Anuruddha Bhattacharjee

I am an incoming Assistant Professor in the Department of Mechanical and Materials Engineering at the University of Alabama at Birmingham (UAB), where I will join the faculty in Fall 2026 and establish a research program focused on intelligent robotic systems for minimally invasive healthcare applications. My work spans the design and dynamics of wireless and miniature robotic systems, including modular and soft robotic platforms; perception and state estimation; and control and autonomy for operation in complex physiological environments.

I recently completed my postdoctoral training in the IMERSE Lab at the Johns Hopkins Laboratory for Computational Sensing and Robotics (LCSR), advised by Dr. Axel Krieger. My research focused on wireless millirobots, magnetic surgical tools, and intelligent control systems for minimally invasive procedures and targeted drug delivery. I also collaborated with Dr. Yancy Diaz-Mercado on multi-robot actuation and control strategies. In parallel, I led a robotics team in the AIMD Laboratory within the Hopkins Extreme Materials Institute (HEMI), where I developed robotic automation systems for high-throughput materials characterization and AI-driven materials discovery.

I received my Ph.D. in Mechanical Engineering from Southern Methodist University, where I worked in the BAST Lab under the guidance of Dr. MinJun Kim and Dr. Aaron T. Becker. My doctoral research focused on the design, dynamics, and motion planning of reconfigurable modular robots. I also developed bioinspired soft millirobots and studied their locomotion in complex fluidic environments in collaboration with Dr. Henry Fu.

Prior to graduate school, I served as a Lecturer in the Department of Mechanical Engineering at Sonargaon University in Dhaka. I earned my B.Sc. in Mechanical Engineering from Bangladesh University of Engineering and Technology (BUET).

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Research

My research lies at the intersection of robotics and healthcare, with a focus on developing intelligent robotic systems for minimally invasive diagnosis, therapy, and intervention. I integrate robotic design, perception, actuation, and control to create technologies that can safely navigate, interact with, and operate within complex physiological environments. My approach combines miniaturized mechanical design with wireless magnetic actuation, sensing and perception, and real-time autonomous control to expand the capabilities of clinicians and enable new approaches to diagnosis and treatment.

I envision a future where wireless and miniaturized robotic systems can safely reach and interact with regions of the body that are inaccessible to conventional instruments, reducing invasiveness and improving procedural precision. Realizing this vision requires advances in robotic design, localization, autonomy, and control. Miniature robots operate in highly constrained and dynamic environments, where tissue interactions, physiological motion, and fluid flow create significant challenges for tracking, navigation, and precise control.

To advance this vision, I am pursuing the following research directions:

• Robotic Design and Dynamics: How can we design robotic systems that safely operate in confined and dynamic physiological environments? My work explores wireless robotic tools, modular robotic systems capable of task-specific assembly and reconfiguration, bioinspired soft robots, and the underlying dynamics that govern robot-environment interactions in complex anatomical spaces.


• Perception and State Estimation: How can miniature robots be reliably localized and tracked when sensing is limited, noisy, or intermittent? My research investigates computer vision, medical imaging integration, localization, tracking, and state estimation methods for robotic systems operating in complex physiological environments.


• Control and Autonomy: How can robots perform precise and reliable tasks in the presence of uncertainty, disturbances, and complex environmental interactions? My work focuses on wireless magnetic actuation, feedback control, planning, and the integration of learning-based and model-based approaches to enable autonomous medical robotic systems.

I am actively looking for motivated PhD students who are excited about working at the intersection of mechanical engineering, robotics, and healthcare. If you are interested in building robotic systems that can one day operate inside the human body, I would love to hear from you.

Prospective Students

I am actively recruiting PhD students in Mechanical Engineering at the University of Alabama at Birmingham (UAB) for Fall 2026 and Fall 2027. Students interested in medical robotics or minimally invasive healthcare technologies are encouraged to reach out.

If you are interested in joining my group, please email me your CV, transcripts, and a brief description of your research interests at bhattacharjee.anuruddha@gmail.com.

Publications

The publication list below includes published, accepted, and under-review journal and conference papers. A complete and up-to-date list of published work is also available on Google Scholar.

^† Co-first authors, * Corresponding authors
First-author papers are highlighted.

Journal Articles

We present here the Artificial Intelligence in Materials Design Laboratory (AIMD-L), an automated, high-throughput facility for characterizing the microstructure and properties of structural metals and ceramics, with an emphasis on materials in extreme environments.

The system presented in this work automates the full workflow of laser-driven micro-flyer impact testing, including flyer detection and alignment, laser triggering, data acquisition, and parameter and result logging. With this system, thousands of high-quality experiments can be conducted per day with minimal human supervision.

This work presents wireless modular millirobots with autonomous navigation, tissue penetration, and on-demand docking/undocking for targeted drug delivery in a heart phantom under pulsatile flow.

This work presents magnetic modular cubes with six-face magnetic encoding and a multiplex workspace that enable coordinated 2D assembly, 3D structure formation through vertical stacking, and multimodal locomotion under shared global magnetic control.

This work presents a transformer-based imitation learning framework with goal conditioning, relative action outputs, and automatic contrast dye injections to enable generalizable soft robotic guidewire navigation in an aneurysm targeting task.

This work presents magnetically actuated modular millibots capable of autonomous self-assembly, wall climbing, and closed-loop navigation using a vision-based feedback controller that integrates a harmonic traveling salesman problem (HTSP) solver with motion dynamics for obstacle-aware, deterministic self-assembly.

This work presents magnetically actuated cuboid robots capable of self-assembly, pivot-walking locomotion, and vision-based closed-loop 2D navigation with path planning in mazes.

This work presents magnetically actuated, uniform rod-like soft robots, along with their numerical modeling and propulsion performance in viscous and constrained fluidic environments, including a human aneurysm model.

This work introduces a novel nested electromagnetic coil system and a singularity-resolving controller for precise closed-loop control of magnetic robots, achieving sub-millimeter precision in trajectory tracking of a PillCam™ and a permanent magnet robot.

This work presents a vision-guided closed-loop control method for self-assembling magnetic modular cubes into user-defined 2D polyomino shapes using uniform magnetic fields and boundary-assisted interactions across multiple length scales.

This work presents a bacteria-inspired, magnetically actuated rod-like soft robot capable of swimming and boundary rolling in highly viscous fluids, with experimentally validated and simulated propulsion dynamics under low Reynolds number conditions.

This work presents a scalable modular robotic platform with programmable assembly–disassembly of magnetic cubes into 2D polyomino shapes using open-loop control and motion planning, demonstrating robust performance across varied length scales.

This work presents open-loop manipulation of snowman-shaped soft microrobots under a uniform rotating magnetic field.

This work presents a low-cost millirobot that is simple in design, easy to fabricate, highly scalable, and can be used as modular sub-units within complex structures for large-scale manipulation.

This paper presents a robust control framework combining UNet-based localization, A* planning, and a sliding mode controller with a disturbance observer (SMC-DOB controller) for multi-coil electromagnetic actuation of millirobots in pulsatile cardiac flow.

This paper presents a control framework that remains accurate and stable under low frame-rate fluoroscopic imaging by combining a nonlinear model predictive control (NMPC) framework that directly outputs coil currents, an analytically differentiable magnetic field model based on Zernike polynomials, and a Kalman filter to estimate the robot state.

This work introduces a semi-autonomous control strategy for an untethered magnetic suture needle for robotic suturing tasks in bladder repair surgery, experimentally validated through suturing on tissue-mimicking gel phantoms.

Presents a novel controller for robust waypoint tracking in magnetic robots, avoiding singularities using field-based planning and optimal current control.

Introduces a vision-based automation framework for precise control of flyer targets in high-throughput laser-driven impact experiments.

Enumerates all reachable configurations of magnetic modular cubes for self-assembling polyomino and polycube shapes under uniform magnetic fields.

Introduces an adaptive control strategy to track the motion of a biologically-inspired alginate artificial cell under external magnetic actuation.

Demonstrates programmable 2D motion and collaborative assembly of magnetic cuboid robots under uniform rotating magnetic fields with boundary-assisted control.

Presents a rod-like soft robot actuated magnetically in free space and constrained environments, with numerical modeling and experimental propulsion validation.

Proposes feedback control strategies for heterogeneous Janus particles with controllable 3D magnetic locomotion in fluid environments.

Numerical investigation of heat exchanger performance enhancement by optimizing the helix angle of continuous helical baffles.

Conducts a CFD study on turbulent mixed convection flow in pipes, analyzing thermal and velocity profiles under different boundary conditions.

Investigates thermal performance of finned versus plain tube bundles in shell-and-tube heat exchangers using CFD simulations.

Simulates transient MHD mixed convection in an L-shaped enclosure filled with ferrofluid, highlighting effects on heat transfer and fluid flow.

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