Maneet Chatterjee
 Email: maneet2018@gmail.com | 2023meb045.maneet@students.iiests.ac.in

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More about me: Blog | Coursework | Ongoing Projects

I am a third-year undergraduate in Mechanical Engineering at Indian Institute of Engineering Science and Technology Shibpur with a deep interest in Robotics, Artificial Intelligence and its applications. My work spans robotic manipulation, computer vision, IoT architectures, and simulation-based control, with hands-on experience in ROS, Isaac Sim, PyBullet, Blender, and embedded systems. Recently, I've been exploring Reinforcement Learning and SLAM in robotics.

I recently completed a Research & Development (R&D) Internship at Synopsys working with Vinod Singh Rao and Gopal Sharma in the Synopsys Innovation Group (SIG). My research focused on IoT, digital twins, computer vision and robotic manipulations.

Previously, I was a Research Assistant at IIEST Shibpur with Dr. Sudip Ghosh, working on photovoltaic cells and their use in hydrogen production for small scale industries.

I am a passionate photographer and spend time clicking pictures around in my city (Kolkata) in my leisure time. I also love reading about finance and geopolitics. I also play football and cricket.

I am always open to collaborations and discussions. Please feel free to reach out!

Other: Achievements | Fun/Favorites

  Recent News
     [Oct 25] First Technical Paper "Framework for Digitalization of Brownfield Deploymentsusing IT-OT Integration and Digital Twins", with Synopsys, accepted at AIIoT 2025! [LinkedIn]
     [Oct 25] Our research work at Synopsys was presented at the prestigious Ansys(part of Synopsys) TechCon Conference, Pittsburgh, USA! [LinkedIn]
     [Oct 25] Paper "Beyond CNNs: EfficientMamba Powered Sequence Learning and Curriculum-Guided Domain Adaptation for Fossil Classification" accepted at InGARSS 2025! [LinkedIn]
     [Jul 25] Completed summer internship at Synopsys - SIG! Worked on IT-OT integration, robotics and computer vison. [LinkedIn]
     [Apr 25] Received the prestigious IEEE Geoscience and Remote Sensing Society Travel Grant of US $1,550.0 to present at IGARSS 2025. [LinkedIn]
     [Mar 25] Paper "EEMAMBA: A Hardware-Aware Energy-Efficient State-Space Model for EUROSAT Classification" accepted at IGARSS 2025! [LinkedIn]
     [June 24] First-author paper published in IEEE Xplore! [LinkedIn]
  Publications
DigitalTwin

Framework for Digitalization of Brownfield Deploymentsusing IT-OT Integration and Digital Twins
Gopal Sharma, Maneet Chatterjee, Harshaditya Punera, Vinod Singh Rao, Aniruddha Mukhopadhyay
To be presented at AIIoT 2025

efficientmamba

Beyond CNNs: EfficientMamba Powered Sequence Learning and Curriculum-Guided Domain Adaptation for Fossil Classification
Angshuman Roy, Anuvab Sen, Samyajit Das, Maneet Chatterjee, Jayanta Paul
The 2025 IEEE India Geoscience and Remote Sensing Symposium (InGARSS) 2025

EEMAMBA

EEMAMBA: A Hardware-Aware Energy-Efficient State-Space Model for EUROSAT Classification
Maneet Chatterjee, Anuvab Sen, Subhabrata Roy
The International Geoscience and Remote Sensing Symposium (IGARSS) 2025

SNN

ExoSpikeNet: A Light Curve Analysis Based Spiking Neural Network for Exoplanet Detection
Maneet Chatterjee, Anuvab Sen, Subhabrata Roy
IEEE 13th International Conference on Communication Systems and Network Technologies (CSNT) 2024, 802-807

  Experience
R&D Intern
May 2025 - July 2025
Synopsys
Pune, India
Worked with Vinod Singh Rao and Gopal Sharma in Synopsys-Special Innovation Group (SIG). Developed a real-time digital twin of a 6-axis robotic manipulator, integrating a low-latency data streaming pipeline for synchronized state transfer between the physical system and simulation. Employed computer vision to enable and evaluate diverse robotic manipulation tasks within the Isaac Sim–based physics-aware simulation environment.
Research Assistant
Aug 2024 - Dec 2024
IIEST Shibpur
Kolkata, India
Worked with Prof. Sudip Ghosh on the system-level design and performance analysis of solar-powered hydrogen electrolysis systems, integrating photovoltaic sources with alkaline/PEM electrolyzers. Designed and optimized DC power conditioning and energy models using real-world irradiance data to estimate hydrogen yield and evaluate system efficiency.