About
Welcome! We are ACME (Assimilation, Control, Modeling, and Estimation) Research Labs, housed in Aerospace Engineering Department at Indian Institute of Technology Madras (IIT-M).
At ACME Research Labs, we believe grand challenges demand grand tools. Just like the name suggests, we build the "ACME toolkit" for the future—methods that let us assimilate data seamlessly, control complex systems with confidence, model phenomena at scale, and estimate the unknown with precision. From engines to orbits, from turbulence to autonomy, our vision is to tackle problems that matter for science, technology, and society—turning clever ideas into robust solutions that can stand the test of real-world uncertainty.
Figure 1: Research overview showing the intersection of controls, computational sciences, and data-driven methods.
Open Opportunities
If you resonate with our vision and are interested to join our group. Please reach out to Aniketh via email and indicate your interest on topics you find interesting. Some open positions in our group are listed below:
- Postdoctoral Fellow: We are looking forward for postdoctoral fellows—with a Ph.D. in the field of control & dynamical system theory, or in compuatational sciences—to join us on our journey to develop digital twin frameworks for complex aerospace applications. [See IPDF Opportunities]
- Ph.D. students: We are actively looking for students to pursue their doctoral thesis on cutting edge topics at the intersection of control theory, data-driven modeling and optimization theory. Some projects would include
- Uncertainty quantification in reduced-order models
- Modeling multi-scale systems using reduced-order models
Control, guidance, navigation of aero & space systems.
ACME Research Lab encourages prospective students to apply for PMRF. Ensure to check eligibility before applying.
- Project Staff: We are looking for a project staff to join us on multiple projects. Interested candidates should be excited to learn in a dynamic environment while working with in close collaboration with the team. Some broad project areas are:
- Use of Neuromorphic cameras (event-based cameras) for object detection and tracking in aerospace applications.
- Developing reduced-order models from sparse sensor measurements to model flow field in a mini-gas turbine engine.
- Internships: We accept interns via the IIT-M's Summer research fellowship for both Masters and Bachelors students. [See IITM-SFP]
Latest News
- June-Nov 2025: Aniketh will be teaching AS 5401: Data-Driven Modeling of Complex Aerospace Systems and Fluid Flows
- Jun 2025: Aniketh travels to DRDO's Research Center Imarat for technical discussion on digital twins and their applications in aerospace industry.
- Mar 2025: Aniketh gives a talk at the National Defence College (NDC), Delhi. The talk is on the topic Next-Generation Force Multipliers: Big Data, Predictive AI & Digital Twins.
- Feb 2025: Aniketh visits Indian Space Research Organization's Satellite Application Center (ISRO-SAC). The visit included technical discussion and a talk on Data Assimilation using Reduced-Order Models for Nowcasting.
- Jan-May 2025: Aniketh will be teaching AS 3050: Flight Dynamics II
- Sep 2024: Aniketh joins the Aerospace Engineering Department at IIT-Madras
Research
Our Mission
To advance the state-of-the-art in aerospace control systems through innovative research, exceptional education, and meaningful industry partnerships that address critical challenges in autonomous flight, space exploration, and defense applications.
Research Themes
Nonlinear Flow Analysis and Control (details: pdf1, pdf2, pdf3)
Harnessing advanced methods in fluid dynamics and control theory to actively manipulate flows, analyze stability, improve efficiency, and enable smarter aerospace designs. Example project: Active flow control to suppress transition to turbulence.
Data-Driven Modeling and Digital Twins (details: pdf1, pdf2)
Building reduced-order models that blend physics with machine learning to create fast, accurate digital twins for complex aerospace systems. Example project: Data-driven reduced order models for fluid flows, engines, etc.
Autonomous Space Systems (details: pdf)
Developing adaptive control strategies to enable resilient, coordinated operations in challenging space environments. Example project: Adaptive control of satellite formation flying.
Space Safety and Sustainability (details: pdf)
Leveraging AI and computational tools to detect, classify, and track orbital debris, supporting long-term sustainability of space operations. Example project: Space-debris classification.
Multi-Sensor Data Fusion (details: pdf)
We develop algorithms that combine information from multiple sensors to deliver accurate and reliable state estimates in demanding environments. By fusing diverse data sources, our work enhances guidance, navigation, and control for high-dynamic aerospace applications—where split-second decisions and resilience to uncertainty are critical.
Research Philosophy
- Progress is Collective – Breakthroughs come from collaboration and shared insight, not isolated brilliance.
- Persistence Beats Perfection – Steady effort and resilience drive research forward more than flashes of inspiration.
- Teamwork is the Multiplier – Diverse skills and perspectives amplify what any individual can achieve.
- Growth Through Challenge – We embrace a growth mindset, treating obstacles and failures as opportunities to learn, adapt, and advance.
- Learning Never Stops – If we don't learn, we don't grow, if we don't grow we are not moving towards our goal
Research Facilities
- Neuromorphic cameras for event-based vision sensing in UAVs
- Mini gas turbine engine
- Hardware-in-the-loop simulation system
- High-performance computing setup
The Team
Principal Investigator
Dr. Aniketh Kalur, Assistant Professor
- Postdoctoral fellow, Oden Institute of Computational Engineering and Sciences, University of Texas at Austin, Texas, USA.
- Ph.D. in Aerospace Engineering, University of Minnesota-Twin Cities, Minneapolis, Minnesota, USA.
- M.S. in Aerospace Engineering, University at Buffalo, Buffalo, New York, USA.
- B.S. in Electronic Engineering Technology (Avionics), Vaughn College of Aeronautics and Astronautics, New York, USA.
Current Team
Hemanth Madduri
Topic: Reduced-order modeling and variational data assimilation
Current degree status: M. Tech 2nd Year
Satwik Ladi
Topic: Multi-sensor data fusion for high-dynamic applications
Current degree status: M. Tech 2nd Year
Teaching
Courses Taught
AS 3050: Flight Dynamics II
AS 5401: Data-driven modeling for complex aerospace systems and fluid flows
Course Philosophy
Our courses emphasize:
- Theory with Practice: Strong mathematical foundation coupled with hands-on implementation
- Modern Tools: MATLAB/Simulink, Python, ROS, and industry-standard software
- Real Applications: Projects based on actual aerospace systems and challenges
- Research Integration: Opportunities to work on cutting-edge research problems