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About Me


With a PhD at the intersection of nanotechnology, biology, and AI, and a 2-year stint as a life sciences strategy consultant, I bring to the table a wealth of technical expertise including machine learning, data science, and bioinformatics. My technical proficiency is complemented by my strong interpersonal skills, cultivated through hands-on experience in leadership roles interfacing with pharma and biotech clients as a strategy consultant.

Currently, I am actively seeking opportunities that empower me to spearhead initiatives generating impactful societal change at the forefront of innovation. I'm primarily interested in biotech, climate tech, and health tech but open to other opportunities.

I recently published a two-part blog post, combining my passion for healthcare and machine learning, where I [embed multi-modal clinical trial data using large language models](https://medium.com/@lennart.langouche/clinical-trial-outcome-prediction-a4c6d279fd42?source=friends_link&sk=9e2330d6cf1fe4548f5d94965bfec825) and train a machine learning model on those embeddings to [predict clinical trial outcomes](https://medium.com/@lennart.langouche/clinical-trial-outcome-prediction-7ce6c27831f9?source=friends_link&sk=f65fd3cce048a5e72ffe54673062e70f).

During my PhD in the [Bioengineering Department at UCSD](https://be.ucsd.edu/) I focused on using AI/ML for infectious disease diagnostics in the context of systems medicine as part of the [Fraley Lab](https://fraley.ucsd.edu/systems-medicine). My PhD resulted in publications in Bioinformatics and Biomicrofluidics:

L. Langouche, Advancing Rapid Infectious Disease Screening Using a Combined Experimental/Computational Approach, University of California, San Diego (2021)

L. Langouche, A. Aralar, M. Sinha, S.M. Lawrence, S.I. Fraley, T.P. Coleman, Data-driven noise modeling of digital DNA melting analysis enables prediction of sequence discriminating power, Bioinformatics, 6 (2020)

W. Cai, E. Wang, P.W. Chen, Y.H. Tsai, L. Langouche, Y.H. Lo, A microfluidic design for desalination and selective removal and addition of components in biosamples, Biomicrofluidics, 13.2 (2019)


While in Grad School, I interned at Illumina, where I gained a better understanding of genomics and product management. After my PhD I worked as a Life Sciences Strategy Consultant for two years at IQVIA, where I became experienced at leading small teams to address complex business challenges for major pharmaceutical companies.

 

**Skills**
Business Strategy · Bioinformatics · Clinical Research · Cloud Computing · Computational Biology · Data Analysis · Data Science · Data Visualization · Diagnostics · Entrepreneurship · Git · ImageJ (Software) · Image Processing · Infectious Disease · Laboratory Skills · Large Language Models (LLMs) · Leadership · Linux · Machine Learning · Matlab · Next-Generation Sequencing · PCR/dPCR · Project Management · Python (Programming Language) · R (Programming Language) · Statistics · SQL · Tableau · Technical Writing