Credit: Jess Campitiello/Cornell Tech Caption: Members of the Roosevelt Island community test out th

An iconic red shuttle bus ferries commuters and visitors along the winding streets of New York City’s Roosevelt Island. But this isn’t a typical sightseeing tour.

Passengers all don virtual reality headsets for an eye-opening experience – a cutting-edge blend of the physical and digital worlds, designed to engage communities in new ways through the Communal eXtended-Reality (CXR) system.

Date Posted: 9/11/2024
A color photo showing 7 new faculty members

The Cornell Ann S. Bowers College of Computing and Information Science has bolstered its faculty ranks with the addition of seven new faculty members hired during the 2023-2024 recruiting season.

The new faculty members bring expertise in areas like computer vision, robotics, generative models, causal inference, and fairness in algorithms, among others.

 
Date Posted: 8/27/2024
A color graphic with the text BURE Bowers Undergraduate Research Experience

Research takes time.

“On top of classes and extracurricular commitments, I often struggle to find enough time for research during the semester,” said James Kim ’25, a computer science and math major.

But this summer, thanks to the Bowers Undergraduate Research Experience (BURE), Kim, along with 60 of his undergraduate peers from the Cornell Ann S. Bowers College of Computing and Information Science, can give research the time it requires. In the process, Kim is discovering a career path.

Date Posted: 8/14/2024
A color graphic with the Cornell Bowers CIS and LinkedIn logos

Four faculty members and four doctoral students from the Cornell Ann S. Bowers College of Computing and Information Science are the latest recipients of annual grants from the college’s five-year partnership with LinkedIn.

This year’s award winners – the third cohort from the Cornell Bowers CIS-LinkedIn strategic partnership – will advance research in areas including algorithmic fairness, reinforcement learning, and large language models.

Launched in 2022 with a multimillion-dollar grant from LinkedIn, the Cornell Bowers CIS-LinkedIn strategic partnership provides funding to faculty and doctoral students advancing research in artificial intelligence. Awards to doctoral students include academic year funding and discretionary funds. The five-year partnership also supports initiatives and student groups that promote diversity, equity, inclusion and belonging.  

Faculty award winners

Sarah Dean, assistant professor of computer science, believes the algorithms that power social network platforms are too short-sighted. The models anticipate short-term engagement, like clicks, but fail to capture longer-term impacts, like a user’s growing distaste of clickbait headlines or educational content that no longer serves their skillset. In “User Behavior Models for Anticipating and Optimizing Long-term Impacts,” Dean seeks to develop models that can anticipate long-term user dynamics and algorithms that can optimize long-term impacts. 

Michael P. Kim, assistant professor of computer science, will explore fairness in algorithmic predictive models in his project, “Prediction as Intervention: Promoting Fairness when Predictions have Consequences.” Today's predictive algorithms can influence the outcomes they are meant to predict. For instance, algorithms may help job seekers connect with relevant companies, making it more likely for them to get hired by the company. Kim's project aims to understand the potential for such algorithms to cause harm by overlooking individuals from marginalized groups, but also to promote new opportunities through deliberate predictions.

Jennifer J. Sun, assistant professor of computer science, aims to leverage large language models (LLMs) to process text data from veterinarians at Cornell College of Veterinary Medicine. The goal of her project, “Learning and Reasoning Reliably from Unstructured Text,” is to use LLMs to develop a system to synthesize the text data into actionable insights for improving animal care, such as predicting surgical complications. Sun aims to develop algorithms that could scale to industry-level applications, for example, for use in tasks such as skills matching and career recommendations.

Daniel Susser will explore misalignments between the ways different actors conceptualize and reason about privacy-enhancing technologies (PETs) – statistical and computational tools designed to help data collectors process and learn from personal information while simultaneously protecting individual privacy. In “Navigating Ethics and Policy Uncertainty with Privacy-Enhancing Technologies,” Susser will develop shared frameworks for data subjects, researchers, companies, and regulators to better reason, deliberate, and communicate about the use of PETs in real-world contexts. 

Doctoral student award winners

Zhaolin Gao, a doctoral student in the field of computer science advised by Wen Sun and Thorsten Joachims, aims to improve methods used in reinforcement learning from human feedback (RLHF), which is used to train large language models. Gao’s project is called “Aligning Language Model with Direct Natural Policy Optimization.”

Kowe Kadoma, a doctoral student in the field of information science advised by Mor Naaman, studies how feelings of inclusion and agency impact user trust in artificial intelligence. In her project, “The Effects of Personalized LLMs on Users’ Trust,” Kadoma will expand on existing research that finds LLMs often produce language with limited variety, which may frustrate or alienate users. The goal is to improve LLMs so that they produce more personalized language that matches users’ language style.

Abhishek Vijaya Kumar, a doctoral student in the field of computer science advised by Rachee Singh, will develop systems and algorithms to efficiently share the memory and compute resources on multi-GPU clusters. The goal of the project, called “Responsive Offloaded Tensors for Faster Generative Inference,” is to improve the performance of memory and compute bound generative models. 

Linda Lu, a doctoral student in the field of computer science advised by Karthik Sridharan, will explore privacy through “machine unlearning,” a paradigm to give users the ability to delete any personal data that could be used to train large language models. Lu’s project is called “A New Algorithmic Design Principle for Privacy in Machine Learning.”

By Louis DiPietro, a writer for the Cornell Ann S. Bowers College of Computing and Information Science.

 

Date Posted: 7/23/2024
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Aditya Vasistha creates culturally aware artificial intelligence technologies to improve social and economic outcomes for underserved communities, including more than 250,000 community health workers, low-literate people and blind users of social media.

“I design technologies for the left behind – the 85% of the world limited to a low income, who are working in oppressive conditions and living in societies with deep social, digital and health inequities,” he said.


Date Posted: 7/10/2024
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Using experiments with COVID-19 related queries, Cornell sociology and information science researchers found that in a public health emergency, most people pick out and click on accurate information.

Although higher-ranked results are clicked more often, they are not more trusted, and misinformation does not damage trust in accurate results that appear on the same page. In fact, banners warning about misinformation decrease trust in misinformation somewhat but decrease trust in accurate information even more, according to “Misinformation Does Not Reduce Trust in Accurate Search Results, But Warning Banners May Backfire” published in Scientific Reports on May 14.


Date Posted: 7/09/2024
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The Center for Teaching Innovation (CTI) supports Cornell University teaching community members, from teaching assistants and postdoctoral fellows to lecturers to professors, with a full complement of individualized services, programs, institutes, and campus-wide initiatives.

Date Posted: 7/02/2024
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Computer scientist and health equity scholar Emma Pierson has an impact well beyond academia, publishing widely in such outlets as The New York Times, FiveThirtyEight and Wired. Pierson is an assistant professor at Cornell Tech, the Jacobs Technion-Cornell Institute and Technion.

Date Posted: 7/02/2024
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Sterling Williams-Ceci is a doctoral student in information science from Ithaca, New York. She earned her B.A. in psychology and the College Scholar Program at Cornell University and now studies the influence of AI on people’s thoughts about societal issues under the guidance of Michael Macy and Mor Naaman at Cornell and Cornell Tech, respectively.

Date Posted: 7/02/2024
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Portobello, a new driving simulator developed by researchers at Cornell Tech, blends virtual and mixed realities, enabling both drivers and passengers to see virtual objects overlaid in the real world.

This technology opens up new possibilities for researchers to conduct the same user studies both in the lab and on the road – a novel concept the team calls “platform portability.”

Date Posted: 6/27/2024

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