"The code isn't working... oh, I forgot a semicolon."
Every programmer has experienced this moment. But in my lab, the story is different.
"The sensor isn't responding... maybe yesterday's humidity is affecting it?"
This is the reality of computer science research dealing with physical materials.
My Research Field: The Intersection of Digital and Physical
In HCI (Human Computer Interaction), which I specialize in, we go beyond traditional keyboards and mice to make fabrics, wood, and metals themselves become interfaces.
For example:
- Smart Fabrics: Sensors embedded in clothing detect body movements
- Tangible Interfaces: Controlling digital information by manipulating physical objects
- Interactive Materials: Developing new materials that respond to touch
In these research areas, digital logic and physical laws intertwine in complex ways.
The First Wall: The Collapse of the "Debugging" Concept
Code World vs Physical World
// Bug cause: clear
if (user.age > 18) {
// ← This was wrong!
allowAccess();
}
Meanwhile, in physical systems:
Sensor values: 500 yesterday, 320 today... why?
- Humidity change (65% → 78%)
- Temperature change (22℃ → 25℃)
- Material aging
- Minute wire degradation
- Human hand temperature and moisture
Causes cannot be identified, cannot be reproduced, correction methods are unclear — this is the reality of physical systems.
Actual Experience
Last month, a perfectly functioning fabric prototype with pressure sensors suddenly stopped responding. After 3 days of investigation, the culprit was "static electricity." As the lab became drier, static electricity was affecting the sensor circuits.
In software, you can handle exceptions with "try-catch," but there's no "try-catch" in the physical world.
The Second Wall: The Nightmare of Reproducibility
A World Where "Same Conditions" Don't Exist
In software development, reproducibility is taken for granted:
- Same code → Same result
- Same input → Same output
- Bug report → Definitely reproducible
But in physical systems:
"We used the same cotton fabric for the experiment, so why are the results different?"
Upon investigation:
- Minute differences in weaving: Thread tension varies depending on machine condition
- Different preprocessing: Type of detergent, water hardness, drying time
- Storage environment: Humidity, temperature, UV accumulation
- Measurement conditions: Experimenter's hand temperature, grip strength, contact angle
There is no such thing as the "same" material in this world.
Battle with Statistics
To fight this uncertainty, we deploy statistical weapons in full force:
- Multi-sample verification (minimum 20 samples)
- Noise filtering (moving average, Kalman filter)
- Machine learning correction (prediction models considering environmental variables)
- Dynamic threshold adjustment (changing judgment criteria according to environment)
Yet even then, 100% stability cannot be achieved. The physical world is inherently probabilistic.
The Third Wall: The Complexity Called Interdisciplinarity
Computer science knowledge alone cannot create physical systems.
Required Knowledge Domains
- Materials Engineering: Fiber structure, metal fatigue, plastic degradation
- Electronics Engineering: Circuit design, noise countermeasures, EMC (electromagnetic compatibility)
- Physics: Mechanics, thermodynamics, electromagnetism
- Mechanical Engineering: Manufacturing processes, tolerance design
- Design: Usability, ergonomics
- Psychology: Tactile cognition, behavioral analysis
Difficulty of Collaboration with Experts
When talking with experts in each field, the absence of a common language becomes a major barrier.
Electronics engineer: "Impedance matching is..." Materials engineer: "Crystal structure anisotropy is..." Me: "...Sorry, could you explain that more simply..."
True interdisciplinary research also requires skills as a translator.
The Fourth Wall: Desperately Different Time Scales
Software Development Rhythm
Modern software development is ultra-fast:
- Code change → Compile (seconds)
- Test execution (minutes)
- Deploy (tens of minutes)
- Feedback (hours)
With CI/CD pipelines, you can release multiple times a day.
Physical System Development Rhythm
Meanwhile, in physical systems:
- Design change → Prototype creation (days to weeks)
- Material procurement (weeks)
- Experiments and measurements (days to weeks)
- Data analysis (weeks)
- Result interpretation (months)
It's not uncommon for a single hypothesis verification to take months.
Dismantling the PDCA Cycle
The PDCA cycle valued in business doesn't function in physical research:
- Plan: Can be planned similarly to digital ✅
- Do: Executable despite constraints ✅
- Check: Significantly delayed due to measurement difficulties ❌
- Action: Difficult to judge what should be improved ❌
Especially in the Check (verification) and Action (improvement) phases, the complexity of the physical world shows its fangs.
The Fifth Wall: Complexity of Measurement
Clarity of the Digital World
user_count = 1247 # Clear value
response_time = 156.7 # Accurate to milliseconds
Ambiguity of the Physical World
Pressure sensor values: 487, 502, 493, 501, 488, 495...
"Average is 496, so 496 is the correct value" Really?
Is this variation:
- Sensor noise?
- Actual physical phenomena?
- Measurement system problem?
- Environmental factors?
In physical measurements, distinguishing noise from signal is the greatest challenge.
Why We Continue: The Irreplaceable Nature of Physical Sensation
VLM Progress and Physical Sensation
With the advent of ChatGPT and GPT-4V, AI can "see" images and "understand" text. However, AI lacks physical sensation:
- The warmth of wood texture
- The coldness and weight of metal
- The softness and elasticity of fabric
- The texture and sound of paper
These bodily sensations are uniquely human capabilities.
Future Interfaces
What our research aims for is to fuse this physical sensation with digital experience:
- Haptic Technology: Immersive experiences through tactile feedback
- Ambient Interfaces: The environment itself becomes a computer
- Embodied Interaction: Intuitive operation utilizing physicality
These can never be realized through purely digital approaches.
The Essence of Research: What Lies Beyond Limitations
Research is about pushing current technological limitations one step forward.
In research dealing with physical materials, these "limitations" are multi-layered:
- Constraints of physical laws
- Constraints of material properties
- Constraints of manufacturing technology
- Constraints of human perception
We break through these constraints with the power of computers to create new experiences. That is our challenge.
Finally: The Value Beyond Difficulties
Computer science research dealing with physical materials is indeed full of difficulties:
- The concept of debugging doesn't apply
- Ensuring reproducibility is extremely difficult
- Vast interdisciplinary knowledge is required
- Development cycles are overwhelmingly long
- Measurement and evaluation are complex
However, beyond these difficulties lies unique value that can never be obtained through purely digital research.
No matter how much AI progresses, experiences in the physical world will continue to be special for humans. Enriching those experiences and opening new possibilities is the significance of our research.
Confronting physical constraints and exploring digital possibilities. I believe this challenge is what will create the next generation of interfaces.