Team

Roberto Souza - Assistant Professor, University of Calgary

Principal Investigator

Roberto Souza is a dual citizen from Brazil and the United States, working as an Assistant Professor at the Electrical and Software Engineering Department at the University of Calgary, Canada, since July 2020. He has a B.Sc. in Electrical Engineering from the Federal University of Pará (2012), an M.Sc. (2014) and PhD (2017), both in Computer Engineering from the University of Campinas (UNICAMP). Before becoming an Assistant Professor, Roberto worked for three years as a postdoctoral scholar in the Radiology Department at the University of Calgary. He has international experience, having worked as an intern at the Grenoble Institute of Technology, France, and the University of Pennsylvania, United States. Dr Souza has extensive expertise in image processing and machine learning. His research is currently focused on innovative strategies for data integration and data mining in imaging applications. Look at his Google Scholar page for a list of relevant publications. 

Mariana Bento - Assistant Professor, University of Calgary

Principal Investigator

Mariana is an Assistant Professor of Biomedical and of Electrical and Software Engineering, a full member of the Hotchkiss Brain Institute, funded by NSERC, who has expertise in medical image processing and machine learning applied to aging and dementia. Mariana has a B.Sc. in Teleinformatics Engineering from the Federal University of Ceará (2011), an M.Sc. (2013) and PhD (2016), both in Computer Engineering from the University of Campinas (UNICAMP). Before the current position, she served as a postdoctoral fellow at the Radiology and Clinical Neurosciences, University of Calgary.  She develops more robust and reliable open tools in neuroimaging and is engaged in open science activities and EDI activities, including conducting workshops. Look at her Google Scholar page for a list of relevant publications. 

Anik Das  – MSc Biomedical Engineering (University of Calgary)

Anik Das is a graduate student who is pursuing his MSc in Biomedical Engineering at the University of Calgary under the supervision of Dr. Mariana Pinheiro Bento. He completed his BSc and 1st MSc in Computer Science & Engineering. He has been studying and working with machine learning and deep learning since his bachelor program. Now, the area of his research is introducing ML and DL techniques to study medical images (e.g. brain MRI), considering data augmentation, domain adaptation and transfer learning.

Pedro Paiva – PDF, Biomedical Engineering (University of Calgary)

Pedro Paiva is a Postdoctoral fellow of AI2Lab and BTLab, working with bias mitigation strategies in medical AI and computer vision on Biometrics. Pedro has a B.Sc. in Computer Science from the Federal University of Alagoas (2016), an M.Sc. (2019), and a Ph.D. (2024), both in Information and Communication Systems from the University of Campinas (UNICAMP). Before becoming a PDF, Pedro was a visiting student at the University of Calgary at BTLab under the supervision of Dr. Marina Gavrilova and fully funded by the Brazilian Ministry of Education. He is interested in Computer Vision, Deep Learning, and AI Fairness. He was a researcher in the Cyber-Physical Division at the Renato Archer IT Center – Brazil. He also has experience as a Computer Vision engineer, working on a wide range of applications for several companies. Pedro was awarded by the Eyes High and Hotchkiss Brain Institute postdoctoral programs. Pedro has published several peer-reviewed papers in major journals and conferences. Look at his Google Scholar page for a list of relevant publications.

Mumu Aktar – PDF, Electrical and Software Engineering  (University of Calgary)

Mumu Aktar is a postdoctoral associate in the AI2 Lab at the University of Calgary, specializing in medical imaging and machine learning. She earned her B.Sc. (2014) and M.Sc. (2018) in Computer Science and Engineering from Rajshahi University of Engineering and Technology, Bangladesh. Mumu holds a Ph.D. (2023) in Computer Science from Concordia University, where she developed computer-aided systems for ischemic stroke treatment, specifically focusing on applying deep learning techniques.

With four years of teaching experience at Northern University Bangladesh and Rajshahi University of Engineering and Technology, Mumu Aktar brings a wealth of knowledge to her research. Her current work involves investigating domain adaptation techniques to translate fast synthetic brain MRI deep learning models trained on adult data to newborn infants.

Mumu's programming skills include Python and Matlab. For more details on her research and publications, you can visit her Google Scholar Page.

Amir Shamaei – PDF, Electrical and Software Engineering  (University of Calgary)

Amir Shamaei is a skilled medical signals analysis and reconstruction expert who specializes in applying deep learning and machine learning techniques. He holds a Ph.D. in medical signal analysis using deep learning from Brno University of Technology, where he received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant. Amir is a postdoctoral fellow at the prestigious Advanced Imaging and Artificial Intelligence Lab at the University of Calgary. In this role, he develops and implements novel autoDL reconstruction methods to improve MRI imaging. His research focuses on incorporating redundancies in MRI data, such as integrating past subject-specific information via deep learning models. Amir is also developing MRIntelligence, a software application that combines these innovations to reduce MRI examination times and expedite analysis. Previously, he gained extensive experience as a medical image and signals software developer at Czech Academy of Science, translating innovative research into practical solutions for medical diagnostics. Amir has published several peer-reviewed papers in major journals and conferences. His programming skills include Java, Python, C++, PyTorch, and MATLAB. Outside of work, Amir’s interests include artificial intelligence, history, Arduino, and reading nonfiction books. 

Kauê Tartarotti Nepomuceno Duarte – PDF, Biomedical Engineering (University of Calgary)

Kauê TN Duarte is a fellow member of the AI2Lab and Vascular Imaging Laboratory groups. He obtained his B.Sc. in Systems Analysis from the University of Campinas in 2014. In the same university, he earned his M.Sc. in System Informatics and Communication in 2017 and completed his Ph.D. in the same field in 2021. Throughout his career, KTND has focused on developing techniques for image segmentation, classification, and clustering across various domains. His primary objective is enhancing machine learning techniques to achieve generalizability and explainability. Google Scholar link (https://scholar.google.com/citations?user=Fr7gWkkAAAAJ&hl=en&oi=sra) 

Alexandre Lopes – PhD Student, Computer Science (University of Campinas)

Alexandre Lopes is a PhD Student at the University of Campinas under the supervision of Prof. Helio Pedrini (from the University of Campinas) and Prof. Roberto Souza (from the University of Calgary), and he is a part-time data scientist at Venturus, a Brazillian Inovation Institute.

Alexandre is currently a member of the Visual Informatics Laboratory (LIV) of the University of Campinas and Advanced Imaging And Artificial Intelligence Lab [(AI)**2] of the University of Calgary.

His main interest is on computer vision projects, and he is currently working with monocular depth estimation. He has previous experience with NLP, especially working with BERT-based models!

Mohammad Sahnoon – PhD Student, Electrical and Software Engineering (University of Calgary)

Mohammad Sahnoon is a PhD candidate at the Electrical and Software Engineering department at the University of Calgary and works under the supervision of Dr. Roberto Souza and Dr. Merkebe Demissie. He is a part of the NSERC-CREATE-IISC Group which is an interdisciplinary group with a focus on sustainable infrastructures funded by NSERC. Mohammad has a B.Sc. in Electrical and Electronics Engineering from University of Sharjah, UAE (2015) and an M.Sc. in Electrical Engineering with a focus on Machine Learning from the American University of Sharjah, UAE (2017). Mohammad’s research focuses on developing a machine learning technique to forecast the demand of shared on-demand mobility services to support the operational side of these emerging mobility services. His main research interests are in computer vision applications, target detection, and deep learning. 

Hanna Bugler  – MSc Biomedical Engineering (University of Calgary)

Hanna is a master’s student in Biomedical Engineering under the co-supervision of Dr. Ashley Harris and Dr. Roberto Medeiros de Souza. She completed her BEng in Biomedical and Electrical Engineering at Carleton University. Her research project seeks to analyzes, in real-time, the quality of magnetic resonance spectroscopy data to determine required minimum scan times. Her previous research experience includes developing pre-processing protocol and automating regions of interest selection for second harmonic generation collagen fiber microscopy images.

Farzaneh Dehghani – PhD Student, Biomedical Engineering (University of Calgary)

Farzaneh is a Ph.D. student in Biomedical Engineering at the University of Calgary, working under the supervision of Dr. Mariana Bento and Dr. Sayeh Bayat and funded by the HBI International Graduate Recruitment Scholarship. She received her MSc degree in Biomedical Engineering from the University of Isfahan, where she worked on the Bone Age Assessment of children in an automatic manner. Medical image processing, computer vision, deep/machine learning, and computer-aided diagnosis constitute her areas of interest. The objective of her research is to develop trustworthy machine learning algorithms for Alzheimer’s Disease and healthy aging.

Zeyad Khaled Samir – MSc Student, Biomedical Engineering (University of Calgary)

Zeyad is a master’s student in Biomedical Engineering under the supervision of Dr. Roberto Medeiros de Souza. He completed his BSc in Biomedical and Engineering at Cairo University. Zeyad is interested in computer vision research and its applications in healthcare. He previously worked on problems related to 3D scene understanding and object detection. His current research aims to use deep learning to develop fast brain MR image reconstruction techniques for infants. 

Yeganeh Bahari – MSc Student, Electrical and Software Engineering (University of Calgary)

Yeganeh is a master's student in the Electrical and Software Engineering program at the University of Calgary, working under the supervision of Dr. Roberto Souza. She completed her BSc in Physics, where she started to learn about AI and computational modeling, and received her first MSc degree in computer science, where she worked on self-supervised learning and image processing. Her research interest is in the area of computer vision, using AI techniques in healthcare and specifically medical imaging.  

Natalia Dubljevic – MSc Student, Biomedical Engineering (University of Calgary)

Natalia is a Biomedical Engineering master's student specializing in medical imaging at the University of Calgary under the co-supervision of Richard Frayne and Roberto de Souza. She received her BSc in Honours Physics from the University of British Columbia. Natalia is interested in research at the intersection of medical imaging and AI, and has previously worked on problems such as tumour segmentation and radiomics analysis. Her current project investigates the effect of MR coil configurations on deep learning MR image reconstruction. 

José Carlos Cazarin Filho  – MSc Electrical and Software Engineering (University of Calgary)

José is a master’s student in Electrical and Software Engineering program at the University of Calgary, working under the supervision of Dr. Roberto Souza. He received his B.Sc. degree in Electrical Engineering from the University of Campinas. He has worked in the industry of embedded systems since 2013, with experience in medical devices, localization systems and, more recently, machine learning and image processing in embedded devices. 

Mahsa Dibaji  – MSc Electrical and Software Engineering (University of Calgary)

Mahsa is a master's student in Electrical and Software Engineering program at the University of Calgary, working under the supervision of Dr. Mariana Bento. She received her B.Sc. in Computer Science from Amirkabir University of Technology, Tehran, Iran. She is interested in medical applications of machine learning and developing interpretable and fair models to address Equity, Diversity, and Inclusion in healthcare. Her research project aims to mitigate bias and ensure fairness in machine learning applications applied to Brain Magnetic Resonance Imaging. She currently holds an Alberta Graduate Excellence scholarship for international students.

Abbas Omidi  – MSc Electrical and Software Engineering (University of Calgary)

Abbas is a Software Engineering M.Sc. student at the University of Calgary, supervised by Dr. Roberto Souza. His interests are machine learning in general and deep learning in particular. He is working in the applied AI area and is curious about implementing practical AI-based solutions to real-world problems. He loves teaching, sharing his experiences, and volunteering. He currently holds the Alberta Graduate Excellence Scholarship (AGES) and is the Vice President External of the ESEG. You can keep in touch with him through his LinkedIn. 

Saad Ashraf – MSc Biomedical Engineering (University of Calgary)

Saad is a Biomedical Engineering Master’s student specializing in Medical Imaging, supervised by Dr. Mariana Bento. He completed his BSc in Computer Science and Engineering from the Islamic University of Technology, Dhaka, Bangladesh. As a Machine Learning Engineer in the industry, he worked on various computer vision applications such as Human Skeletal Modeling, Motion Recognition, Segmentation, Anomaly Detection. Currently, he is interested in applying image processing and computer vision skills in healthcare. His research aims at efficient brain MR imaging techniques for infants. Visit his LinkedIn profile to know more!

Mansi Singhal  – MSc Biomedical Engineering (University of Calgary)

Mansi Singhal is a graduate student in Biomedical Engineering at the University of Calgary, working under the supervision of Dr. Mariana Bento. She holds a B.Tech degree in Electrical Engineering from Dayalbagh Educational Institute, India (2024). She worked as a research intern in the MITACS Globalink Research Internship at the University of Calgary (2023) and in an international student exchange program at Hong Kong University (2022). She was awarded the Director's Gold Medal for Rank 1 in the Diploma in Electronics Engineering (2021). Her prior research focused on machine learning and image processing models for brain MRI and lung cancer detection. Currently, her research centers on responsible AI and fairness in AI applications for healthcare. Look at her Google Scholar Link for a list of relevant publications.

Brooke Kindleman – MSc Biomedical Engineering (University of Calgary)

Brooke Kindleman is a masters student in Biomedical Engineering at the University of Calgary under the supervision of Dr. Mariana Bento. She completed her B.Sc. in Software Engineering at the University of Calgary. During her undergraduate degree, she focused on computer graphics and modelling and found a passion for image rendering. Her primary interests are applications of AI and computer graphics in medical imaging to improve diagnostic outcomes for patients.

Arshin Soltan  – MSc Biomedical Engineering (University of Calgary)

Arshin received her B.Sc. in Biomedical Engineering from Amirkabir Universit of Technology, where she focused on medical image processing and analyzing brain imaging data in cases related to memory and cognition using AI algorithms. She is interested in working on processing Magnetic Resonance images by employing ML and DL techniques to study various features of the brain and how these techniques perform under specific challenges in image acquisition.

Poulami Basu  – MITACS Globalink Intern (University of Calgary)

Poulami is a research intern under the MITACS Globalink Research Internship program at the University of Calgary under Dr. Roberto Souza. She is a Bachelor's student in the Computer Science and Engineering program of Heritage Institute of Technology, India. She worked as a research intern at New Jersey Institute of Technology, USA (2023) by applying machine learning in traffic forecasting. She is interested in deep neural networks, graph algorithms, computer vision and natural language processing.  Her current research involves on-demand shared mobility services prediction with machine learning.  

Adrian Thereparambil – MITACS Globalink Intern (University of Calgary)

Adrian is a 2024 MITACS summer intern at the University of Calgary, working under the supervision of Dr. Roberto Souza. Originally from Mumbai, Adrian is a junior Computer Science (AIML) Engineering undergrad at A.P. Shah Institute of Technology. He possesses expertise in Deep Learning, Neural Networks, Computer Vision, and NLP, with a strong command of Python. Adrian has demonstrated leadership skills through roles such as Joint Cultural Secretary and President of the AIML Department at his home institute. Currently, he is involved in a project to develop an AI tool to analyze CT scan reports and detect nodules in breast cancer patients to identify potential cancerous cells spread to secondary regions such as the lungs. 

Aminreza Abbasi – Computer Science (University of Calgary)

Aminreza Abbasi is currently a dedicated Bachelor of Computer Science student at the University of Calgary, with a minor in Data Science. His research focus is on developing and implementing advanced deep learning models for brain age analysis using T1-Weighted MRI scans. Working under the supervision of Dr. Roberto Medeiros de Souza at the AI2Lab, Aminreza's work involves preparing and maintaining datasets to enhance model training and evaluation accuracy, implementing voxel-level age predictions to identify regions of premature aging, and comparing the accuracy and reliability of different model architectures. Aminreza brings a strong background in Python, Java, R, and several other programming languages, along with expertise in AI, ML and NLP. His commitment to AI research is complemented by his role as Vice President External of the Artificial Intelligence Club at the University of Calgary, Aminreza has also been recognized with awards like the PURE Award and the Alberta Innovates Summer Research Studentships, underlining his potential and dedication to his research.