Manini Banerjee

Systems Designer & Research Engineer making environmental complexity legible and actionable.

COMPUTATIONAL ECOLOGY:

BIOPOD Co.
ECOLOGY · INFRASTRUCTURE · SYSTEMS
Designing deployable ecological infrastructure for wetland restoration based on environmental research.

Ecological AI

PREDICTION · INTERFACE · DATA
A Decision-Support System for Targeted Ecosystem Restoration.

Algorithmic Morphogenesis

BIO-COMPUTATION · DATA MATERIALIZATION
inscribing real-time human neurological data (EEG) into living algal morphology using phototactic actuation

HARDWARE & INTERFACES:

Threads

EDGE ML · HARDWARE · TEXTILES
Sentient Surfaces + Edge ML on Textiles. Human-AI Symbiosis through Ubiquitous Computing.

S(kin)-orb
HAPTICS · BIOSENSING · AFFECTIVE COMP. A bio-digital interface translating electromyographic (EMG) signals into haptic feedback for remote affective communication.

Vermiform

COMPONENT · SOFT ROBOTICS · WEARABLE
Bio-mimetic architectures for wearable computing.

Chito-bot
BIOCOMPOSITES · TRANSIENT ELECTRONICS
Investigating material compliance and structural integrity in bio-composite hexapods.

STRATEGIC SYSTEMS:

PFV

MOBILITY · ECOLOGY · SYSTEMS

Autonomous Mobility as Urban Bio-Infrastructure.

Aero

SENSING · MATERIALS · DATA
Developing robotic material systems for localized air-quality sensing and pollutant sequestration through embedded environmental intelligence.

Bio - intelligence
COPMUTATION · SYSTEMS · BIOLOGY
Exploring biological computation as an alternative model for system intelligence and control.

Algorithmic Morphogenesis

Inscribing neurological data (EEG) into living matter using phototactic actuation.

PROBLEM
Current HCI (Human-Computer Interaction) translates human intention into digital actions; systems of permanence without presence.

RESPONSE

Algorithmic Morphogenesis is a
"Bio-Autographic Interface" a system that functions like a biological record player/encoder.

LOGIC

This system uses light to translate human cognition into living algal density.

GOAL

To move beyond screen-based visualization and achieve material inscription, where internal human states (focus, memory, stress) physicalize into a living, breathing morphology.

ROLE

Role: Bio-Computation, Research & Concept, Hardware + Wetware

PROJECT SPECS:

Input: Real-time EEG (Muse Headset / Alpha & Beta Waves)

Actuation: Optical Projection System (DLP/LED Light Field)

Medium: Chlamydomonas reinhardtii (Single-celled Green Algae)

Mechanism: Positive/Negative Phototaxis via Channelrhodopsin

Code: Python (Signal Processing) + Arduino (Hardware Control)

System Architecture -> Hardware and Wetware Integration

INPUT
Hardware: Muse Headset (4-channel EEG) via Bluetooth.

Context: User engages in a 5-minute verbal narration.

Protocol: Real-time data streaming using pylsl (Lab Streaming Layer) to synchronize EEG time-series data with audio inputs.

TRANSLATION
Signal Processing: Raw EEG data is denoised and filtered to isolate frequency bands:
Theta (4-7 Hz)
Alpha (8-12 Hz)
Beta (13-30 Hz)
Gamma (30-45 Hz).

Affective Computing: Custom Python scripts calculate real-time cognitive indices.

OUTPUT
A custom 2-axis robotic assembly. The "Record Plate" rotates over time (t), while the "Arm" extends radially based on the Memory Index (r).

A 550nm LED (optimal for C. reinhardtii phototaxis) at the tip of the arm modulates brightness based on Arousal.

The robot physically "plots" the cognitive state onto the petri dish, guiding the algae to swim into the high-intensity zones, biologically developing the data graph.

Computational Pipeline: From raw signal processing to kinematic control of the record player arm. The system maps 'Memory' to spatial coordinates and 'Arousal' to light intensity which guides the algal growth.

Oganism Collaborator: Chlamydomonas reinhardtii

SENSOR

The algae possesses an "eyespot" (stigma) rich in channelrhodopsin: a light-gated ion channel.

ACTUATOR

When exposed to specific light wavelengths, the channel opens, triggering electrical signals that alter flagellar beating. This causes Phototaxis: the physical movement toward or away from light.

ENCODING

By controlling the light field via EEG data, we hijack this survival mechanism to "steer" the algae into specific densities, effectively printing a high-resolution image of the user’s brainwaves using the organisms themselves.

Temporal Resolution -> Time-lapse of phototactic migration over 10 minutes. Algae density shifts from uniform to patterned distribution.

Morphological Results -> istinct cognitive states produce distinct biological patterns. High-arousal states ('Fear') create dense, sharp clustering, while low-arousal states ('Nostalgia') create diffuse, gradient distributions.

System Calibration -> High-Resolution Optical Testing with portrait images to test movement of the algae to produce higher resolution imagery

Process:

Micro-Actuation: Real-time observation of C. reinhardtii clustering in response to light stimuli.

Works Referenced: