Future of Educational Innovation-Workshop series

Data in Action: Digital Ecosystem and Emerging Tools for Education (Hybrid)

16 – 18 January, 2023
Monterrey, Mexico

In Partnership with

IEEE-Logo-1

Program Overview:

The 2023 version of the Future of Educational Innovation-Workshop series is dedicated to training participants in identifying, extracting, handling, and analyzing the internationally available databases as invaluable resources accessible by researchers of diverse expertise. In this hands-on event, we benefit from the knowledge of our distinguished guests to provide attendees with a set of skills and tools which would result in conducting cutting-edge research and analysis.

Data in Action: Digital Ecosystem and Emerging Tools for Education aims at presenting current research to expand our understanding of the technological tools and the methods they can be leveraged to generate impact on educational processes. The focus of this workshop is highlighting how researchers in the fields of Education are innovating and examining the digital ecosystem to study pedagogical approaches and ideas. We would like to present how technology may help researchers better understand educational phenomena from a perspective of data Sciences. By bringing together researchers with unique perspectives in these fields, we hope to provide a space for presenters to share innovative ideas and perspectives that are shaping the future of Education and discuss how educational practices are being shaped by new research paradigms.

Program

Day 1
16th January 2023

  • Lobby (09:00 am)
  • Opening statement (09:30 am)
  • Lectures (10:00 am – 01:00 pm)
    Covered topics:
    Internationally Available Databases
    Web Scrapping and Extraction
    Data Science Engineering
    Data Cleaning and Processing
  • Lunch break (01:00pm – 03:00 pm)
  • Presentations of research papers
    (03:00 pm – 05:00 pm)

    3 parallel tracks – 8 papers on each track
    Track 1 chaired by Prof. Claudia Bautista
    Track 2 chaired by Dr. Asad Abbas
    Track 3 chaired by Dr. Nora León-Real

Day 2
17th January 2023

  • Lobby (09:00 am)
  • Opening statement (09:30 am)
  • Lectures (10:00 am – 01:00 pm)
    Covered topics:
    IData Handling (e.g. Panda data framework)
    Data Synthesis and Analysis
    Conveying a Higher Meaning from the Data
    Communication and Visualization (e.g. matplotlib, VosViewer or bokeh)
  • Lunch break (01:00pm – 03:00 pm)
  • Presentations of research papers
    (03:00 pm – 05:00 pm)

    3 parallel tracks – 8 papers on each track
    Track 1 chaired by Dr. Kingsley Okoye
    Track 2 chaired by Ana Marie Perea
    Track 3 chaired by Prof. Claudia Camacho

Day 3
18th January 2023

  • Networking Cocktail (7:00 pm – 11 pm)
    Almacen 42 located in Barrio Antiguo

Invited
Presenters

Professor Amlan Chakrabarti

Professor and Director, School of Information Technology, University of Calcutta, India

Dr. Amlan Chakrabarti is a Full Professor in the A.K.Choudhury School of Information Technology at the University of Calcutta. He was a Post-Doctoral fellow at the School of Engineering, Princeton University, USA during 2011-2012. He has 20+ years of experience in Engineering Education and Research. He is the recipient of the DST BOYSCAST fellowship award in Engineering Science (2011), the Indian National Science Academy (INSA) Visiting Faculty Fellowship (2014), the JSPS Invitation Research Award (2016), Erasmus Mundus Leaders Award (2017), the Hamied Visiting Professorship from University of Cambridge, UK (2018), Siksha Ratna Award by Dept. of Higher Education Govt. of West Bengal (2018) and has been awarded as the Fellow of West Bengal Academy of Science and Technology (2022). He has also served in various capacities in various higher education organizations both at national and international levels.

He has contributed immensely in the development of efficient computer algorithms and systems in multiple projects supervised by him in both International and National levels. He led research and consultancy projects supported by CERN Geneva, GSI Helmholtz Research Laboratory Germany, DST, DRDO MietY, Intel, TCS etc. He is also serving as the Head of IT and Tech. Innovation Cell of the Dept. of Higher Education Govt. of West Bengal. He has graduated 20 Ph.D. students till date and has published 200+ research papers. He is the Series Editor of Springer Transactions of Computer Systems and Networks, the Series Editor of the Springer Book Series on “Water Informatics”, an Associated Editor of the Elsevier Journal of Computers and Electrical Engineering and Guest Editor of the Springer Journal of Applied Sciences. He is a Sr. Member of IEEE and ACM, IEEE Computer Society Distinguished Visitor, Distinguished Speaker of ACM, Secretary of IEEE CEDA India Chapter, Member of the International Water Association, Vice President of the Data Science Society and Life Member of CSI India. His areas of research are Machine Learning, Computer Vision, Reconfigurable Computing, VLSI CAD and Quantum Computing.

Dr. Uohna Thiessen

Dr. Uohna Thiessen

Senior data scientist at Meta

Dr. Uohna Thiessen is a data scientist and data science educator whose mission is to promote data science education to as many as possible. A statistician by training, she strongly advocates for the inclusion of scientific rigor in all data science endeavors. She earned a Ph.D. in Epidemiology, with an emphasis in biostatistics, from Walden University, Minneapolis, MN. Her research focused on using cross-sectional or cohort data to develop disease prediction algorithms. Her dissertation led to improved performance of a risk prediction model for cardiovascular disease. Her extensive background in teaching, research, neuroscience, and machine learning gives her a wealth of knowledge and makes her a formidable force for promoting data literacy and data science education.

Dr. Uohna holds an undergraduate degree in Biochemistry from Oakwood Oakwood University, Huntsville, AL, where she started her research career. She conducted cutting-edge research in plant electrophysiology research, under her mentor Dr. Alexander Volkov. Upon graduating from Oakwood, she worked as a formulator for Procter & Gamble (P&G), developing healthcare products. She is credited with having formulated the dozens of flavors for the Crest Whitening Expressions toothpaste campaign, which was a first of its kind and marketing success. After P&G, she pursued a Ph.D. in Neuroscience at Wright State University, Dayton, OH. Completing the required course work and successfully defending her comprehensive exam, she qualified as ABD (All But Dissertation). However, while conducting electrophysiology experiments, she realized that she was more enthusiastic about compiling, analyzing, and presenting research data- hers and her colleagues, than she was about bench experiments. So, she transitioned to Walden University, where she would eventually earn her doctorate. It was as a graduate teaching assistant, both at Walden and Wright State, that her passion for teaching statistics and quantitative analysis was harnessed.

After Walden, she served as an adjunct lecturer at several colleges, including Kettering College of Medical Arts, Kettering, OH, while also parlaying her statistics skills as a part-time statistician consultant. She quickly developed her competence in Python and R programming languages and switched from statistician to data science consultant. Working mainly with small to medium-sized companies across various industries, she helped leverage the power of their data in facilitating innovation and growth. Eventually, she also became an instructor at Flatiron School and Simplilearn, teaching courses in data science, statistics, and machine learning. Most recently, she joined the technology consulting firm Accenture and is on assignment at Meta. She brings her teaching, data science, and data engineering knowledge to one of Meta’s Ad tech teams.
 
Dr. Uohna remains passionate about making data science knowledge available to all. To that end, she launched her YouTube channel, with videos teaching data science and statistics principles. Earlier this year, she started a new project- ‘Data Science and Dance,’ where she uses the latest TikTok dances to teach basic statistics and machine learning fundamentals. Philosophically, she believes that the data belongs to those who generate it, and as such, they should know how to use it. Dr. Uohna believes that the key to data literacy is to make learning data science part of a fun activity- like dancing!

Dr. Mark Thiessen

Senior System Analyst at NASA

Mark Thiessen is a system analyst for NASA Kennedy Space Center (KSC) as part of the Test Operations Support Contract (TOSC), where he leads a launch control software team for NASA’s Artemis program. His goal is to support NASA’s return to human exploration of deep space. At NASA, Mark views everyone as his customer. This philosophy led to him receiving a “TOSC ACE” award.

Mark has a bachelor’s degree in electrical engineering technology from Roger Williams University. His electrical, computer, and software engineering experience span three decades supporting numerous organizations, including Branson Ultrasonics, Spectra Physics, Trimble Navigation, and now NASA KSC.

Dr. Mark Thiessen

For Branson, Mark helped bring their tabletop “Bransonic” ultrasonic cleaners into the computer age. He did this by designing two circuit boards for a new generation of ultrasonic cleaners; one board that used microcontroller-ready power MOSFETs (new technology transistors in those days) to drive the ultrasonic transducers rather than the bipolar transistors used by the previous generation of cleaners and a second board that used an 8-bit 6805 microcontroller to provide timing and heating controls for the user. The program he wrote for that microcontroller was the first he wrote professionally.

For Spectra Physics and Trimble, Mark helped bring their machine control products into the computer age (seeing a pattern?) by replacing their hard-wired products with “smart” products. He did this by designing numerous power and microcontroller circuit boards and ever larger embedded, hard real-time programs, especially for “BladePro,” a series of products that added precision automated control to heavy-duty road graders using ultrasonic, laser, and GPS receivers.

Mark enjoys life outside work with his wife, Uohna. Together they work on machine learning projects, each contributing their relative expertise in analytics, statistics, and programming. As part of NASA’s mission is to expand the interaction of the public, they provide access the massive quantities of their Earth science data. Mark’s excited to talk about NASA’s Mission Data products, particularly the Small Bodies Node, which uses planetary science data to study dwarf planets, objects in the Kuiper Belt, and small planetary satellites.

Dr. Jyoti Gautam

Dr. Jyoti Gautam

SJSS Academy of Technical Education, NOIDA (Affiliated to Dr. APJ Abul Kalam Technical University)

B.E. from Delhi Institute of Technology (NSUT), Delhi University in the year 1997. M.E. from Delhi College of Engineering (DTU), Delhi University in 1998. Done PhD in Computer Science and Engineering in the year 2015 in the area of Semantic Web from Gautam Buddha University under the guidance of Dr. Ela Kumar, Professor in IGDTUW, Delhi. Served as Associate Professor and HOD CSE Department at JSS Academy of Technical Education NOIDA. Currently working as Associate Professor, IT Department, JSS Academy of Technical Education, NOIDA, Uttar Pradesh. Currently, working as Digital Water Program Steering Committee Member of the International Water Association (IWA) for 2022-24. Member IWA India National Executive Committee. Representing as State President Delhi Artificial Intelligence Council, WICCI.

Received the Award of Exceptional Women of Excellence at the 84th Edition of Women Economic Forum. Visiting Professor with Rajiv Gandhi National Institute of Youth Development (Institute of National Importance) Ministry of Youth Affairs and Sports, Govt. of India, Sriperumbudur. Patent granted alongwith Prof. Amlan Chakrabarti in the domain of water conservation and management. Visiting Researcher at the Waterinformatics Laboratory of the department of Information Technology, AKCSIT, University of Calcutta. Presented a Workshop session on ‘An Innovative Paradigm in Water Informatics for Smart City Applications’ alongwith Prof. Amlan Chakrabarti Copenhagen, Denmark from 11th to 15th September, 22. Received certificate of completion for Innovation Ambassador Training ‘Foundation Level’ conducted in online mode by MOE’s Innovation Cell & AICTE during the Academic Year 2021-22. Reviewed the “Digital Water Book’ by the International Water Association. Resource person for presenting a workshop on Water Informatics at IASECT 2021, hosted by PMU, Kingdom of Saudi Arabia.

Invited as a resource person by CEBT (Centre for Emerging Business Technologies) – School of Business and Management (MBA) (Deemed to be University), Pune Lavasa campus for a Water Symposium on the title ‘Designing Digital Solutions for Water Management’. Invited as a resource person by Sinhgad Institute of Management (SIOM), Pune for one Week online FDP sponsored by AICTE on Machine Learning, Data Science and Deep Learning with Python. Invited as a resource person by IWA Headquarters, London for a Webinar on ‘Water Informatics: Introduction and Case Studies’. Webinar hosted by IWA Headquarters, London and is now available on IWA Learn. Invited by IWA (International Water Association) Specialist Group Water Loss, to present a webinar on the research findings in the domain of Water Loss. Invited as a Session Chair by International Water Association, World Water Congress and Exhibition held in Tokyo in September, 2018. Got MOU signed between Xinova, Seattle, USA and JSSATE NOIDA. Invited as a speaker and session chair from different countries for various research works. Jury for Smart India Hackathon and World Skills Competition. Working in Smart Systems, Data Analytics, Data Mining, Machine Learning and Artificial Intelligence. Published papers and Reviewer for various reputed International journals and conferences.

Call for Papers

This workshop welcomes research and practice-based works. We encourage authors to present their research results or work in progress addressing (but not limited to) one or several of the following topics:

  • Educational data mining and learning analytics
  • Technology-enhanced teaching and learning
  • E-learning and transforming educational environments
  • Human–machine collaborative learning
  • Higher education to prepare workforce for Industry 4.0
  • Data-driven Education
  • Digitization, machine learning and deep learning at service of education
  • Neural network and artificial intelligence
  • Immersive Learning Environments
  • Ubiquitous smart technologies in education
  • Virtual, augmented and mixed reality in education
  • Wearable devices and mobile learning
  • Robotics in teaching and learning
  • Remote learning
  • Technology-enabled lifelong learning
  • Technology and aftermath of COVID-19 pandemic
Copy of Future of Educational Innovation-Workshop series (3)
Copy of Future of Educational Innovation-Workshop series (5)

The accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements. The most promising contributions presented at this workshop will be invited to send their extended versions to the linked Special Issues.

We are calling for papers addressing (but not limited to) one or several of the following questions:

  • What are the challenges facing educational researchers employing machine learning as a research tool?
  • What strategies can be implemented in real pedagogical contexts combining machine learning applications in educationally innovative contexts?
  • How are these methodologies, tools and technologies being blended into existing practices?
  • What are the new data points from emerging technologies in machine learning settings?
  • How are the results of machine learning approaches supporting different educational domains?
  • What are the ethical considerations when employing machine learning to support educational innovations?
  • What is the future of machine learning to support educational innovations?
  • What role can AI and ML play in facilitating home-based learning in a pandemic situation?
  • How can ML enable evaluating learning efficiency of students using streaming video inputs?
  • How can ML facilitate academic evaluation for students to gauge teaching-learning effectiveness?

Dates of importance

Submission deadline (Extended Abstract):
8th August 2022 – 8th September 2022

Acceptance Notification:
10th September 2022

Early bird registration:
13th September 2022

Final registration:
13th September 2022

Full paper submission:
1st November 2022 – 8th November 2022

Workshop participation and presentation:
15th December 2022

Revision Notification:
15th January 2023

Full paper acceptance notification:
16-18 January 2023

Submission process

You may submit your contribution in two PDF documents: a blind extended abstract (without author(s) information) and a document with the abstract title and author(s) information.
It is necessary to use the IEEE template for the extended abstract and the full article.
The contributions will be managed through CONFTOOL.

Publications

The accepted papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements. The most promising contributions presented at this workshop will be invited to send their extended versions to the Special Issues linked to this event.

Organizing Committee

General chairs:

Prof-Samira-Hosseini

Prof. Samira Hosseini

Tecnologico de Monterrey, Mexico

Session chairs:

Dr. Asad Abbas

Dr. Asad Abbas

Tecnologico de Monterrey, Mexico

Dr. Kingsley Okoye

Dr. Kingsley Okoye

Tecnologico de Monterrey, Mexico

Dr. Alexander Amigud

Tecnologico de Monterrey, Mexico​

Prof. Claudia Bautista

Tecnologico de Monterrey, Mexico

Prof. Claudia Camacho

Tecnologico de Monterrey, Mexico

Conference coordination:

Dr. Ivan Acebo

Dr. Ivan Acebo

Tecnologico de Monterrey, Mexico

Dra. Nora León-Real

Tecnologico de Monterrey, Mexico

Fernando Torres Guerra

Tecnologico de Monterrey, Mexico

Ana Marie Perea

Tecnologico de Monterrey, Mexico

Registrations

Two-day workshop Participation

$440 USD

Two-day workshop Participation
Certification
Access to the online writing tools and trainings

$560 USD

Disclaimer : This event was an independent university initiative, not affiliated with SAMYRAD.

Sponsors

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Registration for SAMYRAD 2026 will open on July 15, 2026