Stephanie Rebecca

About

Tue, 28 Apr 2026 23:23:32 +0000

About Stephanie Rebecca

Projects

Tue, 28 Apr 2026 23:23:32 +0000

Projects and case studies

Tuesday Pos

Tue, 28 Apr 2026 00:00:00 +0000

Things I found this week…

Carl Jung on the mountains
@kejunYing weekend project
S2Vec: learns city structure from map data alone, creates embeddings that predict income, population, emissions, even in unseen regions. Best results come when combined with satellite models like RS-MaMMUT, maps + imagery together.
Kawase Hasui woodblock prints

Tuesday Post

Tue, 28 Apr 2026 00:00:00 +0000

Things I found this week…

Carl Jung on the mountains
@kejunYing weekend project
S2Vec: learns city structure from map data alone, creates embeddings that predict income, population, emissions, even in unseen regions. Best results come when combined with satellite models like RS-MaMMUT, maps + imagery together.
Kawase Hasui woodblock prints

Friday Post

Fri, 23 Jan 2026 00:00:00 +0000

**The penguin… ** It went viral because it hit several very deep psychological points. Because animals let us talk about ourselves without ego defense. Most viral content today is driven by sparking outrage. The penguin felt so calming, a feeling - “I don’t know where I’m going. I just know it’s not there.” Existentialism. Meaning isn’t discovered by following the “correct” path; it’s created by choosing despite absurdity. For those that built identity on achieving. For those that reached milestones, and found it left them feeling empty. Water in Jungian symbolism almost always represents the unconscious; the ocean, specifically, is the collective unconscious. The penguin’s colony lives here. The ego must separate from the collective psyche or it never becomes itself.

Sunday Post

Sun, 21 Dec 2025 00:00:00 +0000

A collection of others cool and unique imprints on the world/internet…

Cool things found this week:

Barcelona, 1906. The Sagrada Família basilica in the background, 24 years into its construction.
Midwinter evening by a forest road, Dalarne (1913)
Peder Mørk Mønsted (1859–1941)
L’Empreinte de Dieu dans le monde quantique by Yves Dupont
Finding out Frank Gehry designed a yacht

Predictive Analysis in Biotech

Sat, 11 Jan 2025 00:00:00 +0000

Evaluating the mechanism of action (MOA) of therapeutic targets, specifically differentiating between upstream and downstream interventions. Systematically analysing how the position of a target within a biological pathway influences the probability of success (POS). For example, if a biotech company targets RAS mutations in pancreatic cancer but the primary oncogenic drivers occur downstream of RAS in the signalling cascade, the target is less likely to succeed in trials. Upstream targets, often involved in early signalling processes, present unique challenges and opportunities compared to downstream targets, which tend to be closer to the therapeutic outcome. Understanding these distinctions allows for a more accurate prediction of clinical trial outcomes, regulatory approval likelihood, and eventual market performance. Let’s dive into how predictive analysis reshapes biotech equities, delve into the intricacies of upstream versus downstream MOAs, and discuss how this innovative approach reshapes the investment landscape in the biotechnology sector.

Factors Influencing Probability of Success (POS)

Target Biology and MOA

Understanding the biological context of a therapeutic target is foundational. Upstream targets, like transcription factors or signalling regulators, can disrupt entire pathways but often face redundancy due to compensatory mechanisms. These targets frequently suffer from poor druggability due to structural challenges or lack of surface binding pockets. Conversely, downstream targets—closer to the disease phenotype—are more actionable, offering measurable biomarkers but posing risks of off-target effects due to their proximity to cellular machinery critical for normal functions.

Where is my flying car?

Tue, 08 Oct 2024 00:00:00 +0000

***The demonstration that no possible combination of known substances, known forms of machinery and known forms of force, can be united in a practical machine by which man shall fly long distances through the air, seems to the writer as complete as it is possible for the demonstration of any physical fact to be. —Simon Newcomb (1906) ***

J. Storrs Hall’s book ‘**Where Is My Flying Car?’ **asks why certain anticipated technologies haven’t become mainstream despite our technological capabilities. Hall uses the flying car as a metaphor to discuss innovation stagnation that has plagued since the 1970s, a period he refers to as the “Great Stagnation.”

AI Supply Chain

Thu, 03 Oct 2024 00:00:00 +0000

Last year, went down the rabbit hole on earth materials and how they fit into the theme of supply chain demand, particularly with the growth of compute required AI. Defense contracts heavily depend on lithium, especially for electronic components and warfare applications. Currently, the US mainly rely on outsourcing lithium from countries such as China and Australia.

Core Components of AI Compute

At the heart of systems are powerful computing units that require a variety of minerals and materials:

Differential Privacy application to Federated Learning

Thu, 03 Oct 2024 00:00:00 +0000

I want to talk about ***a rabbit hole I have fallen down *since reading a paper on The Promises and Predicaments of Federated Learning in Healthcare. **

Last year, I had the privilege of working with an incredible team focused on applying machine learning techniques to tackle data interoperability challenges within our healthcare system. We grappled with issues like disparate data formats, strict privacy regulations, and the sheer volume of sensitive patient information scattered across multiple institutions. These hurdles sparked my curiosity about how emerging technologies could offer solutions, ultimately leading me to delve deeper into federated learning and privacy-enhancing technologies. These challenges led me to further explore the promise of technologies, such as homomorphic encryption and differential privacy, and their integration into federated learning.

Adoptive Immunotherapy In Bone Metastases

Wed, 25 Sep 2024 00:00:00 +0000

Attachments

cancer adoptive immunotherapy in bone metastases.pdf

AI Impact Scenario Exploration

Wed, 25 Sep 2024 00:00:00 +0000

Attachments

Scenario Impact of AI.pdf

Allogeneic Cellular Immunotherapy in Primary Bone Tumours

Wed, 25 Sep 2024 00:00:00 +0000

Attachments

Poster Presentation Trial Space and Market Analysis.pdf

Ambrosia Therapeutics

Wed, 25 Sep 2024 00:00:00 +0000

Attachments

Formated Business Plan Ambrosia.pdf

Magdrive

Wed, 25 Sep 2024 00:00:00 +0000

Attachments

MAGDRIVE Valuation.pdf

The Changing Landscape of Precision Cancer Medicine

Wed, 25 Sep 2024 00:00:00 +0000

Summary of “The Changing Landscape of Precision Cancer Medicine”

This research paper explores recent advancements in precision cancer medicine, highlighting how personalized treatments are revolutionizing oncology. Key points include:

Genomic Profiling: The increasing use of next-generation sequencing to identify cancer-driving mutations and tailor treatments accordingly.
Targeted Therapies: Development of drugs that specifically target molecular abnormalities in cancer cells, improving efficacy and reducing side effects.
Immunotherapy: Breakthroughs in harnessing the body’s immune system to fight cancer, including CAR-T cell therapy and checkpoint inhibitors.
Liquid Biopsies: Advancements in non-invasive diagnostic techniques using circulating tumor DNA for early detection and treatment monitoring.
AI and Machine Learning: Integration of artificial intelligence to analyze complex genomic data and predict treatment outcomes. The paper concludes that while precision medicine has shown remarkable progress, challenges remain in terms of treatment resistance, tumor heterogeneity, and accessibility. Future directions point towards combination therapies and further personalization of treatment plans.

Attachments

AFM Thesis