
Study with us
Be involved with innovative & important research through either our Master of Computer Science program or our PhD in Computer Science.
Our active research institute & groups:
Institute for Big Data Analytics
The Institute for Big Data Analytics is a first of its kind in Canada. It has a mission create knowledge and expertise in the field of Big Data Analytics by facilitating fundamental, interdisciplinary and collaborative research, advanced applications, advanced training and partnerships with industry.
bigdata@cs.dal.ca
https://bigdata.cs.dal.ca
Director: Dr. Stan Matwin, Ph.D. CRC
Following his Ph.D., Stan was an Assistant Professor in the Department of Mathematics and Computer Science, Warsaw University. He joined University of Guelph in 1977, and Acadia University in 1980. Since 1981 at the University of Ottawa, as of 2011 a Distinguished University Professor (on leave). For many years in charge of graduate studies in Computer Science at the University of Ottawa, and a founding father of the Graduate Certificate in Electronic Commerce at University of Ottawa in 1999. Also affiliated with the Institute for Computer Science of the Polish Academy of Sciences as a Professor, Stan has worked at universities in the U.S, Europe, and Latin America. Recognized internationally for his work in text mining, applications of Machine Learning, and data privacy, author and co-author of more than 250 research paper. Former president of the Canadian Artificial Intelligence Association (CAIAC) and of the IFIP Working Group 12.2 (Machine Learning). Stan has significant experience and interest in innovation and technology transfer. One of the founders of Distil Interactive Inc. and Devera Logic Inc.
Dalhousie Natural Language Processing (DLNP) group
The Dalhousie Natural Language Processing Group (DNLP) provides information about NLP-related research conducted at the Dalhousie University, and it is a forum for discussion, collaboration, and interaction between researchers interested in the philosophies, theories, and applications related to NLP.
Group Website: | http://dnlp.ca |
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Contact Information: | Dr. Vlado Keselj vlado@cs.dal.ca Phone: 1-902-494-2893 Fax: 1-902-492-1517 (att. Vlado Keselj) |
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Hierarchical Anticipatory Learning (HAL) Lab
We are a lab at Dalhousie University whose research interests are primarily in the fields of Computational Neuroscience and Machine Learning.
Group Website: | http://projects.cs.dal.ca/hallab |
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Contact Information: | Thomas Trappenberg at: tt@cs.dal.ca |
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Funding: | NSERC, CIHR |
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Industry Partners: | DRDC |
Seminar Series: | Hallab chats Wednesdays 10am-11:30 |
Related Conferences and Journals: |
Cosyne, NIPS, IJCNN |
Image Pattern Analysis and Machine Intelligence (IPAMI)
The research interests of the group include human vision perception and perceptual organization, computation models of perception and perceptify technology, statistical and structural image pattern analysis, perceptual pattern learning, generic image segmentation, perceptual feature classification and grouping, vision applications on surveillance (motion), content based image retrieval, medical imaging, and robot vision, etc.
Group Website: | http://projects.cs.dal.ca/ipami/ |
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Contact Information: | Dr. Qigang Gao Phone: 1-902-494-3356 Email: q.gao@dal.ca |
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Funding: | NSERC, MITACS & Industrial partners |
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kNowledge Intensive Computing for Healthcare Enterprises (NICHE)
The NICHE (kNowledge Intensive Computing for Healthcare Enterprises) Research Group conducts research in advancing knowledge technologies and developing innovative knowledge-intensive solutions, in particular for healthcare enterprises.
The NICHE group both promotes and pursues inter-disciplinary research whereby the group's investigations span from the abstract epistemological orientations of knowledge to the capture and representation of knowledge to practical operationalization of knowledge via intelligent systems.
Group Website: | http://niche.cs.dal.ca/ |
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Contact Information: | niche@cs.dal.ca Tel: 1-902-494-2129 Fax: 1-902-492-1517 |
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The wide spectrum of activities conducted in NICHE group falls in the realm of four inter-related research areas: NICHE researchers work across a cross-section of the above-mentioned themes, developing both novel knowledge-centric methods and applying these methods in knowledge-intensive tools. Currently, the researchers are working towards the development of a knowledge creation, morphing and sharing framework for capturing and operationalizing heterogeneous knowledge modalities present within an enterprise; the development and application of intelligent techniques to customize web-based services and information content as per a user-model; the formal computerization of healthcare knowledge artifacts to offer point-of-care decision support services; and the application of knowledge and data-driven intelligent systems to provide innovative healthcare services for both practitioners and patients. Details of individual projects can be found at the individual researcher's websites. Our research projects are largely funded by government agencies, private organizations and industry. |
Funding: | The NICHE projects have been funded by CANARIE, National Sciences and Engineering Research Council of Canada (NSERC), Canadian Foundation of Innovation (CFI), Nova Scotia Health Research Foundation (NSHRF), Green Shield Foundation Canada and Agfa Healthcare Canada. |
Faculty Members: | Dr. Raza Abidi |
MALNIS
Combining textual content and link information for describing, classifying, clustering and visualizing networked information spaces formed by large collections of documents are the focal tasks of the MALNIS lab. The core methodology involves the application of machine learning, graph theory and natural language processing to problems in networked information spaces, i.e. large document collections which have the form of a graph, where nodes are occupied by documents and links represent relations between documents (hyperlinks or citations). Specific research problems addressed include similarity and clustering based on both content and link information, low-dimensional representations of special text corpora based on knowledge resources such as Wikipedia and word, term and document embeddings, document summarization, and interactive visualization of document corpora to support high-recall interactive information retrieval and sense-making tasks for the subject matter expert. Networked information spaces of particular interest include the scientific and medical research literature, list servers of communities of experts, social media data streams, and grey literature. To address the computational requirements of these tasks, we have been using cloud computing resources provided by Compute Canada.
The MALNIS lab has active collaborations with the following universities:
University of São Paulo (Universidade de São Paulo), Sao Carlos, Brazil (Professors Maria Cristina Ferreira de Oliveira, Rosane Minghim, Alneu de Andrade Lopes)
Universidade Federal de São Paulo (UNIFESP) (Prof. Lilian Berton)
National University of the South (Universidad Nacional del Sur) & CONICET, Bahia Blanca, Argentina (Drs Ana Gabriela Maguitman and Axel Juan Soto)
Universidad Técnica Federico Santa María, Santiago, Chile (Prof. Marcelo Mendoza)
Students interested in doing a thesis with the MALNIS lab are encouraged to take as many of the following courses as possible as part of their course requirement towards their degree:
- CSCI 4152/6509: Natural Language Processing
- CSCI 6515: Machine Learning for Big Data
- CSCI 4155/6505: Machine Learning
- CSCI 6612: Visual Analytics
- CSCI 4146: Process of Data Science
- CSCI 4xxx: Deep Learning
- CSCI 4163/6610: Human-Computer Interaction
- CSCI 4166/6406: Visualization
Group Website: | https://projects.cs.dal.ca/malnis/ |
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Contact Information: | Dr. Evangelos Milios Email: eem@cs.dal.ca Phone: 902-494-7111 |
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Publications of the lab that provide details on current and recent research projects can be found on Google Scholar. Highlighted areas include:
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Funding: | Funded MALNIS projects The following projects all have openings with funding for eligible Master's and PhD students. You are encouraged to make a Skype appointment by email or simply drop in to discuss potential thesis topics. Our industrial partners offer employment opportunities to graduates of the MALNIS group.
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Ocean Data Analytics (ODA) Lab
The Ocean Data Analytics (ODA) Lab is a research group lead by Luis Torgo that is part of the Institute for Big Data Analytics at Dalhousie University.
The mission of this Lab is to use the power of Data Science to benefit the economic, environmental, regulatory, and social aspects of the Ocean.
Group Website: | https://web.cs.dal.ca/~ltorgo/ODA/ |
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Contact Information: | Dr. Luis Torgo ltorgo@dal.ca |
Research Areas |
We study these topics using a multitude of Machine Learning and Aritificial Intelligence methods |
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Who we are:
Raza Abidi

- Semantic web
- Health informatics
- Knowledge management
- Information personalization & intelligent systems
Vlado Keselj

- Text processing
- Natural language processing
- Data mining
- Computational number theory
- Programming languages
Stan Matwin

- Artificial intelligence
- Machine learning
- Data mining / Text mining and text analytics
- Big data
- Data privacy
Evangelos Milios

- Networked information spaces
- Machine learning
- Social network mining
- Digital libraries
Sageev Oore

- Machine learning
- Deep learning
- Computational creativity
- Deep learning models and tools for music, art & text generation
Thomas Trappenberg

- Computational neuroscience
- Machine learning
Dirk Arnold

- Evolutionary computation
- Optimization