Oct 2024 – now
Machine Learning
Tools for Humanity (World), Munich
Production ML for proof of personhood at planetary scale: verify a unique human without surveilling them, privacy as a design input.
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Eklavya Goyal
Physics @ TUM · Mathematics @ LMU · ML @ Tools for Humanity
Munich, DEeg@eklavyagoyal.comgithub.com/eklavyagoyallinkedin.com/in/eklavya-goyaleklavyagoyal.com/cv
Double-degree student in Munich: physics at TUM, mathematics at LMU. Machine learning at Tools for Humanity (World), on proof of personhood.
Golden Chalk 2025 (best TA, TUM Physics, taught in German). Three hackathon wins in 2026 (and a 4th of 130+ teams). Ships language and education products on the side.
Experience
Oct 2024 – now
Machine Learning
Tools for Humanity (World), Munich
Production ML for proof of personhood at planetary scale: verify a unique human without surveilling them, privacy as a design input.
2024
Physics-Informed Learning
TUM
Physics-informed networks: conservation laws become a training signal, not a constraint fought against, and the same loss recovers unknown physical constants from noisy data.
2024 – now
Teaching Assistant, Physics
TU Munich
Golden Chalk 2025: best TA in the department, for tutorials taught in German.
Education
Oct 2023 – now
B.Sc. Physics
Technical University of Munich
One of two degrees run at the same time; the main academic anchor.
Oct 2024 – now
B.Sc. Mathematics
LMU München
Physics and maths side by side, on purpose. Where the rigor comes from.
2022–2023
Studienkolleg, technical course
TU Munich
Natural sciences, taught and examined in German.
2021–2022
German language, TELC C1
EIIE Eurasia Institute, Berlin
C1 from zero in three years.
2019–2021
Senior secondary, natural sciences
CBSE
95.8%, German-grade equivalent 1.0.
Skills
ML & code
Python, PyTorch, TypeScript, LaTeX
Domains
Diffusion models, LLM orchestration, Embeddings, Sentinel-1/2 remote sensing, pandapower / N-1 analysis, AMD MI300X (ROCm), Next.js
Awards
Track winner
Warden, Energy Hack Munich (E.ON), 2026
4th of 130+ teams
TUM.ai Makeathon, osapiens challenge, 2026
2× first place
TUM.ai × Unite Data Mining Hackathon, 2026
Languages
English (fluent), German (TELC C1), Hindi (native)
Eklavya Goyal
Physics @ TUM · Mathematics @ LMU · ML @ Tools for Humanity
Munich, DEeg@eklavyagoyal.comgithub.com/eklavyagoyallinkedin.com/in/eklavya-goyaleklavyagoyal.com/cv
Double-degree student in Munich: physics at TUM, mathematics at LMU. Machine learning at Tools for Humanity (World), on proof of personhood.
Golden Chalk 2025 (best TA, TUM Physics, taught in German). Three hackathon wins in 2026 (and a 4th of 130+ teams). Ships language and education products on the side.
Experience
Oct 2024 – now
Machine Learning
Tools for Humanity (World), Munich
Production ML for proof of personhood at planetary scale: verify a unique human without surveilling them, privacy as a design input.
2024
Physics-Informed Learning
TUM
Physics-informed networks: conservation laws become a training signal, not a constraint fought against, and the same loss recovers unknown physical constants from noisy data.
2024 – now
Teaching Assistant, Physics
TU Munich
Golden Chalk 2025: best TA in the department, for tutorials taught in German.
Education
Oct 2023 – now
B.Sc. Physics
Technical University of Munich
One of two degrees run at the same time; the main academic anchor.
Oct 2024 – now
B.Sc. Mathematics
LMU München
Physics and maths side by side, on purpose. Where the rigor comes from.
2022–2023
Studienkolleg, technical course
TU Munich
Natural sciences, taught and examined in German.
2021–2022
German language, TELC C1
EIIE Eurasia Institute, Berlin
C1 from zero in three years.
2019–2021
Senior secondary, natural sciences
CBSE
95.8%, German-grade equivalent 1.0.
Skills
ML & code
Python, PyTorch, TypeScript, LaTeX
Domains
Diffusion models, LLM orchestration, Embeddings, Sentinel-1/2 remote sensing, pandapower / N-1 analysis, AMD MI300X (ROCm), Next.js
Awards
Track winner
Warden, Energy Hack Munich (E.ON), 2026
4th of 130+ teams
TUM.ai Makeathon, osapiens challenge, 2026
2× first place
TUM.ai × Unite Data Mining Hackathon, 2026
Languages
English (fluent), German (TELC C1), Hindi (native)