Optimization and Data Science (OptiMi'nDS) research group, headed by Dr. Irfan Younas, carries out research and development in Optimization and Data Science related areas. Major research themes in our research group include Evolutionary Computation, Swarm Intelligence, Evolutionary Deep Learning, Multi/Many-objective Optimization, Artificial Intelligence, Data Science, Machine Learning, Natural Language Processing and Information Retrieval.
Solving large scale optimization problems have always been very challenging and demanding. Our research group carries out multi-disciplinary research into mathematical models and intelligent algorithms for a variety of real world optimization, specifically NP-hard problems. The NP-hard problems are very complex with intractably large and highly complex search spaces.
Our research group also works in area of Natural Language Processing (NLP) and Machine Learning. NLP addresses fundamental questions at the intersection of human languages and computer science. Understanding complex language utterances is also a crucial part of artificial intelligence. Applications of NLP are everywhere because people communicate almost everything in language: web search, advertisement, emails, customer service, language translation, radiology reports, etc.
Research Group Members:
· Dr. Irfan Younas (Faculty member)
· Dr. Arshad Ali (Faculty member)
· Dr. Maryam Bashir (Faculty member)
· Mr. Muhammad Amir Iqbal (Faculty member & PhD student)
· Mr. Shakeel Zafar (Faculty member & PhD student)
· Mr. Qamar Askari (PhD student)
· Ms. Maria Tamoor (PhD student)
· Ms. Sadia Marium (PhD student under co-supervision)
· Ms. Umber Nisar (PhD student)
· Mr. Asif Ameer (PhD student)
Past and Ongoing Projects:
· Designing novel Socio-inspired Optimization Algorithms for Global Optimization
· Developing Transfer Learning Based Classifier System for Image Classification
· Evolving Deep Neural Networks using Evolutionary Computation
· Large scale optimization of Assignment, Planning and Scheduling Problems
· Distributed Large Scale Many Objective Optimization
· Multi and Many Objective Optimization Algorithms
· Many Objective Optimization for IoT
· Learning Regular Expressions using Learning Classifier Systems
· Solving Large-scale Optimization Problems using Evolutionary Computation and Machine Learning
· Solving Classification and Learning Problems using Evolutionary Machine Learning
· Predicting Future News Events and Crimes using Data Science
Recent Publications:
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Notes
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- Qamar Askari+, and Irfan Younas. "Improved Political Optimizer for Complex Landscapes and Engineering Optimization Problems." Expert Systems with Applications 182 (2021): 115178. (Impact Factor = 6.954)
- Maria Tamoor+, Irfan Younas, and Hassan Mohy-ud-Din. “Hybrid Active Contour Model for Robust Endocardial Segmentation.” Multimedia Tools and Applications (2021): 1-27. (Impact Factor = 2.757)
- Maria Tamoor+, and Irfan Younas. “A Novel Hybrid Model for Automatic Segmentation of Medical Images using an Evolutionary Algorithm and Active Contour Model.” Journal of X-Ray Science and Technology (2021): 1-19. (Impact Factor = 1.535)
- Qamar Askri+, Irfan Younas, and Mehreen Saeed. “Emphasizing the Importance of Shift-Invariance in Metaheuristics by Using Whale Optimization Algorithm as a Testbed.” Soft Computing, Accepted, 2021: (Impact Factor = 3.643)
- Saba Kanwal+, Irfan Younas, and Maryam Bashir. "Evolving Convolutional Autoencoders Using Multi-Objective Particle Swarm Optimization", Computers & Electrical Engineering 91 (2021): 107108: https://doi.org/10.1016/j.compeleceng.2021.107108. (Impact Factor = 2.663)
- Qamar Askari+, and Irfan Younas. "Political Optimizer Based Feedforward Neural Network for Classification and Function Approximation" Neural Processing Letters 53, no. 01, (2021): 429-458. (Impact Factor = 2.891)
- Shah Bano+, MaryamBashir, and Irfan Younas. "A Many-objective Memetic Generalized Differential Evolution Algorithm for DNA Sequence Design", IEEE ACESS 8 (2020): 222684-222699. (Impact Factor = 3.745)
- Qamar Askari+ , Irfan Younas, and Mehreen Saeed. "Political Optimizer: A novel socio-inspired meta-heuristic for global optimization." Knowledge-Based Systems (2020): 105709. (Impact Factor = 5.921)
- Qamar Askari+, Mehreen Saeed, and Irfan Younas. "Heap-based optimizer inspired by corporate rank hierarchy for global optimization." Expert Systems with Applications (2020): 113702. (Impact Factor = 5.452)
- Irfan Younas*, Uzman Perwaiz+*, and Adeem Ali Anwar+. "Many-objective BAT algorithm." Plos one 15, no. 6 (2020): e0234625. (Impact Factor = 2.740)
- Qamar Askari+, Irfan Younas, and Mehreen Saeed. "Critical evaluation of sine cosine algorithm and a few recommendations." In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pp. 319-320. 2020. (CORE rank A)
- Adeem Ali Anwar+, and Irfan Younas. "Optimization of Many Objective Pickup and Delivery Problem with Delay Time of Vehicle Using Memetic Decomposition Based Evolutionary Algorithm." International Journal on Artificial Intelligence Tools 29, no. 01 (2020): 2050003. (Impact Factor = 0.689)
- Hafiz Asadul Rehman+, Muhammad Iqbal, Irfan Younas, and Maryam Bashir. "Learning Regular Expressions Using XCS-Based Classifier System." International Journal of Pattern Recognition and Artificial Intelligence (2019): 2051011. (Impact Factor = 1.375)
- Irfan Younas, Farzad Kamrani, Maryam Bashir, and Johan Schubert. "Efficient genetic algorithms for optimal assignment of tasks to teams of agents." Neurocomputing 314 (2018): 409-42 (Impact Factor = 4.438)
International Collaborations:
- Carleton University, Ottawa, Ontario, Canada
- Higher Colleges of Technology, Fujairah, UAE