Freshman Sriman Achanta applies AI expertise to real-world research
"Complex research requires really deep analysis, something AI is great at, so I learned how to apply it in my work," said Sriman Achanta, a first-year computer science student at Virginia Commonwealth University's College of Engineering.
Achanta is already contributing in the Biomagnetics Laboratory led by Ravi Hadimani, Ph.D., in Mechanical & Nuclear Engineering. His focus: using AI and high-performance computing to build better brain stimulation models that can inform clinical research.
From high school prototyping to lab-grade AI
Before arriving at VCU, Achanta's team advanced a machine learning project to design and test a 3D-printed transradial prosthetic with independent finger movement and sensory feedback. The work earned third place in the robotics category at the Regeneron International Science and Engineering Fair, the world's largest STEM competition for high school students.
Learn more about Regeneron ISEF.
AI + HPC for patient-specific neurostimulation models
At VCU, Achanta runs head-model simulations on the High Performance Research Computing Core, processing MRI data from autistic and nonautistic patients. The goal is to derive subject-level magnetic characteristics to study how Transcranial Magnetic Stimulation (TMS) interacts with different brains-a step toward more precise stimulation paradigms.
"Computer programming is a great way to solve problems," he said. "I've been doing it since middle school, but in high school I realized the depth of problems I can solve with just programming is limited. Complex research requires really deep analysis, something AI is great at, so I learned how to apply it in my work."
Technical work is only half the job: communicate
The Todd Allen Phillips Center for Medical Sciences at Mills E. Godwin High School helped Achanta build range-combining biomedical curiosity with AI chops and frequent presentations. "By the time our team got to ISEF, we'd presented about 40 times," he said. "It made us comfortable enough to tailor the presentation for our audience."
That practice carries into the lab. "At the VCU College of Engineering, this is immensely helpful. I could be working with a researcher who doesn't know about magnetics or TMS but who does understand mechanical or electrical engineering concepts, so I know to shift our discussion to a perspective they are more familiar with."
Building with teams: HyperRAMS VIP
Achanta also contributes to HyperRAMS (Robotics Autonomous and Mechatronics Systems), a Vertically Integrated Project where undergraduates and graduate students tackle real problems alongside faculty. It's a practical setting to align AI, software, and hardware decisions against shared milestones.
Why this matters for research teams
- Early integration of motivated undergraduates expands a lab's experimentation bandwidth and idea flow.
- AI + HPC pipelines let teams test hypotheses at scale-e.g., MRI-to-field modeling for TMS-while maintaining reproducibility.
- Cross-disciplinary translation (mechanical, electrical, magnetics, AI) reduces friction in design reviews and accelerates iteration.
- Frequent presenting builds clarity, improves peer feedback, and surfaces edge cases sooner.
Access counts
"The research opportunities that immediately presented themselves, even as a freshman, surprised me," said Achanta, who grew up in Richmond aware of VCU's research focus. "I was able to schedule a meeting with Dr. Hadimani and leave with an opportunity to work in his lab."
He also credits consistent guidance from researchers like Radhika Barua, Ph.D., assistant professor of mechanical and nuclear engineering. Meanwhile, friends at other universities are still waiting to get into labs. "VCU and the College of Engineering do a much better job of trusting students," he said, "and giving them a chance to take part in important research that moves science forward."
For practical approaches to applying AI in labs and institutes, see AI for Science & Research.
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