Printable CV
Resume - Emran Ali | |
I am a Doctor of Philosophy (Ph.D.) candidate in Information Technology (IT) at Deakin University, Australia, in collaboration with Coventry University, United Kingdom. I am a research and development enthusiast in Data Analytics, Machine Learning, Interpretability and Optimisation. Experienced in: Machine Learning, Deep Learning, Health Informatics, Disease Prediction and (Physiological) Signal Processing.
- Ph.D.: IT@Deakin & CSM@Coventry University - (Ongoing)
- Master's: IT(Research)@Deakin
- Bachelor's: CSE@HSTU
- Scholarship (Ph.D.): DUPRS, Cotutelle (Deakin & Coventry)
- Fellowship (Master's): BSTF, Ministry of Sci.&Tech., Bangladesh
- Membership: ACS, IEEE, EMBS, DUSA, DAIS & DSEC
- Industry Involvement (Research): Alfred Health and AETMOS
- Teaching: HSTU & (Casual)@Deakin
- Software Development: Sr. Dev.@DROIDBD & AAPBD
- Projects: ICU Seizure Detection & Air Quality Prediction
- Email: emran.ali@research.deakin.edu.au
- Skype: wwm.emran
- Website: https//www.linkedin.com/in/wwmemran
- Website: https://wwm-emran.github.io
Recent works with: EEG Signal, EEG Channel Optimisation, Epilepsy, Sleep, Aging, Seizure Detection, ML Model Interpretability, Meteorological Data, Air Quality Prediction.
Research Area: Artificial Intelligence (AI) | Machine Learning (ML) | Deep Learning (DL) | Interpretability* | Health Informatics* | (Bio)Signal Processing | Medical Technology (MedTech) | EEG | Epilepsy | Sleep* | Aging* | Air Quality
Key Information
12 Years of teaching and research experience
3 Years of software development experience
5 Projects with research contribution
15 Publications related to research
5 Institutional involvement in academic and research
5 Industrial involvement in research and software development
4 Research collaboration with institutes and industries
20 Specialisation Certificates for courses and training
Education
Professional Experiences
Research Experiences
Teaching Experiences
Training Experiences
Industrial (Software Development) Experiences
Expertise, Skills and Achievements
All the expertise, skills and achievements from study and professional careers.
| Area | Subjects | Expertise Level |
| Programming | Python, Java, Swift, Objective-C, C, C++, C#, SQL, PHP, R | 100% |
| Datascience | Data Collection, Cleaning, Preprocessing, EDA, Analysis, Feature Engineering, Numpy, Pandas, Matplotlib | 90% |
| Machine Learning | Concept and Application, Scikit-learn, Auto-ML | 90% |
| Deep Learning | Concept and Application, Pytorch, Tensorflow, Keras | 85% |
| Health Informatics and Signal Processing | Disorder detection, Epilepsy, Sleep disorders, EEG | 85% |
| Could Platforms | AWS, AWS Sagemaker, MS Azure, Azure ML Designer | 85% |
| Teaching and Training | Demonstration, Communication, Supervision | 100% |
| Reporting and Presentation | LaTeX, MS Word, MS Excel, MS PowerPoint, Illustrator | 90% |
| Management and Leadership | Project Management, Team Lead, Client Management | 90% |
| Soft Skills | Critical Thinking, Problem Solving, Communication, Collaboration | 90% |
AWS AI/ML Scholarships (Phase 1 and 2) for 2 Udacity nanodegrees worth more than $8,000
Joint Ph.D. Program & Funding (During study period at Coventry University) - CSM, Coventry University · (Ongoing)
Joint Ph.D. Program & Funding (During study period at Deakin University) - DUPR, Deakin University · (Ongoing)
Annual School Conference - School of IT, Deakin University · Dec 2021
Fully funded fellowship for higher education - BSTF Trust, Ministry of Science and Technology, Bangladesh · Feb 2020
Best employee of year 2014 - Advanced Apps Bangladesh (AAPBD) Ltd., Bangladesh · Jul 2014
Post-graduation Entrance Exam - South Asian University (SAU), New Dehli, India · Apr 2013
First Place from the undergrad batch - HSTU, Bangladesh · Mar 2012
Intra-University Programming Contest (InUPC) Champion - HSTU, Bangladesh · Feb 2009
| Subject | Description |
| Bertelsmann Udacity - Foundation of Generative AI (Nanodegree) | Bertelsmann Udacity - Foundation of Generative AI (Nanodegree). Funded by Bertelsmann Next Generation Tech Booster Scholarship 2024 (Phase 1 - Winter 2024). Among a few chosen students from a challenge entrance test. Wroth more than $1,500. 9 weeks duration, 2 online courses, regular community sessions. Knowledge gained: Machine Learning (ML), Deep Learning (DL), Generative AI (GenAI), Large Language Model (LLM), Deep Learning, Autoencoder, Transfer Learning, Retrieval-Augmented Generation (RAG), Prompt Design, PyTorch and Hugging Face. |
| AWS Udacity - AI Programming with Python (Nanodegree) | AI Programming with Python (Nanodegree by Udacity). Funded by AWS AI/ML Scholarship (Phase 1 - Winter 2023). Among chosen 2,000 students from "AWS Deep Racer" challenge. Wroth $4,000. 5 months duration, 6 online courses, weekly connect sessions. Knowledge gained: Python programming, Machine Learning (ML), Deep Learning (DL); different data manipulation, visualisation, ML and DL libraries; Pytorch package for transformer and custom DL models. 2 computer vision projects with DL. |
| AWS Udacity - AWS Machine Learning Fundamentals (Nanodegree) | AWS Machine Learning Fundamentals (Nanodegree by Udacity). Funded by AWS AI/ML Scholarship (Phase 2 - Summer 2024). Among chosen 500 students from Scholarship Phase 1. Wroth more than $4,000. 5 months duration, 4 online courses, weekly connect sessions. Knowledge gained: Machine Learning (ML), Deep Learning (DL), Convolutional Neural Network (CNN), ML Workflow with AWS (preprocessing to deployment automation), and related optimisation techniques using AWS cloud platform. 4 projects with ML, DL and AWS cloud platform. |
| Microsoft - Microsoft Certified: Azure AI Fundamental (AI900) | Offered by Akkodis (Microsoft Skills and Certification Bootcamp 2024). 2 weeks training + certificate exam voucher. Microsoft Azure, Azure cloud platform, Azure AI, Applid ML, Generative and responsible AI. |
| Microsoft - Microsoft Certified: Azure Data Fundamental (DP900) | Offered by Akkodis (Microsoft Skills and Certification Bootcamp). Extra certificate exam voucher from Microsoft Skills and Certification Bootcamp 2024 for best performers. Microsoft Azure, Database Management, Azure Database, SQL, Microsoft SQL, Azure data storage. |
| g·tec - BCI & Neurotechnology Spring School 2022 | g·tec Neurotechnology Spring School 2022. 10 days, 130 hours, 12 credits. Academic and industrial topics. Healthcare, Games, VR, Sports, Entertainment, Production, Education & Research industries. |
| IEEE EMBS - Summer Camp 2022 | IEEE EMBS - Summer Camp 2022. EMBS Students Activities Committee. 8 days, 24 hours. Recent and trending researches. Healthcare, Sports, Production industries related researches. |
| LinkedIn Learning - Develop Critical-Thinking, Decision-Making, and Problem-Solving Skills | LinkedIn Learning. Self-placed learning path. 7 courses in the learning path. Total approximately 9 hours of learning. Section and course wise test. |
| ATN Frontiers - Digital Futures: Data Analytics Advanced and Applied | Webinars, self-study materials, practice tasks, and collaborative teamwork. Learn to use Structural Query Language (SQL) to extract, organise and summarise data. Learn the basics of regular expression (regex) to extract and filter relevant textual data. |
| ATN Frontiers - The Future of Data - Data Analytics: Concepts, Principles and Practice | Concepts, Drivers & Trends: Defining key ideas and principles relating to data, analytics and modelling. Privacy, Security, Ethics. Responsible Data Management. From Question to Data to Insights. Data Analytics Toolkit: Introducing principles, aids and insights for coding and analytics by syntax. Start to Code: Overview and hands-on Python, markdown, Jupyter Notebooks and Kaggle. Explore, Describe, Visualise: Convert and communicate data through graphic representation. Tests, Models, Predict: Demonstrating basic analytical computations using the Analytics Toolkit. |
| Kaggle - Intermediate Machine Learning | Offered by Kaggle. 14 hours, 7 Lessons. Lessons + hands on practice test. Intermediate level knowledge of ML: data preparation, cross validation, XGBoost, data leackage. |
| Section Leader - Code in Place 2023 | Offered by Standford University (online). 6 weeks, 1.5 hours session per week. Instructed student to help learning Python. Teaching a variety of students from diverse background. |
| AppsBroker Academy - Google Cloud Fundamentals: Core Intrastructures | Google Cloud Fundamentals. Google Cloud Infrastructures. Google Cloud IaaS. Part-wise test. |
Project: A MACHINE LEARNING BASED ANALYSIS OF SLEEP PATTERNS IN AGING USING PHYSIOLOGICAL SIGNALS.
Funding: Centre for Computational Science and Mathematical Modelling - Modelling (CSM), Coventry University, United Kingdom. (Jan. 2023 - Ongoing).
Project: Air Quality Prediction (Temperature Prediction) for Indoor Environments in Different Cities of Australia.
Funding: An MAAP linkage project funded by the Australian Research Council (ARC). (Mar. 2022 - Dec. 2022).
Project: Channel minimisation and epileptic seizure detection using single channels using Deep Learning from continuous iEEG of ICU patients.
Funding: A voluntary collaboration of Deakin University, Monash University and Alfred Health. (Apr. 2020 - Mar. 2022) - (Paused).
Project: DESIGNING A 3-LAYER NETWORK SECURITY TECHNIQUE IN SERVERS FOR PREVENTION OF DDOS ATTACK.
Funding: Institute of Research and Technology (IRT), HSTU. (Jul. 2018 - Jun. 2019).
Project: ANALYSIS AND DESIGN OF A NON-INVASIVE WAY OF MEASURING AND MONITORING BLOOD-SODIUM CONCENTRATION LEVEL USING NEAR-INFRARED SPECTROSCOPY.
Funding: Institute of Research and Technology (IRT), HSTU. (Jul. 2018 - Jun. 2019).
Associate Member, Australian Computer Society · Aug. 2023 - Dec. 2024
Deakin University Student Association Member - Deakin University · Apr. 2020 - Dec. 2023
Deakin University Software Engineering Club Member - Deakin University · Jan. 2023 - Dec. 2023
Deakin AI Society Member - Deakin University · Jan. 2023 - Dec. 2023
IEEE Student Member - IEEE · Jan. 2022 - Present
IEEE Engineering in Medicine and Biology Society (EMBS) Student Member - IEEE · Jan. 2022 - Dec. 2023
IEEE Young Professionals - IEEE · Jan. 2022 - Dec. 2023
Programmers Arena - HSTU · Sep. 2014 - Present
CSE Club - HSTU · Sep. 2014 - Present
Keynote Speaker, A seminar on career development and future of Mobile Application Development in Bangladesh, Organized by AFCSE, HSTU on Apr. 2015
Speaker, A seminar on Higher Studies in Abroad - Journey to Australia and Research Experiences, Organized by CSE Club, HSTU on Sepember. 2022
Mother tongue · Excellent LRWS skills.
Medium of instruction at HSTU and Deakin University · IELTS (6.5) - LRWS (6.0,6.5,6.5,7.0) - 2019.
Beginner level self learner.
A fully python based library to download the contents from a web directory including subdirectories and files.
A python and Matlab based library to do feature extraction and feature engineering related task for Machine Learning.
A python Machine Learning and Deep Learning repository containing all the projects completed in AWS AI/ML Scholarship (Phase 1 and 2) programs. It contains total 6 projects from 2 Udacity nanodegree.
Teaching and training the students Python programming · Stanford Online · Apr 2023 - Apr 2024
Scientific journal articles review · European Alliance of Medical and Biological Engineering and Science (EAMBES) · Aug 2023 - Present
Publications
All the publications (reports and articles) in journal, conference, poster, symposium, blog, etc.
Journals |
Epileptic seizure detection using CHB-MIT dataset: The overlooked perspectives
Ali E, Angelova M, Karmakar C. Epileptic seizure detection using CHB-MIT dataset: The overlooked perspectives. Royal Society Open Science (RSOS). 2024 May;11(6):230601.
DOI/Link: 10.1098/rsos.230601 |
Sensor-based indoor air temperature prediction using deep ensemble machine learning: An Australian urban environment case study
Yu W, Nakisa B, Ali E, Loke SW, Stevanovic S, Guo Y. Sensor-based indoor air temperature prediction using deep ensemble machine learning: An Australian urban environment case study. Urban Climate. 2023 Sep 1;51:101599.
DOI/Link: 10.1016/j.uclim.2023.101599 |
A LSB Based Image Steganography Using Random Pixel and Bit Selection for High Payload
Ehsan Ali UA, Ali E, Sohrawordi M, Sultan MN. A LSB based image steganography using random pixel and bit selection for high payload. International Journal of Mathematical Sciences and Computing (IJMSC). 2021 Aug 8;7(3):24-31.
DOI/Link: 10.5815/ijmsc.2021.03.03 |
Enhancement of single-handed Bengali sign language recognition based on HOG features
Tabassum T, Mahmud I, Uddin MD, Emran Ali, Afjal MI, Nitu AM. Enhancement of single-handed bengali sign language recognition based on hog features. Journal of Theoretical and Applied Information Technology (IJTAIT). 2020 Mar;98(5):743-756.
DOI/Link: http://www.jatit.org/ |
Mapping Character Position Based Cryptographic algorithm with Numerical Conversions
Moon M, Tanim AT, Shoykot MZ, Sultan MN, Ali UM, Ali E. Mapping character position based cryptographic algorithm with numerical conversions. International Journal of Computer Science and Software Engineering (IJCSSE). 2020 Mar 1;9(3):56-9.
DOI/Link: https://ijcsse.org/ |
Pseudo random ternary sequence and its autocorrelation property over finite field
Ali MA, Ali E, Habib MA, Nadim M, Kusaka T, Nogami Y. Pseudo random ternary sequence and its autocorrelation property over finite field. International Journal of Computer Network and Information Security (IJCNIS). 2017 Sep 1;11(9):54.
DOI/Link: 10.5815/ijcnis.2017.09.07 |
Smart Campus Using IoT with Bangladesh Perspective: A Possibility and Limitation
Sultan MN, Ali E, Ali MA, Nadim M, Habib MA. Smart campus using IoT with Bangladesh perspective: A possibility and limitation. International Journal of Research in Applied Science and Engineering Technologies (IJASET). 2017 Aug;8:1681-90.
DOI/Link: 10.22214/IJRASET.2017.8239 |
Study of Abstractive Text Summarization Techniques
Yeasmin S, Tumpa PB, Nitu AM, Uddin MP, Ali E, Afjal MI. Study of abstractive text summarization techniques. American Journal of Engineering Research (AJER). 2017;6(8):253-60.
DOI/Link: https://www.ajer.org/ |
Conferences |
An Efficient Feature Optimization Approach with Machine Learning for Detection of Major Depressive Disorder Using EEG Signal
Bhuyain AR, Ferdouse J, Babar MU, Sohrawordi M, Islam MR, Ali E. An Efficient Feature Optimization Approach with Machine Learning for Detection of Major Depressive Disorder Using EEG Signal. In 2023; 26th International Conference on Computer and Information Technology (ICCIT) 2023 Dec 13 (pp. 1-6). IEEE.
|
Optimal Feature Identification and Major Depressive Disorder Prediction through Correlation-Based Machine Learning Approach
Babar MU, Bhuyain AR, Ferdouse J, Sohrawordi M, Ali E. Optimal Feature Identification and Major Depressive Disorder Prediction through Correlation-Based Machine Learning Approach. In 2023; 6th International Conference on Electrical Information and Communication Technology (EICT) 2023 Dec 7 (pp. 1-5). IEEE.
|
Performance Analysis of Entropy Methods in Detecting Epileptic Seizure from Surface Electroencephalograms
Ali E, Udhayakumar RK, Angelova M, Karmakar C. Performance analysis of entropy methods in detecting epileptic seizure from surface electroencephalograms. In 2021; 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) 2021 Nov 1 (pp. 1082-1085). IEEE.
DOI/Link: 10.1109/EMBC46164.2021.9629538 |
Efficient Noise Reduction and HOG Feature Extraction for Sign Language Recognition
Mahmud I, Tabassum T, Uddin MP, Ali E, Nitu AM, Afjal MI. Efficient noise reduction and HOG feature extraction for sign language recognition. In2018 International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE) 2018 Nov 22 (pp. 1-4). IEEE.
DOI/Link: 10.1109/ICAEEE.2018.8642983 |
Indexed Binary Search based efficient search generator for J2ME English to English dictionary
Uddin MP, Ali E, Marjan MA, Al Mamun MA. Indexed Binary Search based efficient search generator for J2ME English to English dictionary. In2014 International Conference on Informatics, Electronics & Vision (ICIEV) 2014 May 23 (pp. 1-6). IEEE.
DOI/Link: 10.1109/ICIEV.2014.6850692 |
Posters |
Deep Learning Model for Detection of Electrographic Seizures from continuous EEG in ICU patients
Habib A, Pham C, Udhayakumar R, Ali E, Thom D, Laing J, Karmakar C, Kwan P, O'Brien T. Deep Learning Model for Detection of Electrographic Seizures from continuous EEG in ICU patients. American Epilepsy Society (AES) Annual Conference 2021, Categories : Neurophysiology, Submission Category: 3. Neurophysiology / 3G. Computational Analysis & Modeling of EEG, Submission ID: 1886502, 22 Nov 2021.
|
Contacts
Please feel free to reach out to me.
