Summary
I obtained my BSc. in Computer Science and Engineering (CSE) from Bangladesh University of Engineering and Technology (BUET) with major in AI.
I am interested in spatial databases and machine learning. I have also worked with meta-heuristics applied in transit network design problem.
Education
| I received my B.Sc. degree in Computer Science & Engineering at Bangladesh University of Engineering & Technology (BUET) in September, 2017. I completed my undergraduate thesis under the supervision of Dr. Sohel Rahman. | |
| I received my Higher Secondary Certificate (HSC) from Dhaka City College. | |
| I received my Secondary School Certificate (SSC) from Government Laboratory High School, Dhaka. |
Research
- A Heuristic Aided Stochastic Beam Search for Solving Transit Network Design Problem
Kazi Ashik Islam, Ibraheem Muhammad Moosa, Jaiaid Mobin, Muhammad Ali Nayeem and M. Sohel Rahman.
Swarm and Evolutionary Computation, Elsevier (Accepted, Feb 15, 2019)
Summary: Designing efficient routes for a transit network is one of the main problems faced by city planners of the world. Designing these routes is a multi-criteria decision making problem with a large solution space. In this paper we present a novel heuristic that can quickly generate good solutions. Also we propose a Stochastic Beam Search algorithm with a heuristic inspired successor operator. We conduct extensive experiments on some benchmark data-sets and perform statistical tests on the results. We compare our results with previous studies and show that our algorithms produce superior results. In particular, for large data-sets, the solutions generated by our heuristic in less than a second turn out to be better than solutions generated in two hours by the state of the art algorithm. - Towards Efficient Maintenance of Continuous MaxRS Query for Trajectories
Muhammed Mas-ud Hussain, Kazi Ashik Islam, Goce Trajcevski, Mohammed Eunus Ali.
20th International Conference on Extending Database Technology (EDBT)
Summary: We address the problem of efficient maintenance of the answer to a new type of query: Continuous Maximizing RangeSum (Co-MaxRS) for moving objects trajectories. The traditional static/spatial MaxRS problem finds a location for placing the centroid of a given (axes-parallel) rectangle R so that the sum of the weights of the point-objects from a given set O inside the interior of R is maximized. However, moving objects continuously change their locations over time, so the MaxRS solution for a particular time instant need not be a solution at another time instant. In this paper, we devise the conditions under which a particular MaxRS solution may cease to be valid and a new optimal location for the query-rectangle R is needed. More specifically, we solve the problem of maintaining the trajectory of the centroid of R. In addition, we propose efficient pruning strategies (and corresponding data structures) to speed-up the process of maintaining the accuracy of the Co-MaxRS solution. - Visualization of Range-Constrained Optimal Density Clustering of Trajectories
Muhammed Mas-ud Hussain, Goce Trajcevski, Kazi Ashik Islam, Mohammed Eunus Ali.
Advances in Spatial and Temporal Databases 15th International Symposium, SSTD 2017 (Awarded as the best demonstration paper).
Summary: We present a system for efficient detection, continuous maintenance and visualization of range-constrained optimal density clusters of moving objects trajectories, a.k.a. Continuous Maximizing Range Sum (Co-MaxRS) queries. Co-MaxRS is useful in any domain involving continuous detection of “most interesting” regions involving mobile entities (e.g., traffic monitoring, environmental tracking, etc.). Our system solves two important problems: (1) Efficiently computing Co-MaxRS answer-set; and (2) Visualizing the results.
Projects
Academic
- Machine Learning and Pattern Recognition Projects: I implemented these projects as part of CSE 472, 474 (Machine Learning, Pattern Recognition) courses. I used various tools such as: C/C++, Python, Matlab for implementation.
- Decision Tree Learning for Cancer Diagnosis
- Ensemble Learning (AdaBoost) for Cancer Diagnosis and testing results by cross validation
- Topic Modeling using Gibbs Sampler on 20 newsgroups dataset
- Expectation-Maximization Algorithm for Gaussian Mixture Model
- Variants of Perceptron Algorithm, Artificial Neural Network
- Template Matching to track a reference object in a video file
- Channel Equalization using context dependent classification
- Clustering (DBSCAN) Algorithm
- Semi-Autonomous Obstacle Avoider In this project we designed afour wheel car which can automatically avoid obstacles in its way and maintain a definite direction. Itcan also be controlled manually. Tools: Raspberry Pi, Python.
- Simplified Automated Quad-copter This project was done as a part of CSE 316 (Microprocessors and Microcontrollers Sessional) course. We controlled simple movements of a quad-copter by avr micro-controllers. Tools: AVR Microcontroller, C
- Checkers AI It is a checkers game playing AI agent that follows the Minimax algorithm with alpha-beta pruning and depth limited search. Tools: Java.
- Online Card Game This is a java implementation of popular card game 29. Players on the same localnet can play. Multiple games at the same time is supported. Tools: Java.
- Grayscale Image Conversion This is a C program that can convert a BMP (bitmap) image file to it’s gray-scale version. It uses “iGraphics” library which is a wrapper for OpenGL in 2D.
- Tower of Hanoi Simulator It is a C program that simulates and solves the tower of hanoi problem. For GUI, it uses “iGraphics” library which is a wrapper for OpenGL in 2D.
Technical Skills
- Programming & Scripting Languages:
- Python: I love programming in python and am using it everyday at my workplace.
- C/C++: I used C/C++ as my primary language for competitive programming contests.
- Java: I used java in several academic projects in undergraduate level.
- Bash: I use Linux (Arch) as my primary OS and am fairly familiar with Shell scripting.
- I have also worked with SQL/PLSQL and JavaScript.
- Database
- Relational Dababases: I actively use PostgreSQL and it’s geographic extensions (PostGIS). I have also worked with Oracle and SQLite.
- NoSQL Databases: I have worked with Elasticsearch extensively. I used it for full text search and geo queries.
- Framework: Django
- Writing Tools: LaTeX, Microsoft Office (Word, PowerPoint).