OBJECTIVES OF THE WORKSHOP:

The objective of this workshop is to create a new community of people who can think rigorously across the disciplines of evolutionary decision making & controllable inferences, ask new questions, and develop the foundations of this new scientific discipline.

ABOUT THE WORKSHOP:

The Centre for Quantitative Economics and Data Science (CQEDS), Birla Institute of Technology Mesra, Ranchi is organizing a Five-Day workshop on Learning dynamical systems and control: foundation, method algorithm and implementation (LDC-FMAID-2025). 

The Workshop is sponsored by Anusandhan National Research Foundation (ANRF) and Jharkhand council on Science, Technology and Innovation (JCST&I).  The explosion of real time dynamic data needs to be sensed and controlled in the vicinity of underlying dynamical systems. This requires theoretical and computational understanding of dynamical systems and control in learning framework to draw decision making inferences from dynamic data in physical and economical worlds. From statistical learning perspective, one of the main challenges going forward is to go beyond pattern recognition and address problems in data-driven control and optimization of dynamical processes. Our overall goal is to create a new community of people who can think rigorously across the disciplines with controllable inferences and optimal decision making, ask new questions, and develop the foundations of this new scientific discipline. 

IMPORTANT DATES: 

Last date of application: July 10, 2025, 

Date of announcement of participants: July 11, 2025,

Last date of registration: July 15, 2025.

🎯 Expected Outcomes

Participants will gain a comprehensive understanding and engage in critical exploration at the intersection of dynamical systems & control, statistical learning, and optimization, with emphasis on the following themes:

🧩 Foundations of Modeling and Learning Dynamical Systems

Two complementary paradigms will be explored:

- Model-Based Approach

Deriving dynamical systems from first principles and physics-based assumptions, followed by local extrapolation for analysis and control.

- Data-Driven Approach with Physical Insights

Leveraging physical and geometric observations to construct inverse models of unknown dynamical systems, enabling global interpolation through learning frameworks.

🔍 Dynamical Analysis and Control

- Classical Analysis:

Investigation of system properties such as well-posedness, stability, controllability, observability, and stabilization.

- Learning-Driven Analysis:

Integration of learning algorithms to infer system dynamics and control policies, structured around a loop of three interdependent learning problems:

- Learning the system dynamics

- Learning the control policy

- Learning the observation or estimation model

This loop aims to bridge the gap between model-based and learning-based paradigms in dynamical systems and control.

🔗 Bridging Paradigms: The LDC-FMAID-2025 Vision

LDC-FMAID-2025 serves as a platform to unify model-based and learning-based approaches by:

- Embedding physical and geometric constraints into learning frameworks

- Promoting hybrid methodologies that respect both theoretical rigor and empirical adaptability

🚀 Applications Across Domains

The insights and methodologies discussed have broad applicability, including but not limited to:

- Autonomous Control Systems:

Decision-making and control in robotics, drones, and intelligent agents

- Quantitative Economics:

Dynamic resource allocation, epidemic modeling, and crime control through feedback-based interventions

CALL FOR PARTICIPATION: 

‐Faculty member or postdoctoral fellow or other who is working in domain of evolutionary decision making & controllable inferences   

‐Master and doctoral students.

Prospective participants are requested to submit their CVs and a write-up (500 words) on how the workshop will contribute to their research and/or teaching output. 

Registration fee detail:

a. General Participation

• ₹3000 – Faculty members, Assistant Professors, Postdoctoral Fellows or Others

• ₹1500 – Graduate and Doctoral Students

b. BIT Mesra Participation

• ₹1500 – Faculty members, Assistant Professors,  Postdoctoral Fellows or Others

• ₹500 – Graduate and Doctoral Students

Note: BIT students are required to pay ₹500 only by selecting any one of the two available payment options. While making the payment, they must mention the appropriate remark clearly to ensure proper identification and processing

c. As part of our commitment to fostering regional academic engagement, the workshop is offering a registration fee waiver for up to 30 participants from Jharkhand. "Local participants are required to submit proof of residence in lieu of the payment receipt."

Application Link:

Registration link: https://forms.gle/2Qv4VRFrbTQQ3ccp8

Local Jharkhand Participant Link: LDC-FMAID 2025 Local Registration