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Northwestern University

Faculty Spotlights

AI@NU has periodical Faculty Spotlights in its weekly newsletters, feauturing instructors who work with AI. The following faculty members have been highlighted:

Ankit AgrawalAnkit Agrawal

Research Professor, Electrical and Computer Engineering, McCormick School of Engineering

Question: Can you describe your research focus and interests, and how you utilize or develop AI in your work?

Answer: I specialize in interdisciplinary AI and big data analytics via high-performance data mining, based on a coherent integration of high-performance computing and data mining to develop customized AI solutions for big data problems with real-world impact in various scientific and engineering disciplines, such as materials science, healthcare, social media, and bioinformatics. Particularly, over the last decade, I have been intently engaged in contributing and rapidly advancing the nascent field of materials informatics (AI for materials) and have successfully led several large-scale materials informatics projects, e.g., I am co-leading the AI group at the Center for Hierarchical Materials Design (CHiMaD), a $60 million NIST-sponsored center of excellence. Please see for my present and past projects by research area, along with team members and collaborators.

Question: How have collaborations with other Northwestern researchers or faculty impacted your work? Or, what connections would you like to establish with other Northwestern faculty/researchers?

Answer: My work and its interdisciplinary impact would not have been possible without support from the university, funding agencies, my mentors, and numerous collaborators. In particular, I've learned a lot from my lab director and former postdoctoral mentor (Prof. Alok Choudhary) and am still learning. I also routinely collaborate with Northwestern faculty from materials science and engineering, mechanical engineering, chemistry, and am also affiliated with the International Institute for Nanotechnology (IIN). Recently, I've started a new collaboration with the Feinberg School of Medicine. As an interdisciplinary AI researcher, I am always interested in exploring new collaborations with domain scientists to develop customized AI solutions to accelerate their workflows and assist them in making more informed decisions.

Question: What AI research outcomes would you like to share with the AI@NU community?

Answer: In addition to our 100+ AI/ML publications, we have also developed and released several AI-based tools and open-source software for the broader research community, available at and 


Mohammed AlamMohammed Alam

Assistant Professor of Instruction, Computer Science, McCormick School of Engineering; Deputy Director, Master of Science in AI

What is intelligence? Mohammed Alam’s research has been focused on answering this question. His artificial intelligence (AI) journey started with a sci-fi-fueled obsession with robots and has developed into studying game theoretic approaches and human decision-making.

Alam’s doctoral research studied ways to predict events by utilizing techniques based on a phenomenon known as the “Wisdom of Crowds.” He’s currently working with researchers from Northwestern’s McCormick School of Engineering, Kellogg School of Management, Pritzker School of Law, School of Communication, and the Weinberg College of Arts and Sciences to study ways to understand social movements on the web toward the UN's 17 Sustainable Development Goals (SDGs). Specifically, researchers are looking at chatter on platforms such as social media to detect, analyze, and characterize behavior and actions of large groups of people who share a common sense of purpose to contribute toward the SDGs.

To develop AI in his work, Alam tries to break the problem down into smaller components. Each smaller problem distills down to a decision point, where there is a link between the problem and a decision. This mapping helps him understand how decisions combine to form the outcome of the original problem. Through his current research, funded by the Roberta Buffett Institute for Global Affairs, he hopes to be able to explore what fundamental principles serve as the building blocks of that decision space.

Alam is currently collaborating with the following faculty members: V.S. Subrahmanian, Brayden King, Daniel W. Linna Jr., Aaron Shaw, and Rob Voigt; and the following students: Smiti M. Singrodia (pursuing PhD at Pritzker), Simon Zouki (pursuing Master of Science in AI), and Gautam Iruvanti (pursuing Master of Science in AI). Alam believes broad collaboration in fields such as computer science, psychology, neuroscience, philosophy, sociology, robotics, and ethics are beneficial to ensure a well-balanced and responsible approach to AI. To connect with him, please reach out.


James LeeJames Lee

Associate University Librarian for Academic Innovation; Associate Professor, Medill School

Question: Can you describe your research focus and interests, and how you utilize or develop AI in your work?

I am an information science and interdisciplinary researcher focusing on (1) techniques to adapt machine learning models to study mixed (and frequently chaotic) text, manuscript, and image datasets, (2) social network analysis of digital media, and (3) data visualization strategies to display high-dimensional AI models.

Much of my work has used machine learning methods applied to large historical library-based text corpora (such as Google Books or HathiTrust, among others) to study a wide range of topics, including Shakespearean texts, the history of climate change as recorded in digitized historical archives, social and political movements in the 21st century on social media, the science of science, and how uncertain or ambiguous language patterns are deployed in scientific literature.

I am currently completing two books under contract: the first uses multimodal ML models to study the intertwined histories of climate change and colonialism in multiple text, image, film, and map archives, and the second focuses on how language has been used to shape emotional and rational discourse on social media networks. These research interests have led me to some surprising and fascinating new areas of collaboration. For example, in the domain of biomedical informatics, I have adapted some of my methods to assist clinicians in measuring the degree of hedging or uncertain language patterns in electronic health records in pediatrics and neurology. 

Methodologically, much of my work has focused on developing a “Model of Models” technique, supported by the Andrew W. Mellon Foundation, which aggregates multiple algorithms run in parallel to investigate research questions using multiple modeling strategies in concert, and then displays the output of the parallel modeling process in human-interpretable interactive visualizations that enables non-technical collaborators to annotate and label results.

Question: How have collaborations with other Northwestern researchers or faculty impacted your work? Or, what connections would you like to establish with other Northwestern faculty/researchers?

Much of my research has been collaborative in nature, and to be honest my most successful projects have employed a team science model with partners from multiple, very distinct disciplines working together to address a common research question. For example, the Mellon Foundation has supported my efforts to develop genuinely interdisciplinary research projects on cross-cutting problems that call for cooperation between the sciences, humanities, social sciences, and professional fields.

In these interdisciplinary projects, I have used the “Model of Models” parallel AI modeling approach as a discipline-agnostic technique that can be adapted to fit the research paradigms of traditionally very different fields. So for example, one Mellon-supported project investigated the scientific literature surrounding COVID and previous pandemics to identify recurring patterns in the basic science community’s response to public health crises. Some of our collaborators required a confirmatory, hypothesis testing approach, whereas other collaborators relied on exploratory data analysis. Part of the objective of the project demonstrated that AI methods are flexible enough to accommodate these different disciplinary modes of making plausible arguments.

In my new administrative role at Northwestern as the Associate University Librarian for Academic Innovation, I am responsible for expanding this vision of collaborative team research, particularly by articulating a new vision for how AI can define the future of the Libraries at Northwestern. I aim to use AI as a catalyst to build new academic collaborations and partnerships with Northwestern’s colleges and schools, centers, departments, and other units, specifically by applying and developing new methods of digital scholarship and data science.

In this spirit of interdisciplinary connection at the heart of my work, I am searching for new partners and intellectual collaborators who are interested in working with a new vision of the Libraries driven by AI but grounded in our foundation of expansive digital collections and dataset access.

My commitment to collaborative interdisciplinary research is also built into the structure of my academic appointment. My administrative appointment is in the University Libraries, but my tenure home and academic appointment is in the Medill School of Journalism, Media, and Integrated Marketing Communications. My joint position between Medill and the Libraries can serve as a technical and methodological bridge between the units, particularly with the Knight Lab, the Local News Initiative, and other areas where AI can advance Medill’s research mission.


Duri LongDuri Long

Assistant Professor, School of Communication

Increasing public interest in and use of AI demands improved resources for its widespread understanding by the general public. Duri Long is a human-centered AI researcher interested in issues surrounding AI literacy and human-AI interaction.

Drawing on the learning sciences, design research, and cognitive sciences, Long’s research looks to how humans interact and learn as a way of informing the design of public AI literacy interventions as well as the development of AI that can interact naturally and improvise creatively with people in complex social environments.

Along with collaborators at Georgia Tech, Long recently received an NSF AISL grant (DRL 2214463) to design embodied, creative museum learning experiences with the Museum of Science and Industry, Chicago. The team will design and build a set of museum exhibits to foster AI literacy and develop theory on how visitors learn about AI in informal settings.

With work related to developing creative AI, designing interactive learning experiences, and incorporating AI in performance and public art, Long is on the AI@NU Committee and affiliated with the Center for Human-Computer Interaction + Design. In her first year at Northwestern, she is eager to establish collaborations with faculty in Computer Science, Learning Sciences, the Segal Design Institute, and within the School of Communication in Performance Studies and Radio/Television/Film.


Hatim RahmanHatim A. Rahman

Assistant Professor, Management and Organizations, Kellogg School of Management

Question: Can you describe your research focus and interests, and how you utilize or develop AI in your work?

Answer: My research investigates how artificial intelligence, undergirded by algorithms, is impacting the nature of work and employment relationships in organizations and labor markets. Broadly, I approach the development and use of AI with a lens at the intersection of management, sociology, and work. My published research, for example, examines how digital labor platforms' use of sophisticated algorithms is changing the nature of control and the way people work. For this research, I primarily use qualitative data and complement it with natural language processing. In new research, I examine how to empower more adults without college degrees to obtain higher-paying STEM jobs created by AI and new technologies. In particular, in light of the way AI and new technology is changing the way we work, I am interested in understanding the situated social, behavioral, and organizational factors influencing the reskilling process for adults without a college degree.

 Question: How have collaborations with other Northwestern researchers or faculty impacted your work? Or, what connections would you like to establish with other Northwestern faculty/researchers?

Answer: Currently, a PhD student (Jodie Koh) and I are collaborating with researchers at Northwestern Medicine to examine the development of AI systems for people in low- and middle- income countries who often lack access to medical care. This collaboration exemplifies the strength of the AI community at NU. Researchers are at the forefront of developing AI that can have huge implications for society, and we are teaming up with them to provide our expertise in examining the organizational factors that we hope will ultimately lead to more sustainable, beneficial practices in developing AI in healthcare and other organizations.

In general, I would love to collaborate with other Northwestern faculty/researchers who have shared or complimentary interests/skills, as I truly believe a collective effort yields much more insightful and impactful research.


James ThomasJames D. Thomas

MD, FASE, FACC, FESC, Professor of Medicine (Cardiology), Northwestern Medical Group

An applied math major who nearly went into astrophysics, James Thomas has applied the principles of physics and engineering throughout his career in medicine to extract more information from echocardiograms and to allow earlier, more precise diagnoses. Thomas first started working with AI in 2015 when approached by a startup

using machine learning techniques to guide echocardiogram interpretation which he felt could impact the field in fundamental ways. 

His collaboration with Bay Labs, (now Caption Health), led to the development of Caption Guidance, which provides turn-by-turn guidance so echo studies are intelligible for diagnoses by ultrasound novices. The FDA authorized the Caption Guidance approach with breakthrough status following a Northwestern-led study that demonstrated nurses could obtain diagnostic quality for left ventricular size and function in over 98% of cases with no prior ultrasound training. The algorithm was named one of the Top 100 Inventions of 2021 by Time Magazine.

In 2018, Patrick McCarthy and the Bluhm Center for Cardiology formed the Center for AI in Cardiovascular Disease which now has a multitude of projects underway. This also provided funding for a dedicated one-year master's program where Thomas works closely with the CS+X program to give cardiologists, surgeons, and trainees a rigorous grounding in the principles of AI and machine learning. He also collaborates regularly with NU researchers across disciplines including Aggelos Katsaggelos and his image processing group, John Rogers for wearable and implantable devices, and Gregory Wagner for computation fluid dynamics.

One of Thomas’s multi-decade passions has been mathematically modeling the cardiovascular system from simple parameter models to multiscale fluid-structure interaction models. He encourages anyone interested in the space to reach out.

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