Introducing the 2025 Siegel and Rubinstein PiTech PhD Impact Fellows: Our most ambitious summer yet!

Written by Kate Nicholson, PiTech Initiative Director of Programs and Partnerships

PiTech is excited to kick off another summer for the PiTech PhD Impact Fellowship— our most ambitious one yet!

The program has more than doubled in size this year, growing from 10 to 21 fellowship placements. This expansion reflects a rising recognition among students and public interest organizations of the value in bringing together cutting-edge expertise and responsible tech perspectives into the non-profit and public sectors. 

Too often, emerging tech practitioners and researchers aren’t exposed to the real-world challenges faced by the public sector. The PiTech PhD Impact Fellowship bridges that gap through a 12-week program that pairs Cornell University PhD students in technical fields with nonprofit and public sector organizations across NYC. Fellows gain invaluable real-world experience working alongside subject matter experts on high-impact technology projects, while organizations that might otherwise lack the resources for advanced technical talent, benefit from exploring emerging technologies like machine learning, data science, LLMs, human-centered design, and consumer-facing technologies such as AR/VR, IoT, and interactive agents.

The growth of the program reflects its past success and a growing recognition that society’s biggest challenges require new opportunities for collaboration between academia, government, and civil society. 

This summer, our 2025 Siegel and Rubinstein PiTech PhD Impact Fellows will undertake projects ranging from transportation and housing to education, climate resilience, and accessibility challenges. In each case, fellows work closely with their public sector and nonprofit partners to explore new ideas and strategic directions. Learn more about their projects below. 

Congratulations to our 2025 Siegel and Rubinstein PiTech PhD Impact Fellows and partners! We look forward to following your work this summer.

• Gabriel Agostini, NYC Department of Transportation
  Analyzing Citi Bike data to identify micromobility route preferences and infrastructure gaps to inform safety improvements and address gaps in urban mobility networks.

• Mohammadreza Ahmadnejadsaein, NYC Housing Authority
  Applying machine learning and regression to identify at-risk buildings within NYCHA's portfolio, while also modeling performance trends across schedule and cost metrics.

• Yuanchen Bai, Young Adult Institute (YAI)
  Personalizing speech therapy interventions and improving communication independence for people supported by YAI through analysis of augmentative and alternative communication (AAC) device usage.

• Axel Bax, NYC Department of City Planning
  Developing a methodology to identify gaps and prioritize investments in community services and facilities by analyzing their locations, investments, quality, and community board requests.

• Jonathn Chang, NYC Department of Environmental Protection
  Building AI capabilities for sound identification, license plate recognition, and vehicle owner information retrieval to automate DEP's video review process for the Noise Camera Enforcement Program.

• Erica Chiang, NYC Department of Education
  Validating use cases for AI to enhance the NYC public schools admissions experience for families, assessing risks and mitigations to align with standards and policies.

• Shuo Feng, Mayor's Office of Climate & Environmental Justice
  Designing an interactive dashboard that integrates heterogeneous NYC climate hazard data with community-submitted imagery, enabling residents to interpret current risks and explore projected climate scenarios for more informed neighborhood-level decision-making. 

• Matthew Franchi, Design Trust for Public Space 
  Analyzing NYC Open Data, community surveys, and agency documentation to develop recommendations for policy reforms that simplify requirements and streamline access to public spaces.

• Jennah Gosciak, NYC Office of Emergency Management
  Exploring how to use data and predictive analytics to help NYC Emergency Management forecast emergencies, focus on at-risk communities, and plan more effectively.

• Laura Greenstreet, Riders Alliance
  Analyzing MTA bus location data and modeling "bus bunching" patterns across NYC transit routes to identify service gaps and evaluate strategies to optimize bus service reliability and inform transit advocacy efforts. 

• Seyedeh Farnoosh Hashemi Fesharaki, Block Party
  Improving Block Party's delivery of Community Board meeting highlights and summaries through generative summarization and topic modeling techniques that turn discussions into accurate, easily digestible content for community members.

• Haesoo Kim, Clinic to End Tech Abuse (CETA)
  Improving the computer security community's understanding of generative AI's impact on interpersonal abuse by analyzing tech-abuse support consultation data and conducting experimental testing to characterize AI systems' vulnerability to exploitation. 

• Sanghee Kim, NYC Office of Technology and Innovation - Office of Data Analytics
  Conducting a time-series analysis of 311 Resolution Satisfaction Survey data to identify statistically significant changes in resident satisfaction across agencies, boroughs, and service categories; with the goal of informing data-driven recommendations for improving agency responses to 311 service requests.

• Jinsook Lee, NYC First STEM Center at Cornell Tech
  Developing a mixed-methods framework to assess and predict the district-wide impact of NYC First’s STEM centers and their programming on NYC students’ academic performance and career trajectories. 

• Meng Hui Liu, NYC Office of Technology and Innovation - Research and Collaboration
  Evaluating machine translation techniques to inform NYC procurement decisions and policies regarding adoption of machine translation tools to increase access to NYC services. 

• Khonzodakhon Umarova, New York City Council Data Team
  Applying NLP and ML techniques to detect duplicates in legislative service requests, thereby streamlining City Council legislative processes 

• Andrea Wang, JustFix and the Center for Justice Innovation
  Designing a conversational AI to help NYC tenants understand and assert their housing rights, navigate complex laws, and connect with the right resources for safe, affordable, and stable housing.

• Yadi Wang, Consumer Reports Innovation Lab
  Designing personalized and autonomous agentic AI systems that genuinely put consumers first— developing guidance to ensure that agents are respectful, loyal, and aligned with consumers' interests. 

• Olzhas Yessenbayev, Center for Family Support
  Prototyping a smart home system at CFS residences to automate specific support-staff functions, enhance daily living for residents with intellectual and developmental disabilities, and alleviate the demands on staff— paving the way for scalable, tech-enabled independent living solutions.

• Shengqi Zhu, NY Public Library
  Developing an LLM agent-based model to simulate how visitors use a library branch throughout the day, helping uncover hidden patterns and guide decisions about staffing, space, and services.

• Ke Xin Zuo, Switchbox
  Developing reinforcement learning models that capture consumer responses to alternative electric rate designs and insights into how novel peak-shaving technologies would affect the NY grid.

The PiTech PhD Impact Fellowship supports Cornell University PhD students in technical fields to participate in 12-week summer externships that advance the missions of nonprofit and public sector organizations across NYC. The program is made possible by generous gifts from the Siegel Family Endowment and Frederic & Susan Rubinstein. Learn more at pi.tech.cornell.edu/pitech-phd-impact-fellowship.