I am a disciplined full-stack data scientist, software engineer, and AI practitioner, abiding by the craftsmanship manifesto. I have a bachelor’s degree in computer software engineering and a master’s degree in the same field with a data science specialization. My Ph.D. is in optimizing notification delivery strategies to enhance the user experience by utilizing artificial intelligence and software engineering. I have hands-on industrial experience as a full-stack developer, software and data engineer, full-stack data scientist, team lead, and chief technology officer at different stages of my career, end-to-end, from ideation to full-fledged products, from small startups to SMEs. I also have a passion for science, research & development, pushing the boundaries, seeking novelty, and solving fundamental problems. Wherein, I honed research experience in various machine learning fields such as predictive modeling, graph mining, causality, and multivariate time series analysis.
Academia
PhD Candidate
2020-2024
Design with Data and AI for Optimized Experience Sampling
Eindhoven University of Technology (TU/e)
During my PhD, as a member of the STRAP (Self TRAcking for Prevention and diagnosis of heart disease, an NWO-funded project) consortium I offer my data science and software engineering expertise, and I have been doing research about data-driven and smart adaptive systems that improve acceptance, adherence, and quality of data collection, especially in the context of the Experience Sampling Method. Accordingly, I have done numerous user studies with participants at TU/e and in collaboration with institutions such as Utrecht University, GGz Centraal, and Wageningen University. You can find a detailed overview of my PhD work in this doctoral consortium workshop paper and in the TU/e research portal.
FOSS contributions
During my PhD, I have created the following open-source projects:
A smartwatch-based experience sampling tool
SimulAting PrticiPant beHavIoR during Experiments
Automated In-Context Learning to Generate Code Provided Examples with Docstrings
Master’s Student Supervision
I have closely supervised 3 master’s students Lars Giling, Sven Bormans, and Catarina Dias de Oliveira who worked on “data-enabled design for cardiac telemonitoring”, “adaptive, context-sensitive smartwatch user interfaces”, and “human digital twins for diabetes management” topics respectively. Below you can find our related publications:
- Lars Giling
- Sven Bormans & Kang Ling
- Comparative Evaluation of Touch-Based Input Techniques for Experience Sampling on Smartwatches (accepted, to be published)
- Catarina Dias de Oliveira
Publications
Below you can find my latest publications related to my PhD research:
- Experiencer: An Open-Source Context-Sensitive Wearable Experience Sampling Tool | SpringerLink
- Simulating Participant Behavior in Experience Sampling Method Research | Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (acm.org)
- IJERPH | Free Full-Text | Assessing the Influence of Physical Activity Upon the Experience Sampling Response Rate on Wrist-Worn Devices (mdpi.com)
For the full list of my publications please visit my Google Scholar page.
Master’s
2015-2018
Data Science
Iran University of Science and Technology (IUST)
The title of my master’s thesis is “Action Extraction from Social Network Graphs Using Causal Structures to Increase Applicability of Extracted Actions”. You can find its cover page and abstract here.
Teaching Assistant
During my master’s, I was an active member of the data engineering lab and I taught “Advanced databases” and “Search engines and web mining” for 2 consecutive semesters.
Publications
Below you can find my publications w.r.t my research during my Mater’s program:
- Actionable knowledge discovery from social networks using causal structures of structural features – IOS Press
- Extracting Actionable Knowledge From Social Networks Using Structural Features | IEEE Journals & Magazine | IEEE Xplore
For the full list of my publications please visit my Google Scholar page.
Bachelor’s
2010-2015
Computer Software Engineering
Urmia University
The title of my bachelor end project is “Location-based Cross-platform Search Engine Application for Local Businesses and Consumers”. You can find its cover page and abstract here.
Certificate of Appreciation
for devoted work at the 7th International Conference on Information and Knowledge Technology, Urmia University, May 26-28, 2015.
Industry
Software Eng. & Data Scientist (Full Stack)
2020-2024
GameBus, Eindhoven, Netherlands
During my PhD at Eindhoven University of Technology (TU/e), I was an active member of the GameBus team, an open-access GDPR-oriented gamified mHealth platform that also acts as a data repository.
- As a PhD candidate with software, data & ML engineering skills within our team of 5-10 (PhDs, researchers, student assistants, and developers) we continuously designed and developed new enhancements to GameBus both at the feature and architecture level.
- I have specifically led the ETL & design and development of data streams from smartwatches for continuous data collection and integration with data visualization solutions while also composing advanced queries to visualize derived metrics from complex physiological data structures.
- I was also involved in upgrading the data model underlying the infrastructure specifically for designing surveys and managing external data-providing devices such as smartwatches.
- I led the design and development of an alerting mechanism using a dynamic interoperable pseudo-programming language that accumulates/processes data streams and generates notifications based on stakeholder-defined rules.
- I also set up our independent docker registry to facilitate our containerized micro service architecture.
Technical Advisor
2022-2024
Dorakk, Remote
Dorakk is an education technology company that provides an online learning and teaching platform focusing on music courses. As a technical advisor, I have been in direct and close contact with the founding team to advise, supervise, and direct:
- Technical personnel recruitment
- Onboarding the technical personnel
- Product design and management
- Forming a roadmap for the data management plan and future AI & ML pathways
- Technology assessment and quality control
Software Engineer
2015-2020
Yekom Consulting Engineers, Tehran, Iran
Yekom is a leading multidisciplinary consultancy private firm with 50 years of experience, 400 staff, and about 1000 local and international projects completed so far. Yekom is among the top 5 Iranian consultancy firms in irrigation, water, and environments. I designed, implemented, and maintained:
- Intranet portal,
- Warehouse management,
- Quality control document management,
- And, payroll management
applications (also including ETL, and data engineering) while at Yekom alongside a technical team of 5.
I also supervised interns and led the onboarding and training of our software developers.
CTO & Advisor
2018-2019
Talasho, Tehran, Iran
Talasho was a shopping platform not limited to goods, and in addition to products, it also provided services. Furthermore, by engaging in collaboration in sales, it could act as an executor for advertising high-quality goods. Talasho as an innovative digital business was born in the year 2018 and I was involved from the beginning alongside the founding team.
- Recruited and then managed a talented software team of 4 (including front-end and back-end developers) working on the Talasho platform.
Co-Founder & CTO
2016-2019
Nullatech AI
Nullatech was a SaaS provider based on big data analysis and machine learning algorithms. We provided analytic and prediction services on massive financial data, customer behavior, fraud detection, and social media mining.
I was heavily involved in the design and development of our algorithm and leading our corresponding team of 5-10 (including data engineers, data scientists, back-end and front-end developers). Besides, I led the technical aspect of work including data and ML engineering (ETL, AutoML, MLOps, DevOps).
TechCrunch Battlefield
We were invited as a top-pick FinTech startup to present our work at the venue in Berlin, Germany in 2018.
TechStars Accelerator
We were qualified for the TechStars accelerator startup acceleration program, London, UK, 2018.
IFIA Award
International Federation of Inventors’ Associations (IFIA) Award for novel AI algorithm design and innovative solution to financial market prediction, Tehran, Iran, 2017.
Startup Istanbul
Nullatech made it to the top 15 finalist startups among 25000 teams from +135 countries, Istanbul, Turkey, 2017.
Entrepreneur In Residence
Our journey started at the Tivan Entrepreneurship Club, then we moved to Samsung AUT Tech, and lastly to Zavié where our IP ultimately merged with another company and the founding team of Nullatech AI made an exit.
Full-stack software developer and data engineer
2011-2020
Freelance
Designed and implemented various software applications, both individually and within teams of 2-10 developers, including:
- 5 commercial mobile applications
- 10 e-commerce, company, and personal websites
- 10 enterprise Windows desktop applications
I was also responsible for server configuration and administration of most such projects some with >10k daily active users.
Besides, I occasionally advised startups and business owners to build or expand their software development teams.
Technical Skillset
I am fluent in:
Python, Java, SQL, JavaScript
And I have ample practical experience with:
C#, C, PHP, HTML, CSS
Also with frameworks and environments such as:
Node.js, Flask, Django, Laravel, ASP.net, Angular, React
For ML projects I frequently use libraries and tools such as:
TensorFlow, ScikitLearn, Keras, Pandas, Numpy, SimPy, Pomegranate, OpenCV
Using a mix of databases such as:
MySQL, MongoDB, MS SQL Server, IndexedDB, PostgreSQL, Redis
Orchestrated mainly by:
Docker, NGINX, Apache
Complying with:
REST, Microservices, MVC, SOLID
Visualized via:
Matplotlib, Metabase, Apache Zeppelin
CI/CD, version controlled, tracked via:
Git (GitHub, GitLab, BitBucket), Jira, Trello
For a variety of operating systems such as:
TizenOS, Linux, Windows, Android
Lastly, I am knowledgeable in:
Distributed systems (HDFS) and data streams (Kafka, and Spark), MLOps, DevOps, ETL, End-to-end Solutions, Cloud Computing, Message-brokers, Algorithms and Data Structures, Software Design Patterns, Database Management, Testing, Networking, Operating Systems, Security Principles, Concurrency and Parallelism.