{"id":24492,"date":"2025-10-15T13:41:53","date_gmt":"2025-10-15T17:41:53","guid":{"rendered":"https:\/\/design.ncsu.edu\/industrial-design\/2025\/10\/15\/nc-state-design-alumna-honored-for-role-in-award-winning-ibm-ai-innovation\/"},"modified":"2026-02-25T23:02:50","modified_gmt":"2026-02-26T04:02:50","slug":"nc-state-design-alumna-honored-for-role-in-award-winning-ibm-ai-innovation","status":"publish","type":"post","link":"https:\/\/design.ncsu.edu\/industrial-design\/2025\/10\/15\/nc-state-design-alumna-honored-for-role-in-award-winning-ibm-ai-innovation\/","title":{"rendered":"NC State Design Alumna Honored for Role in Award-Winning IBM AI Innovation"},"content":{"rendered":"\n\n\n\n\n

NC State College of Design alumna Dipali Aphale<\/a> (BID \u201817) has been recognized on the global stage as part of an IBM team that won Best AI Solution for Data Insights & Knowledge Management at the Banking Tech Awards USA 2025<\/a>.\u00a0<\/p>\n\n\n\n

The award, announced May 29 in New York City and highlighted by IBM in June, recognized IBM Synthetic Data Sets<\/a>: a groundbreaking tool that allows banks and insurers to train artificial intelligence models without relying on sensitive customer information.\u00a0<\/p>\n\n\n\n

The recognition placed IBM alongside some of the biggest names in global finance, but for Aphale, it also marked a personal milestone. \u201cMost of the other winners that night were some of the biggest financial services companies in the world,\u201d she said. \u201cSo the fact that our small but mighty team of five was recognized among giants was a really special experience.\u201d<\/p>\n\n\n\n

Building Responsible Innovation<\/strong><\/h3>\n\n\n\n

Released in early 2025, IBM Synthetic Data Sets uses statistical modeling to replicate the complexity of real financial transactions while stripping out any identifiable personal information. Each dataset is pre-labeled \u201cfraud\u201d or \u201cnot fraud\u201d so that AI systems can be trained and validated more quickly.\u00a0<\/p>\n\n\n\n

The innovation has since earned global attention for its potential to accelerate trustworthy AI development across banking, insurance and other data-intensive industries. For Aphale, who works as a design researcher at IBM, the project was a chance to blend rigorous design methods with cutting-edge technology.<\/p>\n\n\n

\n \n
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\"\"<\/figure>\n\n\n <\/div>\n\n\n
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\"\"<\/figure>\n\n\n <\/div>\n\n\n <\/div>\n\n\n\n

\u201cMy work as a design researcher is split into three key domains: research \u2014\u00a0how did we get here? Design \u2014 where do we go? And strategy \u2014 what do we work on first?\u201d she explained. \u201cBringing each of these domains to the table helped shape the types of data we included in the dataset, how our product was a positive intervention to shorten the AI model lifecycle and which customer segments we prioritized for adoption.\u201d<\/p>\n\n\n\n

Her contributions helped define not just the product\u2019s structure but its purpose: making data innovation faster, safer and more equitable.<\/p>\n\n\n\n

Lessons from Design School<\/strong><\/h3>\n\n\n\n

Aphale traces much of her professional mindset back to her time at the College of Design. <\/p>\n\n\n\n

\u201cOne of my favorite things about design school \u2014 something I wish we did more of in the \u2018real world\u2019 \u2014 was experiencing brutally honest critiques,\u201d she said. \u201cBeing able to objectively break down your work from multiple perspectives that challenge your original intention, all while maintaining emotional composure, and then being actionable about iterating on the work is something that only design school can really prepare you for.\u201d <\/p>\n\n\n

\n
\n

“My classmates and I developed such a thick skin, and also became more competent at challenging an idea, even if it was our own.”<\/p>\n <\/div>\n<\/blockquote>\n\n\n\n

That iterative process, she added, taught her how to separate ego from output, which is a crucial skill in fast-moving, high-stakes innovation environments. \u201cMy classmates and I developed such a thick skin and also became more competent at challenging an idea, even if it was our own.\u201d <\/p>\n\n\n\n

Beyond critique, she points to her industrial design education as foundational for understanding human systems within technological contexts.<\/p>\n\n\n\n

\u201cSo many skills from industrial design are applicable across technology design roles, but specifically for IBM Synthetic Data Sets, user research and market research were cornerstones in getting the product to market,\u201d she said.<\/p>\n\n\n\n

\"Dipali<\/figure>\n\n\n\n

The Human Side of Data<\/strong><\/h3>\n\n\n\n

While the technical achievement behind Synthetic Data Sets is impressive, Aphale believes its true impact lies in what it represents: a step toward ethical, privacy-conscious data science. \u201cIn the age of surveillance capitalism that we live in, I hope this project speeds up the value that AI can bring to financial services without compromising user data for monetary gains,\u201d she said. <\/p>\n\n\n\n

By replacing sensitive personal data with synthetic information that behaves the same way, the technology enables companies to build and test AI tools without the ethical or legal risks of handling real user records. The result: faster innovation, greater transparency and stronger consumer trust.<\/p>\n\n\n\n

\u201cI\u2019m also excited to see what data scientists can do much more effectively with AI models now that they can access data unencumbered by the months of preprocessing that usually takes place in enterprise markets,\u201d Aphale added. <\/p>\n\n\n\n

As technology continues to evolve at lightning speed, Aphale encourages design students to keep their eyes not just on what\u2019s new, but on what\u2019s enduring. <\/p>\n\n\n\n

\u201cTechnology is without a doubt incredibly cool,\u201d she said, \u201cbut pay more attention to patterns in society and how technology has changed or proliferated them. Those patterns will outlast any shiny new thing that gets built.\u201d<\/p>\n\n\n\n

<\/p>\n

This post was originally published<\/a> in College of Design Blog.<\/em><\/p>","protected":false,"raw":"\n\n\n\n\n

NC State College of Design alumna Dipali Aphale<\/a> (BID \u201817) has been recognized on the global stage as part of an IBM team that won Best AI Solution for Data Insights & Knowledge Management at the Banking Tech Awards USA 2025<\/a>.\u00a0<\/p>\n\n\n\n

The award, announced May 29 in New York City and highlighted by IBM in June, recognized IBM Synthetic Data Sets<\/a>: a groundbreaking tool that allows banks and insurers to train artificial intelligence models without relying on sensitive customer information.\u00a0<\/p>\n\n\n\n

The recognition placed IBM alongside some of the biggest names in global finance, but for Aphale, it also marked a personal milestone. \u201cMost of the other winners that night were some of the biggest financial services companies in the world,\u201d she said. \u201cSo the fact that our small but mighty team of five was recognized among giants was a really special experience.\u201d<\/p>\n\n\n\n

Building Responsible Innovation<\/strong><\/h3>\n\n\n\n

Released in early 2025, IBM Synthetic Data Sets uses statistical modeling to replicate the complexity of real financial transactions while stripping out any identifiable personal information. Each dataset is pre-labeled \u201cfraud\u201d or \u201cnot fraud\u201d so that AI systems can be trained and validated more quickly.\u00a0<\/p>\n\n\n\n

The innovation has since earned global attention for its potential to accelerate trustworthy AI development across banking, insurance and other data-intensive industries. For Aphale, who works as a design researcher at IBM, the project was a chance to blend rigorous design methods with cutting-edge technology.<\/p>\n\n\n\n\n\n

\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n\n\n
\"\"<\/figure>\n\n\n\n
\"\"<\/figure>\n\n\n\n\n\n

\u201cMy work as a design researcher is split into three key domains: research \u2014\u00a0how did we get here? Design \u2014 where do we go? And strategy \u2014 what do we work on first?\u201d she explained. \u201cBringing each of these domains to the table helped shape the types of data we included in the dataset, how our product was a positive intervention to shorten the AI model lifecycle and which customer segments we prioritized for adoption.\u201d<\/p>\n\n\n\n

Her contributions helped define not just the product\u2019s structure but its purpose: making data innovation faster, safer and more equitable.<\/p>\n\n\n\n

Lessons from Design School<\/strong><\/h3>\n\n\n\n

Aphale traces much of her professional mindset back to her time at the College of Design. <\/p>\n\n\n\n

\u201cOne of my favorite things about design school \u2014 something I wish we did more of in the \u2018real world\u2019 \u2014 was experiencing brutally honest critiques,\u201d she said. \u201cBeing able to objectively break down your work from multiple perspectives that challenge your original intention, all while maintaining emotional composure, and then being actionable about iterating on the work is something that only design school can really prepare you for.\u201d <\/p>\n\n\n\n\n\n

That iterative process, she added, taught her how to separate ego from output, which is a crucial skill in fast-moving, high-stakes innovation environments. \u201cMy classmates and I developed such a thick skin and also became more competent at challenging an idea, even if it was our own.\u201d <\/p>\n\n\n\n

Beyond critique, she points to her industrial design education as foundational for understanding human systems within technological contexts.<\/p>\n\n\n\n

\u201cSo many skills from industrial design are applicable across technology design roles, but specifically for IBM Synthetic Data Sets, user research and market research were cornerstones in getting the product to market,\u201d she said.<\/p>\n\n\n\n

\"Dipali<\/figure>\n\n\n\n

The Human Side of Data<\/strong><\/h3>\n\n\n\n

While the technical achievement behind Synthetic Data Sets is impressive, Aphale believes its true impact lies in what it represents: a step toward ethical, privacy-conscious data science. \u201cIn the age of surveillance capitalism that we live in, I hope this project speeds up the value that AI can bring to financial services without compromising user data for monetary gains,\u201d she said. <\/p>\n\n\n\n

By replacing sensitive personal data with synthetic information that behaves the same way, the technology enables companies to build and test AI tools without the ethical or legal risks of handling real user records. The result: faster innovation, greater transparency and stronger consumer trust.<\/p>\n\n\n\n

\u201cI\u2019m also excited to see what data scientists can do much more effectively with AI models now that they can access data unencumbered by the months of preprocessing that usually takes place in enterprise markets,\u201d Aphale added. <\/p>\n\n\n\n

As technology continues to evolve at lightning speed, Aphale encourages design students to keep their eyes not just on what\u2019s new, but on what\u2019s enduring. <\/p>\n\n\n\n

\u201cTechnology is without a doubt incredibly cool,\u201d she said, \u201cbut pay more attention to patterns in society and how technology has changed or proliferated them. Those patterns will outlast any shiny new thing that gets built.\u201d<\/p>\n\n\n\n

<\/p>\n"},"excerpt":{"rendered":"

Industrial Design alumna Dipali Aphale (\u201917) is part of the IBM team recognized with Best AI Solution \u2013 Data Insights & Knowledge Management at the 2025 Banking Tech Awards USA. The winning project, IBM Synthetic Data Sets, uses artificial intelligence to generate realistic, privacy-protected data for safer innovation across industries.<\/p>\n","protected":false},"author":14,"featured_media":24493,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"source":"ncstate_wire","ncst_custom_author":"","ncst_show_custom_author":false,"ncst_dynamicHeaderBlockName":"","ncst_dynamicHeaderData":"","ncst_content_audit_freq":"","ncst_content_audit_date":"","ncst_content_audit_display":false,"ncst_backToTopFlag":"","footnotes":""},"categories":[1],"tags":[5],"class_list":["post-24492","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized","tag-_from-newswire-collection-279"],"displayCategory":null,"acf":{"ncst_posts_meta_modified_date":null},"_links":{"self":[{"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/posts\/24492","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/comments?post=24492"}],"version-history":[{"count":1,"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/posts\/24492\/revisions"}],"predecessor-version":[{"id":24497,"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/posts\/24492\/revisions\/24497"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/media\/24493"}],"wp:attachment":[{"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/media?parent=24492"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/categories?post=24492"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/design.ncsu.edu\/industrial-design\/wp-json\/wp\/v2\/tags?post=24492"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}