Artificial intelligence (AI) and machine learning technologies are advancing at a rapid rate. The next generation of engineers is currently working on technologies that will reshape global industries, particularly in the fields of education and finance.
The testing grounds for the newest innovative ideas are hackathons. They are where the brightest and most talented engineers and developers compete in a fast-paced tournament to see who can turn their abstract technological ideas into the most functional, real-world solutions.
IBM SkillsBuild AI Hackathon
The Ohio State University recently collaborated with IBM SkillsBuild and the Buckeye Fintech Group to host a 24-hour AI innovation challenge event entitled the IBM SkillsBuild AI Hackathon. It is increasingly common for universities to collaborate with major tech companies to prepare and challenge the newest AI innovators who are bound to change the future.
Participants of the IBM SkillsBuild hackathon included everyone from engineers and developers to technology specialists. Their task was to design and develop the most sophisticated AI-driven solutions that can help solve real-world problems concerning technology in finance and education. The participants worked in teams and had to create a working product from a conceptualized idea within 24 hours. Each team had anywhere from 1 to 5 members.
A panel of judges, who are affiliated with the event’s organizers and industry partners, was given the task of evaluating the projects to determine the winners. Each technical project was submitted under a chosen challenge track and judged based on the following criteria:
- Technical Execution – Did the project effectively use AI and other necessary technologies to come up with a viable solution? Was the solution easy to use and execute?
- Innovation – Did the AI project provide a unique or interesting solution that differed from other tools and strategies?
- Scalability – Is the solution scalable in a real-world environment? Does it address the needs and demands of a real-world environment?
- Relevance – How relevant is the solution for solving real-world challenges?
- Communication – Does the overall presentation demonstrate a clear solution to the problem? Was it an organized and engaging presentation?
Of course, not every team could be a winner. There were more than 30 participating teams and over 150 individual participants. The judges only issued awards to the top six teams that were believed to have the best performances. Any team that was fortunate to be among the top six has something to be proud of.
AI/ML Engineer Lazizbek Ravshanov’s Team Awarded Third Place
Lazizbek Ravshanov is an AI/ML engineer from the University of Cincinnati. His background and expertise include machine learning systems, AI, and infrastructure optimization, all of which were critical in his contributions toward his team’s solution during the hackathon event. These contributions included:
- Core Architecture – Designing and developing the core AI-powered architecture of the technological solution.
- Data Workflow Organization – Structuring the data workflow and system logic between the Chrome extension and other backend services.
- Analytics Dashboard – Creating an analytics dashboard for the system that provides clear and concise metrics regarding focus time, productivity trends, and distraction events.
- Data Visualization – Building a comprehensive full-end interface where team members can access visualized behavioral insights study session data in real-time by observing interactive charts and monitoring panels.
- User Experience – Implementing role-based views for administrators and students.
- Seamless Integration – Ensuring a seamless integration between the dashboard and the AI classification module.
Ravshanov took on the role of team leader throughout the 24-hour intense competition. His team received the competitive challenge to develop solutions for the challenge track of “AI in Education.” Under his leadership, Ravshanov had to come up with an effective technical strategy for the team and assign roles and duties to each team member based on their own skills and expertise.
The Solution
Ravshanov’s team included brilliant developers like Jaeha Lee and Junna Park. Together, they created an Institutional Learning Analytics Platform that could convert unseen student behaviors into actionable institutional understandings. In other words, the team was not just creating another automated AI study chatbot assistance. Instead, they wanted to create a solution to help students understand and improve their own study patterns.
Meanwhile, learning institutions would now have a system to visualize academic trends to see how well students are doing in various academic fields of study. These kinds of insights prove to be much more reliable than traditional feedback and survey-based insights.
The Outcome
As the team leader, Ravshanov performed the final technical presentation in front of the panel of judges. His knowledge and experience were on full display as he explained his solution’s system architecture, real-world applications, AI logic, and the level of impact it would have on the education-based challenge at hand.
The judges followed up by asking him highly technical questions, which Ravshanov answered with clarity, depth, and detail. It was obvious to the judges and spectators that Ravshanov had full command of the system that his team had developed. His strategic direction turned a mere concept of a solution into an advanced, highly technical, and competitive product. Furthermore, the judges were impressed that his team met all the required deadlines and delivered a complete, realistic, and fully functional solution aligned with modern industry standards.
As a result, the panel of judges granted Ravshanov and his team the Third Place Award at the IBM SkillsBuild AI Hackathon. Even though it was not first or second place, receiving third place is quite an accomplishment when competing against more than 30 other teams. It clearly demonstrates Ravshanov’s rich skills and ability to develop, integrate, and execute scalable AI solutions under enormous time constraints. Few other people in the world could have done the same.
Conclusion
AI/ML engineers like Lazizbek Ravshanov thrive in competitions like IBM SkillsBuild AI Hackathons. Rather than making participants code for 24 hours, they have to work together to come up with AI-powered technological solutions that solve real-world problems.
The time constraints and teamwork allow for their creativity and intelligence to excel more than they can in a research lab. That is why more and more universities are teaming up with tech companies to host similar hackathon events. These are the events where the technological solutions of the future will be discovered.
