Krishna Cheemalapati: Krishna Cheemalapati's expertise as a UX-focused web developer and seasoned educator uniquely positions him to contribute to NeuroLingo's mission. With experience conducting A/B tests to optimize user engagement and implementing full-stack features from wireframes, Krishna can design and develop intuitive, user-centric interfaces that align with NeuroLingo’s vision of personalized learning journeys. His 1,000+ hours of tutoring and teaching have honed his ability to adapt complex concepts to diverse learning styles, enabling him to ensure that NeuroLingo’s AI-driven language lessons are accessible and effective for users from all backgrounds. By combining technical expertise with a deep understanding of user needs, Krishna can help NeuroLingo revolutionize language education through engaging curricula and interfaces.
Tony Juntao Hu: Tony’s unique strengths in both linguistics and computer science are what enabled him to come up with this original product idea. His passion about second language learning and teaching is coupled with his extensive research background in linguistics and language acquisition. These make Tony a critical member to ensuring that our product provides an effective, research-driven approach to language learning. Further, his knowledge about computational linguistics, as well as programming and software engineering practices will allow him to contribute significantly to maintaining code quality and product robustness through testing and DevOps.
Leonid Nediak: As a software developer with experience writing code for scientific computing, Leonid Nediak provides an alternative perspective to the product code. Having worked on medium-large codebases and done research at financial institutions he is well suited to design and write any more mathematically involved code for NeuroLingo. His experience also includes working with databases and data processing, so he can significantly contribute to the back-end and the data pipeline.
Parth Vats: With significant experience working with backend technologies and databases in the industry as a software engineer intern, Parth brings a strong blend of backend knowledge and unique insights to the team. Having previously worked at a fast-paced tech startup, Parth has adopted several key industry practices to help push the team forward. In addition to more than a year of working with web technologies at the startup, Parth also has experience working as a full-stack engineer in software projects, which enhances his ability to work effectively with other engineers on the team. Lastly, having experienced the problems NeuroLingo aims to solve, and with experience developing user-centric solutions, Parth can bring his unique set of experiences and work together with the team to help create an effective solution.
Wilson Sy: Wilson’s industry experience with large backend architectures, both at design and implementation stages, is valuable to ensure that Neurolingo’s codebase is scalable and maintainable from its inception. His technical knowledge will help the team make quick and informed decisions on the many architectural choices that we will encounter building a backend from scratch. Besides engineering skills, Wilson’s strong personal interest in project management and customer development will keep the team aligned on an achievable vision that is informed by hands-on market research. Lastly, Wilson’s care for digital privacy and academic interest in linguistics will provide meaningful perspectives on Neurolingo’s vision, especially around safe and scientifically sound applications of AI.
The most critical area where the team lacks expertise is prompt engineering. Since we anticipate using Cohere’s LLM to implement a large part of our product, effective prompt engineering is key to avoid generating false information, incorrectly formatted data, or natural language that is inappropriate in tone or content. A related weakness is our general unfamiliarity with AI safety, which would help us detect systemic biases in our product and to implement safeguards against harmful content.
Another weakness is our unfamiliarity with gamification or mechanisms to improve user interactivity. Many competitors in the market use gamification to retain users and make the more mundane aspects of language learning, like memorizing vocabulary, more fun.
At a product level, our team lacks experience working with organizational customers. For example, a potential customer segment for Neurolingo is a school board that offers formal language education: we are unsure how to find connections or start conversations with key stakeholders in such a large, structured organization. Overcoming this weakness may be important to growing our market demand beyond B2C sales.
Expert 1: Expert who gamifies linguistic education - Nathan Sanders
Nathan Sanders is a linguistics professor at the University of Toronto who specializes in innovative pedagogy, including gamification, project-based learning, and creative approaches in STEM education. His substantial experience designing educational games aligns with NeuroLingo’s goal of creating engaging, research-backed learning tools. We believe that Professor Sanders’ expertise can guide us in designing gamified exercises that prioritize knowledge retention over streaks and superficial engagement. His focus on equity and inclusion in linguistics education can also help ensure that our product caters to diverse learners by incorporating culturally inclusive content.
Expert 2: A prompt engineer - Adrian Mensah
As mentioned above, our team lacks experience in prompt engineering. Thus an experienced prompt engineer like Adrian Mensah would be a great subject matter expert to contact for advice. As he also has a Bachelor’s in linguistics and experience with teaching English as a second language, he may be able to give us prompt design insight more specific to language learning.
Expert 3: Expert on designing engaging user interfaces - Joseph Jay Williams
Despite our team's experience with UX design, development, and the application of LLMs, we lack the specialized knowledge required to design solutions that both integrate these concepts and effectively address the needs of non-consumer stakeholders. Our limited insights into the intersection of AI-enhanced applications and user experience make it challenging to create interfaces that both communicate our solutions’ value and meet the specific needs of large, structured organizations. This weakness is particularly significant when attempting to build trust and demonstrate value to decision-makers who prioritize functionality, scalability, and alignment with their educational objectives. Professor Williams, a professor at the University of Toronto, has extensive expertise in applying AI-enhanced tools in educational settings and conducting research in human-computer interaction. His work addresses precisely the challenge we face—designing user interfaces and experiences that are both intuitive and compelling in the context of education. By leveraging his insights (both in this specific domain of research as well as his experiences as a professor at numerous universities), we can better understand how to align our product design with the expectations of stakeholders such as school boards and universities, enabling us to bridge the gap between our technical capabilities and the practical needs of organizational customers. This alignment is crucial to overcoming our current limitations and expanding into the broader educational market.
On the visible level, our group lacks diversity in gender, since we all identify as males. The potential implications of this are in areas such as UI design, public relations, and what we prioritize in functionality. However, given that gender issues are often in the spotlight in historically gender-skewed disciplines such as STEM, and that some members are actively engaged in discourse about gender outside of the course, we are confident in our introspective abilities to combat potential biases in this area.
The second visible lack of diversity is in nationality/ethnicity. All our team members are of Asian or half-Asian descent, and the majority grew up in North America. Of course, this means we have some diversity, but our group composition is, in a sense, quite “stereotypical” in CS. While it may be easy for us to understand “mainstream” cultures, like Western or East Asian cultures, it will be harder for us to appreciate under-represented or marginalized cultures, even those such as the cultures of indigenous peoples of Canada. It is not to say that these cultures have a direct impact on our product design or marketing, but a deeper understanding of them will undoubtedly be beneficial (especially if we wish to expand our offerings to such markets in the future).
To illustrate this point, one example we discussed is the difference in UI design philosophies in Western vs. Chinese (or East Asian) tech. Modern Western UI design emphasizes simplicity, clarity, and often places strong emphasis on search. On the other hand, many Chinese apps are designed such that the homepage shows as much variety and as many options as possible, almost like a web portal. Given our team members received higher education, and specifically training in computer science, in the same environment, it will be difficult for us to be aware of these culture-specific differences, which can extend beyond UI/UX.
A third lack of diversity is social class. All our team members are from relatively well-off families who are able to support us financially. Being from a similar social class means that, when we market our product, we may mold the potential customer around a similar profile and forget to consider people who are interested in using our service but are unable to afford it. This has definite implications on our business model and product pricing. Further, people who carry financial burdens also tend to have limited time to spend on language learning. This means that methods that we advocate for, which presume ample time dedicated to learning, may not work as well for them. It is imperative that we take these factors into account, since our mission is to empower everyone, not just people with lots of money to spare, with personalized language learning experiences.
Finally, our team has limited experience considering the needs of people with physical, mental, and other learning disabilities, apart from the fact that one member has ADHD. While we are aware of the importance of accessibility in product design, in many places this is often an afterthought. Therefore, we will need to put effort into eliminating this mindset and focusing on accessibility and supporting different learning styles and needs from the outset.
In sum, our limited diversity in these areas means that we may be inaccurate in our vision of the market segment and customer needs and preferences. We believe, however, that an important tool we have at our disposal is customer surveys and interviews. We are committed to listening to customer suggestions and feedback every step along the way. In fact, we have already crafted our first customer survey. By sending this form to members of all kinds of demographics, we hope to gain valuable insights into their unique perspectives, preferences, and pain points. This feedback will enable us to refine our product offerings, ensure inclusivity, and better align with the diverse needs of our target market(s).