Summer Undergraduate Research Fellowship
Accordion Content
With funding and support provided by the Rutgers-New Brunswick’s Chancellor’s Office, the Rutgers-New Brunswick Office for Research (NB OfR), 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.
2026 RAD Collaboratory SURF
New for summer 2026, the RAD Collaboratory SURF program is part of the larger Chancellor Signature Initiatives Summer Undergraduate Research Fellowship (CSI SURF) program. The CSI SURF program brings together two cohorts of exceptional undergraduate researchers, the RAD Collaboratory SURF fellows and the Life Sciences Alliance SURF fellows.
Although students pursue projects within their individual tracks, they take part in shared workshops, coordinated programming, peer-learning sessions, and cross-cohort networking events that cultivate a vibrant, interdisciplinary summer research community. The CSI SURF program is strengthened by its partnerships with Rutgers University Libraries, the Aresty Research Center, and academic units across Rutgers schools, whose collaboration plays a vital role in delivering high-impact training, enrichment workshops, and research support services.
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- Robot Learning, Perception and Planning
- Faculty mentor: Kostas Bekris, Computer Science, School of Arts and Sciences
- Student(s): Liam Riggs, Computer Science and Mathematics, School of Arts and Sciences, and Sidney Wai, Computer Science and Cognitive Science, School of Arts and Sciences
- Control of Large Language Models (LLM)
- Faculty mentor: Laurent Burlion, Mechanical and Aerospace Engineering, School of Engineering
- Student(s): Ali Kahn, Computer Science, School of Arts and Sciences
- Talking to Air: Designing an AI agent for Accessing and Interpreting Satellite-Based Air Pollution Data
- Faculty mentor: Xiaomeng Jin, Environmental Sciences, School of Environmental and Biological Sciences
- Student(s): Tej Patel, Electrical and Computer Engineering, School of Engineering
- Ai-PEAT: AI-based Protein Engineering AgenT for Sargassum degradation using AI-High Performance Computing interfaces
- Faculty mentor: Sagar Khare, Chemistry and Chemical Biology, School of Arts and Sciences
- Student(s): Ceiron Dushyanthan, Computer Science and Mathematics, School of Arts and Sciences
- Data for Everyone: An Open-source Time Series Generator for Accurate Energy System Models
- Faculty mentor: Robert Mieth, Industrial and Systems Engineering, School of Engineering
- Student(s): Pranav Tikkawar, Mathematics, Computer Science, and Statistics, School of Arts and Sciences, and Sonakshi Sharma, Computer Science, Data Science, and Statistics, School of Arts and Sciences
- Navigating AI Tools for Personalized Learning in Economics and Business Education
- Faculty mentor: Sonal Pandey, Agricultural, Food, and Resource Economics, School of Environmental and Biological Sciences
- Student(s): Bhavya Maheshwari, Computer Science and Economics, School of Arts and Sciences, and Aurko Hasan, Economics, School of Arts and Sciences
- Ocean Exploration with Agentic AI
- Faculty mentor: Hugh Roarty, Marine and Coastal Sciences, School of Environmental and Biological Sciences
- Student(s): Ryan Timko, Electrical and Computer Engineering and Mathematics, School of Engineering
- AI-Driven Chemical Physics and Spectrophotometric Innovations for Low-Cost Water Quality Monitoring
- Faculty mentor: Siddhartha Roy, Environmental Sciences, School of Environmental and Biological Sciences
- Student(s): Juliania Shyprykevych, Computer Science and Cognitive Science, School of Arts and Sciences, and Vinesh Uniyal, Computer Science, School of Arts and Sciences
- Encoder-decoder finite-element-based physics-informed neural networks
- Faculty mentor: Ryan Sills, Materials Science and Engineering, School of Engineering
- Student(s): Xinye Luo, Computer Science, School of Arts and Sciences
- In Silico Drug Discovery with Computational Chemistry and Artificial Intelligence (AI)
- Faculty Mentor: Chong Sun, Chemistry and Chemical Biology, School of Arts and Sciences
- Student(s): Chelsea Sisule, Chemistry, School of Arts and Sciences
- Interpretable Multimodal AI Linking Immune Synapse Imaging and Gene Expression for Precision Immunotherapy
- Faculty Mentor: Ruixiang (Ryan) Tang, Computer Science, School of Arts and Sciences
- Student(s): Joshua Li, Electrical and Computer Engineering, School of Engineering
- Object-Object Physical Interaction Prediction with Transformers
- Faculty Mentor: Jingjin Yu, Computer Science, School of Arts and Sciences
- Student(s): Tanishq Annavaram, Computer Science, School of Arts and Sciences, and Khushwanth Vudhya, Computer Science, School of Arts and Sciences
- Building data science bioinformatics tools for worldwide biology and biomedicine
- Faculty Mentor: Christine Zardecki, Institute for Quantitative Biomedicine, School of Arts and Sciences
- Student(s): Yusuf Mohammed, Electrical and Computer Engineering, School of Engineering, and Hriday Adani, Computer Science and Economics, School of Arts and Sciences
- Robot Learning, Perception and Planning
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In 2026, two CSI SURF Program Assistants will provide assistance with the programming and will guide 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
2025 RAD Collaboratory SURF
In its augural year, the RAD Collaboratory SURF program, overseen by the NB OfR, partnered with the Aresty Research Center to administer the ten week program that included programming, networking, and social events. A total of 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. For one of the projects, two faculty members co-mentored a student.
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 NB OfR, 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 presented posters about their research at the inaugural RAD Collaboratory Research Symposium on March 24, 2026.
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- AI for Good: Predictive Models for Environmentally Responsible Blue Economy Planning
- Faculty mentor(s): Ahmed Aziz Ezzat, Industrial and Systems Engineering, School of Engineering
- Student(s): Het Patel, Computer Science and Data Science, School of Arts and Sciences
- AI-Driven Pipeline Corrosion Management for Digital Twin Integration
- Faculty mentor(s): Hao Wang, Civil and Environmental Engineering, School of Engineering
- 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
- Atomistic tool for identification and characterization
- Faculty mentor(s): Ryan Sills, Materials Science and Engineering, School of Engineering
- Student(s): Pallavi Biswas, Computer Science and Data Science, School of Arts and Sciences
- Building RCSB.org software tools to enable breakthroughs in research and education
- Faculty mentor(s): Stephen K. Burley, Chemistry and Chemical Biology, School of Arts and Sciences, and Director, RCSB Protein Data Bank
- Student(s): Krish Parmar, Computer Science, School of Arts and Sciences
- Machine Learning Approaches to Climate Data Bias Correction and Downscaling
- Faculty mentor(s): Lili Xia, Environmental Sciences, School of Environmental and Biological Sciences, and Zhao Zhang, Electrical and Computer Engineering, School of Engineering
- Student(s): Charles Lee, Electrical and Computer Engineering, School of Engineering
- Mapping Local and Systemic Cell-Cell Communication in Mouse Embryogenesis: An Integrative Framework for Spatial Transcriptomics
- Faculty mentor(s): Jiekun Yang, Genetics, School of Arts and Sciences
- Student(s): Pranav Arra, Computer Science and Genetics, School of Arts and Sciences
- Never let a good crisis go to waste: AI-designed Enzymes for Sargassum deconstruction
- Faculty mentor(s): Sagar Khare, Chemistry and Chemical Biology, School of Arts and Sciences
- Student(s): Arnav Anil Kumar, Computer Science and Mathematics, School of Arts and Sciences
- Physical AI
- Faculty mentor(s): Kostas Bekris, Computer Science, School of Arts and Sciences
- Student(s): Vishal Nagamalla, Computer Science, School of Arts and Sciences, and William Zhang, Computer Science, School of Arts and Sciences
- Remote sensing of air pollution powered by AI
- Faculty mentor(s): Xiaomeng Jin, Environmental Sciences, School of Environmental and Biological Sciences
- Student(s): Atharv Jayprakash, Data Science and Cell Biology and Neuroscience, School of Arts and Sciences
- The role of astrocytes and myelin in regulating the functionality of injured neurons
- Faculty mentor(s): Assimina Pelegri, Mechanical and Aerospace Engineering, School of Engineering
- Student(s): Rohan Karamel, Computer Science and Mathematics, School of Arts and Sciences
- Transforming modeling with physics-informed neural networks
- Faculty mentor(s): Ryan Sills, Materials Science and Engineering, School of Engineering
- Student(s): Anastasia Moreno, Mechanical and Aerospace Engineering, School of Engineering
- Trustworthy and Scalable AI Model Training Through Robust Decentralized Learning
- Faculty mentor(s): Waheed Bajwa, Electrical and Computer Engineering, School of Engineering
- Student(s): Junlin Chen, Mathematics and Computer Science, School of Arts and Sciences
- Understanding social media consumption on Telegram and YouTube
- Faculty mentor(s): Venkata Rama Kiran Garimella, Library and Information Science, School of Communication and Information
- Student(s): Pranav Patil, Computer Science and Mathematics, School of Arts and Sciences
- AI for Good: Predictive Models for Environmentally Responsible Blue Economy Planning
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In 2025, four 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
