy on SBM (10K nodes) with graph partitioning while reducing memory footprint, and enabled scalable training on Reddit where full-batch methods resulted in out-of-memory failures.
Analyzed trade-offs between accuracy, training time, and memory usage, providing practical guidelines for scalable GNN deployment in real-world large-scale social networks.
Undergraduate Course Project & For Fun! · Vali-e-Asr University of Rafsanjan, Department of Computer Engineering & Null References: Game Development Team · Rafsanjān & Kerman & Yazd, Iran ·
Uncertainty is an action-adventure space-shooter game, and currently, It’s under development.
We have utilized the beta version of this game as our ”Software Engineering Lab” course project.
Our game is an open-source game hosted on GitHub.
It’s made with Unity3D
Currently, our team isn’t at its peak since all its members are busy at university. Still, we’re looking forward to continuing the Uncertainty and eventually finishing it when we’re free.
