Director: Bigdata Analytics and Management Laboratory
Farhana H. Zulkernine, PhD, PEng
Farhana Zulkernine is an Associate Professor and the Coordinator of the Cognitive Science program at the School of Computing at Queen's University. She is the Director of the BAM laboratory. She holds a Ph.D. degree from the School of Computing at Queen's University and is a member of Professional Engineers of Ontario. She has more than 15 years of international work experience in three continents in software design, analysis and research. BAM lab focuses on developing efficient multimodal big and streaming data ingestion, analytics, knowledge extraction and management infrastructure for real life applications in many areas such as Business, Law, Medical, and Autonomous Vehicles.
Current Students and Postdoctoral Fellows:
Graduate Students
| Name | Period | Topic |
|---|---|---|
| Drishti Sharma (MSc project) | Jan 2023- | Developing a dialogue system for a chat bot for medical triage system. |
| Jackson Cai(MSc) | Jan 2023- | Analysis of medical structured and unstructured data for disease analysis and prediction. |
| Zihan Zhang (MSc) | Jan 2023- | Analyzing radar point cloud data and video data for human activity recognition. |
| Elyas Rashno (PhD) | Sep 2022- | Multimodal streaming data management and analysis for Triage-bot. |
| Nafiz Sadman (MSc) | Sep 2022- | Security and authentication of user data for Triage-bot. |
| Vidhi Kokel (MEng) | May 2022-Jan 2023 | Analysis of medical structured and unstructured data for a study on Osteoarthritis funded by Pfizer |
| Yuhao Chen (PhD) | Sep 2021- | Using deep learning for knowledge extraction from unstructure text data. |
| Ruikang Luo (MSc) | Sep 2021- | Automatic caption generation using multimodal video and text data (co-supervised) |
| Ian Pepin (MSc) | Sep 2021- | Security and privacy for medical informatics on the cloud (co-supervised) |
| Jacqueline Chan (MSc) | Sep 2021- | Authentication and password based security |
| Sam Baranek (MSc) | Sep 2021- | Facial image analytics for identity verification and emotion recognition (co-supervised) |
| Haoran Qi (MS Project) | Sep 2021- | Human activity recognition using wearable sensors. |
| Vignesh Rao (MS Project) | Sep 2021- | Autonomous Vehicular Sensor Data Analytics (co-supervised) |
| Mojtaba Moattari (PhD) | Sep 2020- | Advancing machine cognition using multimodal asynchronous data stream processing and concept learning. |
| Ahmed Harby (PhD) | Sep 2020- | Distributed cloud-based knowledge graph architecture, management and querying. |
| Zili Lou (MS) | Sep 2020- | Email categorization and automatic email response composition. |
| Calen Irwin (MS) | Sep 2020- | Vehicular sensor data classification for anomaly detection. |
| Austin Carthy (MSc) | Sep 2021- | Detecting cyber threats in emails. |
| Donghao Qiao (PhD) | Sep 2019- | Pattern learning from video data for autonomous vehicles. |
| Sazia Mahfuz (PhD) | Sep 2017- | A smart data profiling framework |
Drishti Sharma
Jackson Cai
Zihan Zhang
Elyas Rashno
Nafiz Sadman
Vidhi Kokel
Yuhao Chen
Ruikang Luo
Austin Carthy
Ian Pepin
Jacqueline Chan
Sam Baraneko
Haoran Qi
Vignesh Rao
Mojtaba Moattari
Ahmed Harby
Zili Lou
Calen Irwin
Donghao Qiao
Sazia Mahfuz
Undergraduate Students
| Name | Period | Topic |
|---|---|---|
| Josh Otten | 2022-2023 | Face recognition and advanced feature extraction from video data. |
| Jing Tao | 2022-2023 | Medical data analytics with advanced annotation tools. |
| Somiona Tian | 2022-2023 | Medical data analytics with advanced annotation tools. |
| Wanqing Li | 2022-2023 | Emotion detection from video data |
| Feiting Yang | 2022-2023 | Noise reduction from rPPG data for face video based vital sign measurement |
| Yuzhe He | 2022-2023 | Prediction of blood glucose level using rPPG from face video |
| Max Beninger | 2023-2023 | Deep learning based vital sign prediction using face video with rPPG method |
| Baorong Wei | 2022-2023 | Speech and text based emotion detection |
| Asher Song | 2022-2023 | Streaming big data ingestion and storage in a data lake with metadata processing |
| Steven Wen | 2022-2023 | Streaming IoT data ingestion pipeline for an advanced data lakehouse |
| Ronan Almeida | 2022-2023 | Developing an end-to-end pipeline for a Triage-Bot to enable voice-video based medical triage service |
| Eyad El Khodary | 2022-2023 | Developing the server end storage and query management system for a web application providing medical Triage-bot |
| Griffin Clark | 2022-2023 | A point-cloud based collaborative perception for autonomous vehicles from an infrastructure point of view |
Joshua Otten
Jing Tao
Somiona Tian
Wanqing Li
Feiting Yang
Yuzhe He
Max Beninger
Baorong Wei
Asher Song
Steven Wen
Ronan Almeida
Eyad El Khodary
Griffin Clark
Past Researchers/Postdoctoral Fellows:
| Name | Period | Funding | Project Title |
|---|---|---|---|
| Hasan Zafari | Dec 2018-Jan 2022 | Mitacs, CIMVHR, IBM, Pfizer | Using Advanced Analytics to Understand PTSD (UAAUP) |
| Haruna Isah | Nov 2017-Dec 2019 | SOSCIP, Gnowit and IBM | A Multilevel Streaming Data Analytics Infrastructure for Predictive Analytics |
Past Students:
Graduate Students
| Name | Period | Topic |
|---|---|---|
| Martin Woo (MSc) | Sep 2020-2022 | Hierarchical clustering of data patterns from streaming IoT sensors for human activity recognition. |
| Amtul Haq Ayesha (MS) | Sep 2020-2022 | Video and sensor based biometric data measurement using AI techniques. |
| Karen Batch (MSc) | Sep 2019-2022 | Annotated radiology text reports analytics for studying cancer metastasis. (co-supervised). |
| Yuhao Chen (MSc) | Sep 2019-2021 | A Three-phase Intelligent Question answering system. |
| Isaac Hogan (MSc) | Sep 2019-2021 | Activity recognition from skeleton video data. (co-supervised) |
| Prithila Angkan (MEng) | 2019-2020 | Human activity recognition using video of skeleton data. |
| Zunayed Mahmud (MEng) | Summer 2020 | Object recognition and reidentification to advance multi-object tracking for autonomous vehicles. |
| Junaid Charaniya (MEng) | 2019-2020 | Clustering streaming IoT human activity data from sensor devices. |
| Mohammed Hamadah Gasmallah (MSc) | 2018- 2020 | An Analysis of Motion Smoothness in Video Object Detection (co-supervised) |
| Jason Lam (MSc) | 2018- 2020 | Deep Learning for Legal and Medical Text Analytics |
| Ftoon Kedwan (PhD) | 2017- 2019 | A hybrid knowledge management doctoral student framework (co-supervised) (incomplete) |
| Tariq Abughofa | 2016 - 2018 | Dynamic graph processing with streaming data |
| Chanderdhar Sharma (MSc Project) | 2017 - 2018 | Unstructured text mining and topic modeling |
| Niventhini Indrajith (MSc Project) | 2017 - 2018 | Text mining for disease diagnostic. |
| Mandeep Kandhari (MEng) | 2017 - 2018 | An intelligent human-machine voice interaction system. |
| Dharmitha Ajerla (MSc Project) | 2017 - 2018 | An edge computing framework for fall detection using wearable sensor devices. |
| Dev Shah (MSc Project) | 2017 - 2018 | Stock market prediction |
| Hadeel Alghamdi (MSc Project) | 2015 - 2017 | Distributed DBMS in WINGS workflow management system (co-supervised) |
| Kireet Bhat (MSc Project) | 2016 - 2017 | Extending Spark for cloud-based big data analytics |
| Tarek Ahmed (PhD) | 2016 - 2016 | Proactive autoscaling of resources for steam processing engines in the cloud (co-supervised) (incomplete) |
| Azadeh Eftekhari (MSc) | 2013 - 2016 | Binary: A framework for Big data Integration for ad-hoc Querying (co-supervised) |
| Mastoureh Hasanezhad (MSc) | 2012 - 2014 | Managing long-running queries using query progress (co-supervised) |
| Rizwan Mian (PhD) | 2012 - 2014 | Smart Spending: Determining cost-effective resource configurations for executing data-intensive workloads in public clouds (co-supervised) |
Undergraduate Students
| Name | Period | Topic |
|---|---|---|
| Anshul Pattoo | 2021-2022 | Breast cancer detection using image data. |
| Zihan Zhang | 2021-2022 | 3D Object Detection. |
| Xinyue Li | 2021-2022 | Optimizing artificial neural networks for multistream data processing for machine cognition. |
| Boqun Shu | 2021-2022 | Understanding pain levels from unstructured text data in EMR. |
| Aleksandar Ivanovic | 2021-2022 | Anomaly detection from autonomous metrorail unlabeled sensor data. |
| Tingye Chen | 2021-2022 | Human Activity Recognition from video data using 2D-3D conversion. |
| Kaiyun Guo | 2021-2022 | Human Activity Recognition from real time video data using video camera. |
| Siyu Chen | 2021-2022 | Speech recognition for assistive technology. |
| Hongli Zeng | 2021-2022 | Speech recognition for assistive technology. |
| Jackson Cai | 2021-2022 | A streaming cloud IOT data ingestion and analytics framework for human activity recognition. |
| Muyun Yang | 2021-2022 | Creating Human Activity data using Unity to train a human activity recognition model |
| James Wang | 2021-2022 | Using Unity to create HAR dataset for video based human activity recogntion. |
| Katherine Mattatall | 2021-2022 | Unity project for HAR data generation and analytics. |
| Simin Zhang | 2020-2021 | A streaming cloud IOT data ingestion and analytics framework for human activity recognition. |
| Tao Ma | 2020-2021 | Chat text summarization for online medical support services. |
| Yuelin Huang | 2020-2021 | Chat text summarization for online medical support services. |
| Jacky Li | 2020-2021 | Driver drowsiness detection for autonomous vehicles. |
| Ruikang Luo | 2020-2021 | Detection of fire events in video or image data. |
| Jie Li | 2020-2021 | Predicting Diabetes risk levels from Electronic Medical Records (EMR). |
| Liam Fiebig | 2020-2021 | Distributed cloud-based IoT data management. |
| Gary Guo | 2020-2021 | A study of social behaviour and visualization through cloud platforms. |
| Kevin Rush | 2020-2021 | A study of social behaviour and visualization through cloud platforms. |
| Yifei Yin | 2019-2020 | Detecting Employee Type from Legal Cases using Deep Learning to Analyze Unstructured Text Data. |
| Liam Tharp (Engg-Phys) | Sep 2019 (1 year) | Hospital Surge Prediction from Near Real Time Data Feed (partner KFLA Public Health) |
| Brendan Kolisnic (CISC) | 2019-2020 | Image Object Detection and Classification (industry partner AIdeal) |
| Zili Lou (CISC) | 2019-2020 | Email classification and Generating Autoreply |
| Zhaoyu Yin (CISC) | 2019-2020 | Driver Fatigue Detection for Autonomous Vehicle Paradigm |
| Chuyan Zheng (CISC) | 2019-2020 | Human Face Recognition using Deep Learning for Real Time Conversation |
| Lixian Su (COGS) | 2019-2020 | Video Object Segmentation using an Attentive Deep Learning Model |
| Ryan Kishenbaum (CISC) | 2019-2020 | Detecting Disease Progression from Electronic Medical Records using Sequential Pattern Recognition Techniques |
| Sara Langlois (CISC) | 2019-2020 | Diagnosing Chronic Obstructive Pulmonary Disease (COPD) from Electronic Medical Records using Machine Learning Models |
| Ethan Peters (CISC) | 2019-2020 | Recognizing Food Items using Deep Learning |
| Martin Woo (CISC) | 2019-2020 | Hierarchical Pattern Learning using Machine Learning |
| Yinchen Shi (CISC) | 2019-2020 | Developing an Adapter for Apache Spark Streaming and IBM Streams |
| Harsh Patel (Mitacs Globalink) | Summer 2019 | Video based human activity recognition. |
| Yu Liu (Mitacs Globalink) | Summer 2019 | Clustering streaming IoT data to extract patterns. |
| Hongkai Chen (CISC) | 2018-2019 | Recognizing patterns from streaming IoT data |
| Isaac Hogan | Winter 2019 | Image Component Separation in Image Super-Resolution. |
| Yuhao Chen | Winter 2019 | Intelligent Interactive Robotic System. |
| Chantal Montgomery | Winter 2019 | Design and Implementation of a Natural Language Customer Query Platform. |
| Grace (Shihao) Ge | Winter 2019 | Design and Implementation of a Scalable and In-memory Data Stream Analytics Pipeline. |
| Kennedy Raltson | Winter 2019 | Creating an Intelligent, Multilingual System with IBM Watson. |
| Karen Batch | Winter 2019 | Modeling of animal learning. |
| Mitchell Skarupa | Winter 2019 | Edge Computing for Wearable Sensors. |
| Alex Wojaczek | Winter 2018 | Data mining and deep learning models for analyzing unstructured medical text data. |
| Ruoran Liuk | Winter 2018 | Design and Implementation of a Data Lake. |
| Marwa Chermiti (Mitacs Globalink) | Summer 2018 | Data mining and deep learning models for analyzing unstructured medical text data. |
| Lucas Rychlo | Winter 2018 | Lab reporting to public health Ontario: A cognitive computing approach. |
| Brayden Dewar | Winter 2018 | Data cleaning and correction using machine learning techniques. |
| Alex Weatherhead | Winter 2018 | Designing autonomous vehicles using optical object recognition. |
| Daisy Barrette | Winter 2018 | Training autonomous vehicles using machine learning approach with sensor data. |
| Michael Petkov | Winter 2018 | Image object recognition using enhanced resolution. |
| Mohammad Gasmallah | Winter 2018 | Video object recognition using deep learning models. |
| Paul Briggs | 2017-2018 | Using machine learning to predict enemy attacks in computer games. |
| Michael Judd | Winter 2018 | Medical text data analytics using NLP and text mining techniques for classification of lower back pain. |
| Alexandra Poole | Winter 2017 | Studying the symptoms of dyslexic patients with a view to building an automatic diagnostic tool. |
| Tiffany Leung | Winter 2017 | Exploring the applications of virtual reality to improve the quality of education. |
| Sacha Lansky | Winter 2017 | Studying the use of bitcoins and blockchains in enabling secure communication in multi-agent systems. |
| Jonathan Creighton | Winter 2017 | Developing a hybrid neural network model for stock market prediction |
| Matthew Sherar | 2016-2017 | Implementing a particle swarm optimization algorithm in Apache Spark for clustering big unstructured text data. |
| Hugo Goncalves | Summer 2016 | An ANN model for categorization and selection of music |
| Travis Rhee | Winter 2016 | An ANN model for predicting box office success using movie and social media data analytics |
| Arwin Chan | Winter 2016 | Creating building design forms using evolutionary computing |
| Dan Lefreniere | Winter 2016 | Predicting hypertension using ANN |
| Conor Fitzpatrick | Winter 2015 | Visual Perception and Attention for Game Development |
| Catherine Aylward | Winter 2015 | Study of cognitive models for Dyslexia |
| Sam Yeon | Winter 2015 | Developing a hybrid neural network model for stock market prediction |
| Mark Simon | Winter 2012 | Implementing CAPRI on Amazon Cloud using a Map-Reduce Framework |
Highschool Interns
| Name | Date Started | Topic Information |
|---|---|---|
| Morgan Gallant (Worked with us twoice) | Summer 2018, 2017 | Query extension for natural language query processing. |
| Kendra Denhart | Summer 2016 | Getting user preference for generating architectural design using evolutionary technique. |