30Under30 Nominee: Yangchen Huang

Great to hear from Significant Insights Global 30 under 30 nominee Yangchen Huang who is the Staff AI Research Engineer and Tech Lead of GenAI Research team at AlphaSense, the largest AI powered market intelligence platform in the world.

The 2024 Global 30 Under 30 List will be announced on November 29th!

So, how did you get into the industry, and take us through how you got to this point?

While pursuing my master’s degree in Management Science and Engineering at Columbia, I interned at JPMorgan Chase as an Applied AI Summer Associate. There, I worked on AI-driven projects focused on condensing and summarizing vast amounts of documents and data to generate insightful analytical reports. This experience marked my first exposure to the research and analytics industry, and I quickly developed a deep passion for it.

Upon graduation, I joined JPMorgan full-time as an Applied AI Scientist, where I designed innovative AI models to streamline the financial research process by reducing the time and complexity of manual tasks. One notable achievement was the development of an earnings call summarization model, which could transform lengthy earnings calls into concise reports; I presented this solution at EMNLP 2021.

Starting 2022, I worked at AlphaSense as a Staff AI Researcher and Tech Lead for the GenAI team. I led the development of two pioneering GenAI products, Smart Summaries and AlphaSense Assistant, which provide high-quality GenAI solutions for professionals in financial research and market intelligence. These products earned lots of industry recognition, including honoree as Forbes AI 50 and WatersTechnology Best AI/ML Initiative. In recognition of my contributions to the global AI and research community, I received the 2023 Global GenAI Award – Individual Innovator. Additionally, I am committed to helping global talent in market research develop and grow, teaching the “Generative AI in Research” course at CFTE, the leading knowledge platform in digital finance and Fintech.

Why should anyone consider a career in market research, data and insights?

A career in market research, data, and insights offers the opportunity to be at the forefront of decision-making in a world driven by data. Market research enables professionals to extract valuable insights from massive amounts of information, empowering businesses to make informed choices, which is the most critical role in today’s ‘big data’ environment. This field combines data analysis with critical thinking, offering a rewarding mix of analytical rigor and creative problem-solving.

The rise of GenAI has only expanded the scope and impact of a career in market research. It allows researchers and analysts to aggregate data, perform complex calculations, and write detailed reports with unprecedented speed and efficiency. By automating routine tasks and facilitating creative analysis, GenAI provides new ways to interpret data and explore innovative strategies. For anyone passionate about shaping the future of decision-making, a career in market research, data, and insights – particularly one that leverages GenAI – is both exciting and impactful.

Career paths are rarely without challenges. Can you share an honest moment from your career when things didn’t go quite according to plan, but the lessons remain with you to this day?

Building AI solutions for market research has come with its share of challenges, especially around accuracy, which is essential for research and analytics. In my experience, Generative AI often generates errors or ‘hallucinations’ – instances where the model assumes incorrect relationships, makes flawed causal inferences, or draws inaccurate conclusions.

Early on, we faced difficulties in aligning Large Language Models with the high accuracy standards required in the research industry. We have improved the accuracy by leveraging innovative RAG pipelines and also introduced citations to ensure one-click verification on the generated content, and users found citations extremely helpful. A valuable lesson I learned is that while AI is advancing rapidly, it’s not a substitute for human oversight. Even with the impressive capabilities of GenAI, maintaining human involvement to verify AI-generated outputs is essential to ensure the highest quality and reliability in research.

What two things should junior researchers focus on as they progress in their careers?

Be Honest with Data: Data integrity is foundational in research. Junior researchers should commit to being honest and transparent with data, as data reveals objective insights critical for sound decision-making. This means avoiding biases, acknowledging limitations, and focusing on what the data truly conveys, even if the findings challenge initial expectations.

Adapt to Cutting-Edge Technology: Staying competitive in the research field also requires adaptiveness to emerging technologies, especially as in recent years GenAI has been revolutionizing research processes. Junior researchers who adopt GenAI can work more efficiently, utilizing AI to accelerate data analysis, summarize lengthy reports, and uncover insights at a much faster pace. Familiarity with these tools enhances productivity, allowing researchers to focus more on strategic thinking rather than time-consuming manual tasks.

Do you have any advice for our sector?

Embracing advancements in AI, especially Generative AI, can significantly enhance efficiency and analytical capabilities in research. Lots of tools powered by AI can automate time consuming manual process and allow researchers to focus more on interpreting insights rather than gathering raw data. While technology can handle many tasks, the real value lies in researchers’ ability to think strategically and generate unique insights.

Go beyond surface-level findings by connecting trends, recognizing patterns, and forecasting implications. In addition, as automation becomes more prevalent, it’s crucial to validate the details to maintain accuracy. Automated tools can expedite processes, but they’re not fool proof. By combining automation with rigorous validation, researchers can ensure high-quality and reliability in research outcomes, which is critical for sound decision-making.

And do you have anyone who has helped your career so far that you’d like to acknowledge and say thanks or give a shout out to?

I’d like to express my gratitude to my manager, Prashant K Dhingra, Managing Director at JPMorgan Chase, for introducing me to the field of developing cutting-edge technology to enhance the research process. I’m also grateful to my manager and friends, Peng Wang, Senior Director of Search and AI, and Chris Ackerson, VP Product, along with every member of the AI Research team at AlphaSense. Together, we built transformative GenAI products that earned significant industry recognition, a success made possible by the leadership and support of Chris and Peng and the dedicated efforts of each team member.