Hi There on Theo Christiaanse, PhD

Interoperable versus integrated process

Wed, 30 Jul 2025 22:46:00 -0700

The following text is an open-ended discussion on interoperable and integrated models of housing delivery. I discuss the use of digital technologies, and barriers faced by industry to improve quality while increasing productivity.

The meaning of interoperable is that various parties can work together and transition information, materials, and project states to one another without the loss of time and information. Integrated processes bring all the parties to the table and work through solutions together. The issue I’ve encountered is that most people can agree that integrated solutions do provide higher quality outcomes but whole project is more fragile and requires a large degree of trust. If a particular set of functions is performed by one party in a unique way when that party departs from the process it will be hard to replace that party with another. We don’t see integrated project delivery being widely adopted because of this fact.

Common sense BIM

Tue, 13 Aug 2024 00:00:00 +0000

Imagine going to the kitchen, opening the fridge and taking what’s there to make a three-course dinner meal. Many would struggle, outcomes would be poor, and you would be misrable during the process.

Now, imagine you plan ahead. You find recipes online, make a shopping list, buy all the ingredients, and organize them in the fridge. You pre-chop some ingredients, plan the timing of each dish, plan your counter and stove space, coordinate with your partner, and make sure the dishwasher is empty. – You even pin the recipes on the wall for easy reference.

BIM? BIM BIM! (resolving the BIM acronym)

Fri, 12 Jul 2024 00:00:00 +0000

Going through the literature and exploring the world of BIM. I keep running into various uses of the BIM acronym. My sense is that its makes learning about BIM and understanding what BIM is so much harder. My goal with this article is to inform: provide context on the use of the BIM acronym and, resolve some issues for some. A second goal with this article is also to get feedback what other practitionairs think, and how we can articulate what BIM is, and what it isn’t.

Communication; Use of technical language

Wed, 17 Apr 2024 00:00:00 +0000

I was asked, “How do we communicate projects that contain lots of technical terms and language?”

The use of technical language is useful when communicating with experts. There is a certain efficiency when we use this language as each word captures lots of background knowledge, and you can communicate with the speed of a hammer gun, instead of a hammer and nail. It’s much faster and less verbose.

However, when we want to communicate our research it makes sense to leave the technical language to the side and use plain-spoken English. And, getting to the heart of the project which is how the study was conducted, and the impact of the results.

Product development: Releasing the MVP of the HOT2000 tool

Tue, 26 Mar 2024 00:00:00 +0000

Hot2000 is a tool used by energy advisors in Canada to help homeowners make decisions on energy retrofits and qualify for federal incentives. However, this tool is only available for Windows. As a Mac user, I saw the need to build a tool that allows people without Windows PCs to run their Hot2000 (.h2k) files quickly. Without knowing how to define success for this project, I wanted to build something quick, small and simple and put it out in the world.

Functional Programming with Python: Going from variables to lists.

Wed, 13 Mar 2024 00:00:00 +0000

Functional programming is a programming paradym that works by reducing the program to set of functions that ideally only have inputs and outputs and don’t have any internal state that changes the outcomes.

The simplist function would look something like this:

def add(a,b):
	return a+b

How on earth would you be able to create complex programs using something as simple as this? In this article we will go over a few methods that are used in functional programming using Python as the language. Python is a language that allows both precedural, declarative, object-oriented, and functional styles.

Running a LLM on a M1 Mac 8GB

Mon, 11 Dec 2023 22:00:00 +0800

Run these commands step by step in the terminal.

1. Brew install LLM

brew install llm

2. Install llm-gpt4all

llm install llm-gpt4all

3. List the models

llm models list

You should see an output like this:

OpenAI Chat: gpt-3.5-turbo (aliases: 3.5, chatgpt)
OpenAI Chat: gpt-3.5-turbo-16k (aliases: chatgpt-16k, 3.5-16k)
OpenAI Chat: gpt-4 (aliases: 4, gpt4)
OpenAI Chat: gpt-4-1106-preview (aliases: gpt-4-turbo, 4-turbo, 4t)
OpenAI Chat: gpt-4-32k (aliases: 4-32k)
OpenAI Completion: gpt-3.5-turbo-instruct (aliases: 3.5-instruct, chatgpt-instruct)
LlamaGGUF: gguf
gpt4all: all-MiniLM-L6-v2-f16 - SBert, 43.76MB download, needs 1GB RAM
gpt4all: replit-code-v1_5-3b-q4_0 - Replit, 1.74GB download, needs 4GB RAM
gpt4all: orca-mini-3b-gguf2-q4_0 - Mini Orca (Small), 1.84GB download, needs 4GB RAM
gpt4all: mpt-7b-chat-merges-q4_0 - MPT Chat, 3.54GB download, needs 8GB RAM
gpt4all: orca-2-7b - Orca 2 (Medium), 3.56GB download, needs 8GB RAM
gpt4all: rift-coder-v0-7b-q4_0 - Rift coder, 3.56GB download, needs 8GB RAM
gpt4all: em_german_mistral_v01 - EM German Mistral, 3.83GB download, needs 8GB RAM
gpt4all: mistral-7b-instruct-v0 - Mistral Instruct, 3.83GB download, needs 8GB RAM
gpt4all: mistral-7b-openorca - Mistral OpenOrca, 3.83GB download, needs 8GB RAM
gpt4all: gpt4all-falcon-q4_0 - GPT4All Falcon, 3.92GB download, needs 8GB RAM
gpt4all: gpt4all-13b-snoozy-q4_0 - Snoozy, 6.86GB download, needs 16GB RAM
gpt4all: wizardlm-13b-v1 - Wizard v1.2, 6.86GB download, needs 16GB RAM
gpt4all: orca-2-13b - Orca 2 (Full), 6.86GB download, needs 16GB RAM
gpt4all: nous-hermes-llama2-13b - Hermes, 6.86GB download, needs 16GB RAM
gpt4all: starcoder-q4_0 - Starcoder, 8.37GB download, needs 4GB RAM

5. Install run a Chat

You can play around with the different models but this one seems to work for me.

Product and Project Management

Thu, 23 Nov 2023 00:00:00 +0000

After a recent interview while hunting for jobs, an interesting topic came up, which was the difference between project and product managers. We spent a bit of time going around on the topic and I wanted to write down my thoughts here as well.

The project manager understands everything in terms of process and boundary conditions – meaning the goals and resources of the project. They fit the work that needs to be done and into those conditions set out at the start of the project. The product manager on the other hand sets the boundaries and most importantly understands the customer needs. By understanding the customer needs, They are able to know what direction to take the project and decide given the potential value creation how much to invest in each feature.

A.I. for social good and googles new weather prediction model

Thu, 16 Nov 2023 09:49:50 -0700

A.I. can help humans.

In my search to see where AI can improve our lives, I came across the “A.I. for social good” movement. It seeks to apply A.I. techniques to the benefit of 17 of the UN’s sustainable development goals.

During my research, I came across some great resources:

Nature paper on Social Good here.
Google’s list of social good projects that involve medical research, building rooflines, flood risk mapping and forest fire prediction. In 2021 Google was supporting another list of 30 projects.
Other organizations such as McKenzie have written extensively about using AI for Social Good.

googles weather model

Among the projects is a newly announced weather model. Looking deeper at Google’s newly announced weather model we can get a glimpse at how it works and how it was built.

Predicting Home Prices

Mon, 13 Nov 2023 00:00:00 +0000

Learnings

Intro

The problem at hand is to predict the home prices for various homes. In the current housing market of fall 2023, we are witnessing a significant decline in home prices. It seems weird to try and find a price point when I know prices are changing, and to values we have not seen in 10-15 years. That being said, let’s dig into this one.

Setting up TensorFlow with pip (no conda required) on M1

Sun, 05 Nov 2023 16:35:30 +0800

Run these commands step by step in the terminal.

1. Get XCODE

xcode-select --install

2. Install homebrew

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

3. Install Python

brew install python

4. Setup the Virtual Environment

python3 -m venv ~/venv-metal
source ~/venv-metal/bin/activate
python -m pip install -U pip

5. Install Tensorflow

python -m pip install tensorflow
python -m pip install tensorflow-metal

6. Run this in the terminal

python3 -c "import tensorflow as tf; print(tf.reduce_sum(tf.random.normal([1000, 1000])))"

I found this last step to be crucial as it sets a few environmental settings.

Predicting Titanic Survivors

Sat, 04 Nov 2023 00:00:00 +0000

Learnings:

Setting a learning goal
Writing a preprocessor (binary and linear)
Checking what an upper limit of accuracy should be
Checking what a simple model is in terms of accuracy

Intro

The problem at hand is to predict which passengers survived on the maiden journey of the Titanic. We are provided with a dataset with various known facts about the passengers, and whether they survived or not.

Machine Learning Projects

Sun, 15 Oct 2023 12:23:00 -0700

Here is a list of various Machine Learning Projects that I worked on to solidify my learnings.

Thoughts on public data to fight climate change

Thu, 17 Aug 2023 15:30:00 -0700

For the past couple of days, I’ve been thinking about pathways-to-net-zero and the role of public data. A deceptively simple question:

“can public data inform pathways to net zero?”

So, does the data published enable the creation of a clear pathway-to-net-zero? And, are there reliable timely metrics to adjust those plans as actions are taken?

Is there a framework out there that can use publically available information to design these pathways? If not, would it be feasible to design such a framework?

Reminder of Negative Work

Sat, 12 Aug 2023 21:48:31 -0700

The idea of being hyper-productive every day might seem like a good thing, but it can actually lead to “negative work”.

Negative work is when you think you are doing great work, but actually, it’s setting you back because you lack the clarity of mind to realize that the work you are doing will not get you closer to your goals.

Often in the past, I would think, let us go for another hour just to squeeze out a bit more. While this works for when you just need to get things done, and there is a place for it. Make more widgets and put in more time. It seems to backfire doing it long term, and especially true for creative work like writing, programming and business design, where this burnout can be very pernicious. Consistency, staying open, and clarity of thought are more important for those types of work outputs than trying to excel every day.

Summer teaching plans of active learning

Tue, 13 Apr 2021 13:00:00 -0700

Today, I will be returning to the topic of active learning. In my last post on active learning I discussed some techniques and technological solutions to incorporate active learning in the classroom. I didn’t write about how to structure active learning, an order of operations as it were. I was inspired to write about this after seeing a video from Lindau Nobel Laureate Meetings website by Carl Wieman called – “Don’t Lecture Me!”

How to get an A+ in any course - A lecture based schedule

Sun, 06 Sep 2020 09:57:30 -0700

At the end of this blog post I will give you a time table that – if you keep to it – you most certainly will pass any course, and have a high chance of acing any course in the science and engineering fields. It will work best with courses that use the lecture-assignment-exam form.

Acknowledgement; I’d like to acknowledge the youtuber Ali Abdaal

First we need to cover some core concepts that are important for you to understand. These are some concepts that you need to understand before you attempt using the timetable. By being aware of these concepts you will be able to make effective use of the proposed time table.

Key Recommendations for COVID

Thu, 20 Aug 2020 11:54:53 -0700

In a recent study some early impacts on COVID-19 have been revealed. This works key findings related to impacts and concerns reflects many aspects that I have personally experienced in the last couple of months. However, in this blog post I would like to highlight some of the key recommendations that were made by the study. Furthermore, please review my previous blog post on various resources we make use of in our group to facilitate remote work.

Publications

Sat, 01 Aug 2020 11:43:54 -0700

2021 (4)

T.V. Christiaanse, R.C.G.M. Loonen, and R. Evins (2021) Techno-economic optimization for grid-friendly rooftop PV systems – A case study of commercial buildings in British Columbia. Sustainable Energy Technologies and Assessments, 47, 101320, https://doi.org/10.1016/j.seta.2021.101320

P. Westermann, T. V. Christiaanse, W. Beckett, P. Kovacs, and R. Evins (2021). besos: Building and Energy Simulation, Optimization and Surrogate Modelling. Journal of Open Source Software, 6(60), 2677, https://doi.org/10.21105/joss.02677

A. Rahimzadeh, T. V. Christiaanse, and R. Evins “Optimal storage systems for residential energy systems in British Columbia” Sustainable Energy Technologies and Assessments vol. 45, p. 101108, June 2021, doi: https://doi.org/10.1016/j.seta.2021.101108

How to keep research alive (Remote work in the time of covid19)

Mon, 23 Mar 2020 16:22:00 -0700

First, I would like to preface this piece by saying that most of our work is related to simulation and data science. This allows us to work mostly from computers, which makes us particularly suited for remote work. If your work is mostly experimental, some of these tips might not work, however it is worth thinking about the long term. Moreover, experimental work needs design of experiments, communication, literature review, theoretical review and writing. Most of these points can be done while in self isolation.

The Process of Process

Sat, 07 Dec 2019 20:14:00 -0700

In past month I had the opportunity to go to two workshops at the learning and teaching center UVic on the teaching dossier - also called a teaching portfolio. The first was on the teaching narrative statement and the second was on the attachments - or data and evidence - that support the teaching narrative statement.

The teaching narrative statement is a description of what makes the writer a great teacher. This narrative statement should refer to data that is in the attachments. The narrative statement is a combination of a lawyer making their case and a promotional ad. I see the narrative statement as something that will show how passionate I am about teaching and mentoring. Additionally, I will support my prose with data and evidence - like a lawyer.

We have a teaching grant!

Tue, 11 Jun 2019 17:41:00 -0700

We have obtained a teaching grant to build and test new teaching materials for a second year civil engineering physics class. In the class, students learn deterministic and well understood physics based laws that are fundamental to doing energy and thermal comfort analysis for buildings. The class is taught using traditional means such as lectures and assignments, with a three tests and a final project. Each lecture is dedicated to a single physical domain, while the assignments, tests and final project selectively bring together multiple principles into a single problem. Naturally, students find those problems in which they have to bring together multiple principles to be the most difficult.

Art and craft of lecturing

Thu, 09 May 2019 20:30:00 -0700

During a workshop facilitated by Marty Wall, we learned about the art and craft of lecturing. The workshop was centered around enhancing student learning through lecturing. The students spend most of their time learning outside of the lectures given. Therefore, the lectures should be seen as a tool to enhance their learning outside of the classroom.

The craft of lecturing consists of acquired skills, while the art is the ability and awareness to enhance learning at the highest level. The craft skill set can be trained and honed over years of teaching. This skills set consists of oral/performance and organizational skills. Everyone can learn these skills and are essential to a good lecturer. The art is more difficult to obtain and comes from years of experience.

Using Bloom's Taxonomy To Write Intended Learning Outcomes

Sun, 17 Mar 2019 16:42:00 -0700

Intended Learning Outcomes (ILO) should be at the heart of each course. They describe exactly what the student will be able to do after taking the course. Doing is implied by an active verb. Bloom’s taxonomy of verbs provides us with a list of verbs that are sorted by cognitive domain. Below is a table with several examples of verbs. Creating is the highest cognitive domain, while remembering and understanding are lower on the scale.

Active learning

Thu, 21 Feb 2019 19:00:00 -0700

As part of increasing my teaching competencies I will do several workshops. The first workshop I attended was on Active learning. Active learning is about activating the student to learn. The basics involve creating the exercise in such a way the students will have to be active. The activity might involve limiting the amount of time or limit the amount of resources. Part of the process is to allow the student to take on the activity, make mistakes and learn by going through this experience.

Hi There on Theo Christiaanse, PhD

Interoperable versus integrated process

Common sense BIM

BIM? BIM BIM! (resolving the BIM acronym)

Communication; Use of technical language

Product development: Releasing the MVP of the HOT2000 tool

Functional Programming with Python: Going from variables to lists.

Running a LLM on a M1 Mac 8GB

1. Brew install LLM

2. Install llm-gpt4all

3. List the models

5. Install run a Chat

Product and Project Management

A.I. for social good and googles new weather prediction model

A.I. can help humans.

googles weather model

Predicting Home Prices

Learnings

Links

Intro

Setting up TensorFlow with pip (no conda required) on M1

1. Get XCODE

2. Install homebrew

3. Install Python

4. Setup the Virtual Environment

5. Install Tensorflow

6. Run this in the terminal

Predicting Titanic Survivors

Learnings:

links:

Intro

Machine Learning Projects

Thoughts on public data to fight climate change

Reminder of Negative Work

Summer teaching plans of active learning

How to get an A+ in any course - A lecture based schedule

Key Recommendations for COVID

Publications

2021 (4)

How to keep research alive (Remote work in the time of covid19)

The Process of Process

We have a teaching grant!

Art and craft of lecturing

Using Bloom's Taxonomy To Write Intended Learning Outcomes

Active learning