Summer Undergraduate Research Fellowships

With funding and support provided by the Rutgers-New Brunswick’s Chancellor’s Office, the Office of the Vice Provost for Research (OVPR), and the Office of the Executive Vice President for Academic Affairs (EVPAA) through its Roadmaps for Collective Academic Excellence initiative, the Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory Summer Undergraduate Research Fellowship (SURF) program engages Rutgers-New Brunswick rising junior and senior undergraduate students in hands-on, in-person research projects in artificial intelligence and/or data science.

In 2025, the RAD Collaboratory SURF program, overseen by the OVPR, partnered with the Aresty Research Center to administer the ten week program that included programming, networking, and social events. In addition to weekly professional development sessions conducted in partnership with the Aresty Research Center and the Research Intensive Summer Experience (RISE) program, the RAD Collaboratory hosted a Welcome Lunch on May 30, 2025 exclusively for the RAD Collaboratory SURF students. The RAD Collaboratory, with oversight from the OVPR, hosted an Artificial Intelligence and Data Science Summer Networking Event on June 27, 2025 to introduce and strengthen interdisciplinary collaboration amongst the RAD Collaboratory SURF students and the greater RAD Collaboratory community. In addition to the Summer Symposium that was held on July 31 with the Aresty Research Center, the RAD Collaboratory SURF students will present posters about their research at the RAD Collaboratory Research Symposium to be held in Spring 2026.

Each RAD Collaboratory SURF student received a $6,000 stipend, and on-campus student housing was provided (as required) at no cost to the selected students. The cost of the stipends was shared by the RAD Collaboratory and the faculty mentor, and faculty mentors received funding to offset research supplies.

In its augural year, 15 Rutgers-New Brunswick undergraduate students, primarily from the School of Arts and Sciences and the School of Engineering, completed the RAD Collaboratory SURF program. To assist these students, 13 faculty mentors and their research teams provided oversight and direction.

The RAD Collaboratory SURF students completed the following 13 hands-on research projects in artificial intelligence and/or data science. In some cases, multiple students were assigned to the same research project. For one of the projects, two faculty members co-mentored a student.

• AI for Good: Predictive Models for Environmentally Responsible Blue Economy Planning
  • Student(s): Het Patel, Computer Science and Data Science, School of Arts and Sciences
  • Faculty mentor(s): Ahmed Aziz Ezzat, Industrial and Systems Engineering, School of Engineering

• AI-Driven Pipeline Corrosion Management for Digital Twin Integration
  • Student(s): Praneeth Damarla, Electrical and Computer Engineering and Mathematics, School of Engineering, and Nancy Zhang, Computer Science and Statistics, School of Arts and Sciences
  • Faculty mentor(s): Hao Wang, Civil and Environmental Engineering, School of Engineering

• Atomistic tool for identification and characterization
  • Student(s): Pallavi Biswas, Computer Science and Data Science, School of Arts and Sciences
  • Faculty mentor(s): Ryan Sills, Materials Science and Engineering, School of Engineering

• Building RCSB.org software tools to enable breakthroughs in research and education
  • Student(s): Krish Parmar, Computer Science, School of Arts and Sciences
  • Faculty mentor(s): Stephen K. Burley, Chemistry and Chemical Biology, School of Arts and Sciences, and Director, RCSB Protein Data Bank

• Machine Learning Approaches to Climate Data Bias Correction and Downscaling
  • Student(s): Charles Lee, Electrical and Computer Engineering, School of Engineering
  • Faculty mentor(s): Lili Xia, Environmental Sciences, School of Environmental and Biological Sciences, and Zhao Zhang, Electrical and Computer Engineering, School of Engineering

• Mapping Local and Systemic Cell-Cell Communication in Mouse Embryogenesis: An Integrative Framework for Spatial Transcriptomics
  • Student(s): Pranav Arra, Computer Science and Genetics, School of Arts and Sciences
  • Faculty mentor(s): Jiekun Yang, Genetics, School of Arts and Sciences

• Never let a good crisis go to waste: AI-designed Enzymes for Sargassum deconstruction
  • Student(s): Arnav Anil Kumar, Computer Science and Mathematics, School of Arts and Sciences
  • Faculty mentor(s): Sagar Khare, Chemistry and Chemical Biology, School of Arts and Sciences

• Physical AI
  • Student(s): Vishal Nagamalla, Computer Science, School of Arts and Sciences, and William Zhang, Computer Science, School of Arts and Sciences
  • Faculty mentor(s): Kostas Bekris, Computer Science, School of Arts and Sciences

• Remote sensing of air pollution powered by AI
  • Student(s): Atharv Jayprakash, Data Science and Cell Biology and Neuroscience, School of Arts and Sciences
  • Faculty mentor(s): Xiaomeng Jin, Environmental Sciences, School of Environmental and Biological Sciences

• The role of astrocytes and myelin in regulating the functionality of injured neurons
  • Student(s): Rohan Karamel, Computer Science and Mathematics, School of Arts and Sciences
  • Faculty mentor(s): Assimina Pelegri, Mechanical and Aerospace Engineering, School of Engineering

• Transforming modeling with physics-informed neural networks
  • Student(s): Anastasia Moreno, Mechanical and Aerospace Engineering, School of Engineering
  • Faculty mentor(s): Ryan Sills, Materials Science and Engineering, School of Engineering

• Trustworthy and Scalable AI Model Training Through Robust Decentralized Learning
  • Student(s): Junlin Chen, Mathematics and Computer Science, School of Arts and Sciences
  • Faculty mentor(s): Waheed Bajwa, Electrical and Computer Engineering, School of Engineering

• Understanding social media consumption on Telegram and YouTube
  • Student(s): Pranav Patil, Computer Science and Mathematics, School of Arts and Sciences
  • Faculty mentor(s): Venkata Rama Kiran Garimella, Library and Information Science, School of Communication and Information

Rutgers graduate assistants provided oversight for the Aresty programming and guided the RAD Collaboratory SURF students with their poster preparation:

• Shannon Hart, Psychology, School of Arts and Sciences
• Amirtha Gridihar, Industrial and Systems Engineering, School of Engineering
• Caylee Brown, Pharmacology and Toxicology, School of Graduate Studies
• Nyla Howell, Geography, School of Arts and Sciences

Please contact the Office of the Vice Provost for Research, Senior Academic Program Coordinator, Tracy Higgins (t.higgins@echo.rutgers.edu), with any questions.