Jeyashree Krishnan

Hey there! I am Jeyashree (or JK), thank you for visiting my website. I am a Senior Machine Learning Scientist/ Engineer at Siemens AG. Over the last several years, I have built a career that sits at the intersection of science, consulting, and engineering. My background includes:

• 10 years of research in numerical simulations
• 7 years of experience in machine learning
• 5 years of experience in computational biology
• 3 years in data science consulting
• 2 years focused on ML engineering, building scalable ML applications and systems
• Over 1 year of work in technical AI safety

Currently, I work in Siemens Corporate IT, building ML products and services for the organization. I am also a visiting researcher at the Center for Computational Life Sciences, University Hospital Aachen, where I work on research topics in computational biology.

I also pursue independent research threads in adversarial ML, interpretability, and explainability. As machine learning is deployed ever more deeply in high stakes settings, from clinical workflows and genomics to critical infrastructure, the bar for trustworthy, well understood models keeps rising. Since September 2026, I have been a MATS 11.0 cohort fellow in the Biosecurity track in Berkeley, working with Manu Shivakumara and Tessa Alexanian at IBBIS (International Biosecurity and Biosafety Initiative for Science) on AI Safety and Biosecurity. Since late 2025, I have been an Apart Research Fellow, working on technical AI safety topics related to genomics with Dr. Ajay Mandyam Rangarajan, Dr. Andrea Loehr, and Dr. Jason Hoelscher-Obermaier. Since May 2026, I have been a mentor across several technical AI safety programs, including SAIGE, PRISM, and Algoverse. I co-supervise SAIGE projects on LLM manipulation with Dr. Ajay Mandyam Rangarajan and Dr. Jason Hoelscher-Obermaier. I am also a Lecturer for the Masters in Applied Data Science at the Frankfurt School of Finance and Management in Winter 2026/27.

Outside of work I enjoy running, CrossFit, books, and traveling to new countries.

Professional Expertise

In my current role at Siemens Corporate IT, I build ML products and services that teams across the organization can reliably use. My work focuses on time series foundation models, forecasting, and LLMs, with an emphasis on production-grade ML i.e. scalable pipelines, monitoring, and maintainable systems. I contribute through hands-on technical delivery including designing and implementing ML services and pipelines, improving model quality and monitoring, supporting deployment and operational stability, and reviewing technical designs and code. I also support product direction through roadmap planning, stakeholder management, and technical leadership.

Previously, I worked as a Data Science Consultant at Siemens Advanta Consulting with Dr. Ulli Waltinger, delivering data-driven solutions across domains such as Finance, Cybersecurity, Digital Twin, Healthcare, Sustainability, and more. I led cross-functional projects end to end, from problem framing and stakeholder alignment to model development and delivery. Before industry, I completed my PhD and postdoctoral research at RWTH Aachen University, at Joint Research Center for Computational Biomedicine and Aachen Institute for Advanced Study in Computational Engineering Science with Prof. Andreas Schuppert, Prof. Andrew Ewing, and Prof. Carl Ernst. My research focused on simulating biological systems and combining model-driven and data-driven methods to understand features that contribute to emergent behavior.

Tools and Technologies

My everyday work involves using a variety of tools and technologies for ML problems. Following are a bunch of tools and technologies I use in my daily work. I built this website with Node.js and Express for the backend and a mix of HTML, CSS, Bootstrap, and JavaScript for the frontend. I also use AI coding assistants and agentic coding workflows such as Claude Code, Codex, Cursor, GitHub Copilot, and Gemini CLI in my day-to-day development. I lean on agentic development methods and tooling like the BMAD-METHOD and Beads, and I regularly run three or more agent sessions in parallel using git worktrees together with tmux.

Research Work

During my postdoctoral work, I contributed to the Neuronode Project, collaborating with the Ernst Group at McGill University and the Ewing Group at Gothenburg University on computational problems related to neurodegenerative diseases. During my Ph.D., I worked on modeling phase transitions in network biology, combining elements of statistical physics with complex networks. I was a visiting researcher at the Douglas Research Institute / Montreal Neurological Institute at McGill University and the Center for Complex Systems at Utrecht University. For more details, please visit my research page.

Papers, Talks and Industry Contributions

I have had the opportunity to present my work at various international conferences, contribute to industry projects, author whitepapers, and have my research published in reputable journals, gaining valuable experience and insights along the way. Check out my talks and research pages to see more.

Hacking and Tinkering

In my spare time, I work on side projects involving coding and mathematics. I explore topics that interest me and enjoy the process of problem-solving. For more details, please visit my portfolio.

Personal Interests

Outside of work, I enjoy:

• Running: I have completed over 10 (ultra-) marathons across 6 continents.
• Traveling: I have visited over 60 countries.
• Reading: I enjoy reading across various topics.
• CrossFit: I enjoy lifting weights and doing the WODs.

For more details, please visit my adventures and blogs pages.

My CV

If you would like to learn more about my professional journey and detailed experiences, you can download my CV here (Last updated: July 2026).

Contact

You can find all my contact information and social media links on my contact page.

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