Our Team
We are innovation driven and quality oriented.
The lead researchers from our research partner RMIT University are outstanding achievers and experts in their respective fields. They will work with TeleMARS to help our customers solve complicated problems. Their profiles can be found through the following links.
Professor Iqbal Gondal
Professor Flora Salim
Professor Zahir Tari
The team of TeleMARS comprises senior ICT engineers and data scientists with average over eighteen years’ professional experience.
The team members have long-time collaboration experience in research, solution development and project delivery.
Chen Lin
Principal Consultant AI Analytics Enabling
Key responsibilities
- Product design authority
- Business analysis and requirement engineering
- Quality control and assurance
- Program and project management
- Business strategy and development
Chen has been practicing in ICT industry for over 25 years with hands-on experience in multiple disciplines across software engineering, data engineering, quality assurance, solution architecture, and project management. She has worked on large-scale projects and transformation programs in various domains including utility, mining, autonomous vehicles, fleet management, train control system, and surveying. Through this journey, she helped organisations to develop Artificial Intelligence (“AI”) and Analytics capabilities to improve productivity, operational performance, workforce effectiveness, business processes, finance performance, infrastructure effectiveness, and customer satisfaction.
Chen is dedicated in continuous learning and staying on top of emerging technology trends. It is Chen’s passion to integrate research activities with industry innovation. She determines to develop right technologies that create values for our community.
Education background
- Master of Computer Engineering, National University of Singapore (research in Advanced Motion Control)
- Bachelor of Electronics, Peking University
Mark Beckett
Chief Commercial Officer
Key responsibilities
- Business management
- Commercial management
- Project coordination
- Communication and Marketing
- Change management
- User experience improvement
Mark has a career background as a lawyer for 20 years. Working in such a fast-paced profession handling complicated processes and vast amount of information on a daily basis, Mark has been motivated to actively adopt advanced technologies to optimise business processes and workflows. His strategic thinking capability, stakeholder management experience, communication and negotiation skills enable him to effectively execute business plans, conduct strong communications, and implement company visions.
He took further study in organisational change management (APMG International Change Management) and project management (PMP) to expand his knowledge and skillsets. He is enthusiastic about helping organisations to get ready for transformation to enable the benefit realisation from adopting new technologies.
Alex Stenlake
Technology Adviser
Key responsibilities
- Technology strategy
- AI solution advisory
- AI and Machine Learning Operation infrastructure
- Data engineering architecture
Working at the forefront of technology design and research commercialisation, Alex has spent half a decade bridging academia and industry in the data science and decision support space. Primarily working within the domains of personalised healthcare, industrial monitoring and finance, Alex has developed a keen sense of what is possible with current technologies, and how organisations can leverage these technologies to unlock value and productivity gains. Alex has built, contributed to and led teams working on dozens of cloud-native, AI-powered applications in both Australia and China, from early-stage startups to multinational enterprises.
As an individual contributor, Alex concentrated on advanced data analytical methods and development of machine learning systems, as well as highly efficient analytics for wearable/embedded devices. This includes data analysis work within the Anaconda stack, extensive RnD experience with the Pytorch ecosystem and cloud-native development including kubernetes and serverless. Observing the failure and stagnation rates within the data science ecosystem, he later turned to solid foundations for sustainable and fault-tolerant data ecosystems, including:
– deploying data quality monitoring systems to improve the quality of organisational data products using open source (Great Expectations, Elemental.ai) and bespoke components.
– designing MLOps automation infrastructure using Terraform, AWS and CircleCI, then building advanced machine learning and statistical microservices for decision automation and credit risk analysis.
– pioneering the use of Modern Data Stack tooling (including Snowflake, DataBricks, DBT, Airbyte, etc.) to promote agile data product development and self-service data analysis.
– contributing code and tooling to the Temporal ecosystem as a potential Airflow successor for DataOps orchestration
Gayan Kulatilleke
Lead AI ML Engineer and Researcher
Key responsibilities
- AI architecture design
- Research and Development
- AI Analytics solution design and development
- AI solution delivery management
Gayan obtained outstanding expertise in practical AI innovation through a combination of industry and research experience.
Gayan worked in software engineering discipline for more than 15 years across various mission critical systems including London Stock Exchange platform and banking systems. He enjoyed implementing a broad variety of cutting-edge technologies to achieve optimal outcomes for customers. He then worked as a PhD researcher in the University of Queensland in the area of AI including Machine Learning. He built in-depth knowledge and experience in computer vision and graph network. His hard work and exceptional research outcomes are widely recognised which won him a series of awards.
- Best paper: Microsoft award: Cybersecurity technical category – HFES 2020
- Best paper: Australasian Joint Conference on Artificial Intelligence – AJCAI 2022
- “Global Knowledge Sharing” award for best technical publication – Virtusa 2003
Gayan is an energetic fast learner with excellent interpersonal and communication skills.
Evgeny Eremeev
Technical Architect
Key responsibilities
- Software architecture design
- Full lifecycle software development
- Technical infrastructure implementation
- Project delivery management
Evgeny masters the art of software engineering through 25 years dedicated practice. He has in-depth understanding in computer system mechanisms, computing methods, and data structure; abundant experience in developing features of enhancing operation system performance and the development of complex applications for national infrastructure.
Evgeny continuously equips himself with new methodologies, frameworks and technologies. He is excellent in designing suitable solutions that not only solve problems but also meet the specific business needs with the vision of short-term and long-term goals,
Jing Yang
Research Advisor
Key responsibilities
- Lead and manage research team
- Guide R&D planning
- Advise research methodologies
- Advise algorithm improvements
Jing is a talented and experienced mathematician and data scientist with over 20 years research experience in data science. She obtained bachelor’s degree in Electronics from one of the most prestige universities in China – Peking University as an outstanding talent. She achieved PhD from the University of Sheffield conducting research in image processing. She worked as a research associate at a number of universities including the National University of Singapore, Warwick University, and the Chinese Academy of Sciences. She conducted and managed research activities in the areas of 3D image reconstruction, satellite image processing, image data extraction, dynamic system analysis, and statistical modelling.
She then moved to United Kingdom the second time in 2013. She has been working as a data scientist at the University of Manchester ever since. She has driven research activities and projects in the areas of machine learning inference approaches to time course data, data model optimisation, biological sequencing data analysis, linear and nonlinear regression, perpetuation point identification, and achieved internationally recognised outcomes. She has great interest in implementing her research experience in resolving real-world problems.