Extract podcast corpus and rewrite career wiki pages

Author: alexeygrigorev

_people/16rahuljain.md

@@ -15,4 +15,4 @@ Rahul has over 12 years of experience in data and engineering, and he's been a m
 
 ## Podcast Discussions
 
-- [Data Engineering Leadership: Scale ETL to ELT, Build Robust Data Platforms & Teams]({{ '/podcasts/data-engineering-leadership-and-modern-data-platforms/' | relative_url }}). Related topics: [data engineering]({{ '/wiki/data-engineering/' | relative_url }}), [career growth]({{ '/wiki/career-growth/' | relative_url }}), career switch.
+- [Data Engineering Leadership: Scale ETL to ELT, Build Robust Data Platforms & Teams]({{ '/podcasts/data-engineering-leadership-and-modern-data-platforms/' | relative_url }}). Discussed: Rahul''s Career Path: From ETL Developer to IoT Data Platform Lead; ETL Foundations to Big Data and Open Source Tooling; Data Engineering Leadership: Stakeholder Management & Prioritization; Technical Credibility: Hands-on Management and Code-Level Involvement. Related topics: [data engineering]({{ '/wiki/data-engineering/' | relative_url }}), [career growth]({{ '/wiki/career-growth/' | relative_url }}), career switch.

_people/aaishamuhammad.md

@@ -18,4 +18,4 @@ Aaisha is a self-taught bioinformatician, machine learning engineer and data sci
 
 ## Podcast Discussions
 
-- [How to Teach Yourself Bioinformatics & ML: Project-First Learning, Resources, and MLOps]({{ '/podcasts/learning-machine-learning-self-taught-bioinformatics/' | relative_url }}). Related topics: bioinformatics, [machine learning]({{ '/wiki/machine-learning/' | relative_url }}), self-learning.
+- [How to Teach Yourself Bioinformatics & ML: Project-First Learning, Resources, and MLOps]({{ '/podcasts/learning-machine-learning-self-taught-bioinformatics/' | relative_url }}). Discussed: Guest Overview: Aaisha — self-taught bioinformatician, ML engineer, scientific; Early Learning & Homeschooling: Python, web development, and flexible study; Choosing What to Learn: prioritization, filtering, and avoiding FOMO; Open Curricula: OSSU pathway for bioinformatics. Related topics: bioinformatics, [machine learning]({{ '/wiki/machine-learning/' | relative_url }}), self-learning.

_people/abouzarabbaspour.md

@@ -2,12 +2,11 @@
 layout: person
 title: "abouzarabbaspour"
 summary: "abouzarabbaspour's DataTalks.Club podcast discussions, organized for topic exploration."
-source_url: "https://datatalks.club/people/abouzarabbaspour.html"
 podcast_episodes: ["theme-park-crowd-modeling-to-tesla-full-stack-data-engineering"]
 ---
 
 # abouzarabbaspour
 
 ## Podcast Discussions
 
-- [From Theme Parks to Tesla: Building Data Products Through Applied ML and Full-Stack Engineering]({{ '/podcasts/theme-park-crowd-modeling-to-tesla-full-stack-data-engineering/' | relative_url }}). Related topics: [machine learning]({{ '/wiki/machine-learning/' | relative_url }}), [MLOps]({{ '/wiki/mlops/' | relative_url }}), [data engineering]({{ '/wiki/data-engineering/' | relative_url }}), [LLMs]({{ '/wiki/llms/' | relative_url }}), [data science]({{ '/wiki/data-science/' | relative_url }}).
+- [From Theme Parks to Tesla: Building Data Products Through Applied ML and Full-Stack Engineering]({{ '/podcasts/theme-park-crowd-modeling-to-tesla-full-stack-data-engineering/' | relative_url }}). Discussed: Early Career: Software Engineering to Data Science; Academic Path: Professional Doctorate & TU Berlin; Research Partnerships: Industry Projects and Applied Research; Efteling Insights: Theme Park Tech and Experience Design. Related topics: [machine learning]({{ '/wiki/machine-learning/' | relative_url }}), [MLOps]({{ '/wiki/mlops/' | relative_url }}), [data engineering]({{ '/wiki/data-engineering/' | relative_url }}), [LLMs]({{ '/wiki/llms/' | relative_url }}), [data science]({{ '/wiki/data-science/' | relative_url }}).

_people/adamsroka.md

@@ -17,4 +17,4 @@ Dr. Adam Sroka, Head of Machine Learning Engineering at Origami Energy, is an ex
 
 ## Podcast Discussions
 
-- [KPI Design & Metrics Strategy: Prioritize Impact, Avoid Vanity Metrics, and Prove ROI]({{ '/podcasts/ml-engineering-kpis-and-metrics-strategy/' | relative_url }}). Related topics: [machine learning]({{ '/wiki/machine-learning/' | relative_url }}), [leadership]({{ '/wiki/leadership/' | relative_url }}), [data science]({{ '/wiki/data-science/' | relative_url }}), product management, strategy, [metrics]({{ '/wiki/metrics/' | relative_url }}), [communication]({{ '/wiki/communication/' | relative_url }}).
+- [KPI Design & Metrics Strategy: Prioritize Impact, Avoid Vanity Metrics, and Prove ROI]({{ '/podcasts/ml-engineering-kpis-and-metrics-strategy/' | relative_url }}). Discussed: Guest Introduction & Career Path; From Physics PhD to Data Science and Reinforcement Learning; Moving into Consultancy: BI, Dashboards, and Client Workshops; Laser Research, Ray-Tracing Tools, and Early RL Experiments. Related topics: [machine learning]({{ '/wiki/machine-learning/' | relative_url }}), [leadership]({{ '/wiki/leadership/' | relative_url }}), [data science]({{ '/wiki/data-science/' | relative_url }}), product management, strategy, [metrics]({{ '/wiki/metrics/' | relative_url }}), [communication]({{ '/wiki/communication/' | relative_url }}).

_people/adityagautam.md

@@ -15,4 +15,4 @@ Aditya Gautam is an AI researcher and engineer whose work spans industrial innov
 
 ## Podcast Discussions
 
-- [The Future of AI Agents]({{ '/podcasts/s23e03-future-of-ai-agents/' | relative_url }}).
+- [The Future of AI Agents]({{ '/podcasts/s23e03-future-of-ai-agents/' | relative_url }}). Discussed: Aditya’s from embedded systems to AI; Enterprise AI research and adoption gaps; AI reliability in legal and healthcare; Specialized models and agent governance. Related topics: [mlops]({{ '/wiki/mlops/' | relative_url }}), [search]({{ '/wiki/search/' | relative_url }}), aditya embedded systems, embedded systems ai, enterprise ai research, ai research adoption.

_people/admondleekinlim.md

@@ -16,4 +16,4 @@ Admond is a data scientist, writer, and speaker who wants to empower people with
 
 ## Podcast Discussions
 
-- [Build a Personal Brand: Publish on LinkedIn/Medium, Grow Audience, Monetize with Online Courses]({{ '/podcasts/personal-brand-for-data-professionals/' | relative_url }}). Related topics: personal brand, [career growth]({{ '/wiki/career-growth/' | relative_url }}), monetization.
+- [Build a Personal Brand: Publish on LinkedIn/Medium, Grow Audience, Monetize with Online Courses]({{ '/podcasts/personal-brand-for-data-professionals/' | relative_url }}). Discussed: Guest Introduction and Career Journey; Personal Brand Defined: Purpose and Positioning; Starting an Online Presence: First Steps and Mindset; Publishing on Medium and LinkedIn: Formats and Best Practices. Related topics: personal brand, [career growth]({{ '/wiki/career-growth/' | relative_url }}), monetization.

_people/agitajaunzeme.md

@@ -15,4 +15,4 @@ Agita has designed a career spanning DevOps/DataOps engineering, management, com
 
 ## Podcast Discussions
 
-- [From DevOps to Data Engineering: Automation, Open Source & Volunteering for Career Transitions]({{ '/podcasts/from-devops-to-data-engineering-automation-open-source-volunteering/' | relative_url }}). Related topics: [open-source]({{ '/wiki/open-source/' | relative_url }}), [data engineering]({{ '/wiki/data-engineering/' | relative_url }}), [software engineering]({{ '/wiki/software-engineering/' | relative_url }}), [practices]({{ '/wiki/practices/' | relative_url }}), [career transition]({{ '/wiki/career-transition/' | relative_url }}), DevOps.
+- [From DevOps to Data Engineering: Automation, Open Source & Volunteering for Career Transitions]({{ '/podcasts/from-devops-to-data-engineering-automation-open-source-volunteering/' | relative_url }}). Discussed: Guest Welcome & Interview Agenda; Career Beginnings: Trade School, Web Design, First Programming; Education & Bootcamp: Computer Science, Accenture, C++; Transition to DevOps: Configuration Management & Early Automation. Related topics: [open-source]({{ '/wiki/open-source/' | relative_url }}), [data engineering]({{ '/wiki/data-engineering/' | relative_url }}), [software engineering]({{ '/wiki/software-engineering/' | relative_url }}), [practices]({{ '/wiki/practices/' | relative_url }}), [career transition]({{ '/wiki/career-transition/' | relative_url }}), DevOps.

_people/aishwaryajadhav.md

@@ -15,4 +15,4 @@ With over 4 years of industry experience as a Machine Learning Engineer, I have
 
 ## Podcast Discussions
 
-- [Applying Computer Vision Research to Building Production-Ready AI Systems for Real-World Deployment]({{ '/podcasts/from-computer-vision-research-to-autonomous-driving-ai/' | relative_url }}). Related topics: [computer vision]({{ '/wiki/computer-vision/' | relative_url }}), [academia]({{ '/wiki/academia/' | relative_url }}), autonomous driving, [MLOps]({{ '/wiki/mlops/' | relative_url }}), [LLMs]({{ '/wiki/llms/' | relative_url }}), [production]({{ '/wiki/production/' | relative_url }}), [career growth]({{ '/wiki/career-growth/' | relative_url }}), [career transition]({{ '/wiki/career-transition/' | relative_url }}).
+- [Applying Computer Vision Research to Building Production-Ready AI Systems for Real-World Deployment]({{ '/podcasts/from-computer-vision-research-to-autonomous-driving-ai/' | relative_url }}). Discussed: Guest Bio & Career Overview: Finance to Self-Driving AI; Morgan Stanley: Big Data Engineering & Transition to ML; Carnegie Mellon: Research Focus & Computer Vision Projects; AI Guide Dog: Mobile Navigation for the Visually Impaired. Related topics: [computer vision]({{ '/wiki/computer-vision/' | relative_url }}), [academia]({{ '/wiki/academia/' | relative_url }}), autonomous driving, [MLOps]({{ '/wiki/mlops/' | relative_url }}), [LLMs]({{ '/wiki/llms/' | relative_url }}), [production]({{ '/wiki/production/' | relative_url }}), [career growth]({{ '/wiki/career-growth/' | relative_url }}), [career transition]({{ '/wiki/career-transition/' | relative_url }}).

_people/aleksanderkruszelnicki.md

@@ -16,4 +16,4 @@ An almost archaeologist. Ex Delivery Hero product manager turned co-founder in t
 
 ## Podcast Discussions
 
-- [Build a Data Consulting Business: Customer Validation, User Interviews & Pricing Strategy]({{ '/podcasts/data-consulting-business-pricing-and-client-acquisition/' | relative_url }}). Related topics: consulting, [entrepreneurship]({{ '/wiki/entrepreneurship/' | relative_url }}), [freelance]({{ '/wiki/freelance/' | relative_url }}), [data strategy]({{ '/wiki/data-strategy/' | relative_url }}), business development, [career growth]({{ '/wiki/career-growth/' | relative_url }}), [startups]({{ '/wiki/startups/' | relative_url }}).
+- [Build a Data Consulting Business: Customer Validation, User Interviews & Pricing Strategy]({{ '/podcasts/data-consulting-business-pricing-and-client-acquisition/' | relative_url }}). Discussed: Career Journey & Archaeology Origin Story; Data Stack as a Service: Market and Technical Limits; Transition to Consulting: Early Projects and First Customer; Customer Validation Techniques for Pre-Product Ideas. Related topics: consulting, [entrepreneurship]({{ '/wiki/entrepreneurship/' | relative_url }}), [freelance]({{ '/wiki/freelance/' | relative_url }}), [data strategy]({{ '/wiki/data-strategy/' | relative_url }}), business development, [career growth]({{ '/wiki/career-growth/' | relative_url }}), [startups]({{ '/wiki/startups/' | relative_url }}).

_people/aleksandermolak.md

@@ -17,4 +17,4 @@ My name is Aleksander Molak. Friends call me Alex. My mission is to translate co
 
 ## Podcast Discussions
 
-- [Causal Inference for Real-World ML: Uplift Modeling, Counterfactuals, Treatment Effects & LLM Integration]({{ '/podcasts/causal-inference-for-machine-learning/' | relative_url }}). Related topics: [causal inference]({{ '/wiki/causal-inference/' | relative_url }}), [LLMs]({{ '/wiki/llms/' | relative_url }}), [machine learning]({{ '/wiki/machine-learning/' | relative_url }}).
+- [Causal Inference for Real-World ML: Uplift Modeling, Counterfactuals, Treatment Effects & LLM Integration]({{ '/podcasts/causal-inference-for-machine-learning/' | relative_url }}). Discussed: Episode Introduction; Guest Intro: Aleksander Molak & book overview; Career highlights and dyslexia prediction project; Causal advocacy: democratizing causal thinking. Related topics: [causal inference]({{ '/wiki/causal-inference/' | relative_url }}), [LLMs]({{ '/wiki/llms/' | relative_url }}), [machine learning]({{ '/wiki/machine-learning/' | relative_url }}).