VP / director / head of AI research and data Science

PROFESSIONAL EXPERIENCE

Managing Partner & Co-Founder Minnow Venture Partners, NY July 2024 - Present

● Strategic planning and execution of tasks required for a VC Fund formation (legal, financial, pitch to investors & partners).

● Designed and implemented a proprietary tech platform to streamline competitive intelligence and due diligence processes.

● Conducted in-depth diligence on startups, including evaluating AI/ML implementations and tech stacks in Healthtech, and drug mechanisms with competitive landscapes in Biotech.

● Analyzed an oncology startup’s drug mechanism of action by reproducing bioinformatics workflows (differential gene expression analysis, gene set enrichment analysis, and drug response prediction modeling) to assess clinical success probability, predict patient population size and market potential, and delivered an enhanced drug response model for improved clinical patient selection.

● Delivered to a startup a proof-of-concept tech stack for web document indexing, incorporating Retrieval-Augmented Generation (RAG) for information retrieval and AI agents for analysis and summarization, within a two-week timeframe.

● Provided strategic guidance on DL approaches and dataset selection to a startup modeling iPSC cell differentiation.

● Supported a startup seeking collaboration partners with competitive intelligence on approved biologics.

● Led a successful pilot project with a university tech transfer office, demonstrating our expertise and platform capabilities, providing advanced data-driven insights to guide strategic decisions on research program funding. Delivered tailored R&D and commercialization strategies for three programs in atherosclerosis, Parkinson’s disease, and schizophrenia. VP, Computational Research & Development Head SMP America, NY July 2023 - July 2024 VP, AI Research Sumitovant Biopharma, NY March 2021 - July 2023 Senior Director, AI Research Sumitovant Biopharma, NY December 2019 - March 2021

● Spearheaded the strategic vision and direction for the Computational Research team, aligning with company objectives.

● Grew and led a multidisciplinary team (hired an AI Scientist, Executive Director of Bioinformatics, Bioinformatics Scientist and KG Scientist), leading a team of 8 (one working from Asia) with seasonal expansion to 14 (interns and rotational analysts).

● Expanded the use of our technology to Drug Discovery, Preclinical, Clinical Research and Competitive Intelligence, leading multiple collaborations across our family of companies.

● Implemented robust project management practices to ensure timely delivery of projects and development objectives.

● Successful novel oncology targets identification, combining information extracted from text and aggregated data from several databases. In-depth review of publications and biological pathways for target ranking. Several targets validated in the lab.

● Engineered an innovative framework for understanding a drug mechanism of action, merging data from various sources, employing ML methodologies, utilizing graph databases (RDF and Neo4j), information extracted from text and bioinformatics. Applied this framework to biomarker identification and optimizing drug indication selection.

● Led initiatives in information extraction from text across various domains including oncology, CNS, and adverse effects, utilizing advanced NLP models and cutting-edge LLMs. Implemented a graph-DB-based chatbot to facilitate data access.

● Directed the enhancement and deployment of a state-of-the-art competitive intelligence email alert system, which evolved into a production-level service catering to over 100 users across our family of companies. This system provided timely insights into market trends, competitor activities, and emerging opportunities, driving informed decision-making across the organization, and replaced similar paid subscriptions.

● Applying latest Deep Learning approaches to scRNAseq data for drug discovery (target prediction).

● Web application development to accelerate novel target search and evaluation in CNS.

● Web application for clinical trial vector-based searches and advanced FDA label searches.

● Successful external collaboration with Neochromosome to identify peptide drug candidates.

● Data Engineering / DevOps / App development: conducted an in-depth trial of MarkLogic, migrated to it from SOLR (hired and supervised a short term contractor). Migrated our ETL to NiFi and then to Airflow. Data modeling for documents and RDF triples. Worked with our ex-US team member to develop various web applications (semantic search engine, web-application to give access to advanced API searches, graph database for a disease’s target landscape exploration).

● Championed a culture of continuous learning and professional development within the team, fostering innovation. Yoann Mamy Randriamihaja, PhD

Y MR

********@*****.*** 518-***-****

Patterson, NY

https://www.linkedin.com/in/yoann-mamy-randriamihaja-a1243430/ Director, Computational Research Roivant Sciences, NY, February 2017 - December 2019

● Joined the DrugOme team as its 3rd member. Significant hands-on contribution to our technology development, leading to our acquisition by Sumitomo Pharma. Played various roles: Data Engineer, Data Scientist, DevOps, Team Leader / Manager.

● Expert at rapid pilot project execution to quickly get to a working prototype and supervise team member implementation: on technologies (SOLR, neo4j, RDF, …), libraries (TensorFlow v1 vs. v2), AI models (NER, document classifiers, BERT, MPNN, etc…)

● Data Science & AI: Promoted the adoption of AI (NLP and ML) by running multiple projects on different pharma use cases. Various data analysis (ex.: BD use cases, indication expansion, target search for diseases, social media text mining), modeling

(ex.: revenue/NPV forecasting) and presentations to technical and non-technical audiences. Supported the launch of VantAI through hands-on exploration of various AI models in the context of compound properties prediction (drug target prediction, toxicity, PK, etc…) and interactions with external customers (consulting role) on drug repurposing projects.

● Data Engineering: MySQL DB design, implementation and tuning. Python ETL code development for data ingestion and entity matching for data aggregation. Implemented web document scraping and indexing into SOLR with custom Python ETL. Developed a news email alert system for BD and Drug Discovery monitoring. Hired and supervised a consultant for a Neo4j Knowledge Base building POC.

● DevOps: AWS admin for our team and point of contact with DevOps team: EC2 (linux instances configuration on CPU or GPU), AMI, S3, IAM roles, security groups and cost control.

● Leadership: Supported the expansion of the larger DrugOme team through hiring and supervising junior members and several interns. Built and managed a team of AI Scientists and Engineers. MTS - Reliability and Technology development Globalfoundries, NY November 2015 - February 2017 Principal Engineer - Circuit Reliability & Tech. dev. Globalfoundries, NY May 2014 - November 2015 Senior Engineer - FEOL Reliability & Tech. dev. Globalfoundries, NY November 2012 - May 2014

● Strong ability and desire to understand data from other technical fields and connect them together to solve complex problems.

● Rapid implementation and transition of novel initiatives supplemented by mentorship for team members.

● Project lead for a new memory reliability qualification (scope & schedule definition, cross-site and cross-functional activities coordination).

● Device reliability (TDDB, BTI, HCI) on advanced nodes (14nm & 20nm, high volume data collection and reporting automation).

● Study of manufacturing process impact on reliability and actively involved in cross-functional process optimization.

● SRAM array extended characterization & HTOL (measurement design /execution with V93k, data processing with VBA scripts, data analysis with JMP, degradation of SRAM parameters with stress, device physics based reliability models, process impact on SRAM reliability).

● Collaborated with Integration, Device, SRAM, Yield, Failure Analysis, Memory Test, Modeling and Customer Interface teams. R&D Engineer - Device & Product Reliability STMicroelectronics France October 2009 - October 2012

● Developed partnership with the Advanced Physical Modeling team.

● Improved oxide defect behavior modeling by co-developing an in-house device simulator (reproducing stressed CV & IgVg).

● Managed a working group on modeling atomic defect creation dynamics under Hot-Carrier stress

● Delivered a complete solution from defect creation to device degradation (applied to Flash programming cycle).

● Evaluation of gate-oxide breakdown impact on ring-oscillators performance.

● Collaboration with Udine University for Monte Carlo simulations of transistors function after defect generation. EDUCATION

Aix-Marseille University Marseille, France November 2012

● Ph.D., in micro & nano electronics

Thesis: Study of advanced CMOS technology reliability, from defect creation to transistors degradation. Joseph Fourier University Grenoble, France 2009

● Master of research in micro & nano electronics

Physic Electronic Materials (PHELMA) Engineering School Grenoble, France 2009

● Master degree in Engineering. Major: microelectronics, MEMS. TECHNICAL SKILLS

● Databases: MySQL, Neo4j, SOLR, MarkLogic, RDF ETL: Apache NiFi (ETL orchestration), DataDog (ETL health monitoring)

● Coding: Python (Hugging Face, TensorFlow, Keras, PyTorch), SQL, Cypher, SPARQL, R.

● AWS admin for our team and interface with DevOps team: EC2 (linux instance configuration on CPU or GPU for various use cases), AMI, S3, IAM roles, security groups, Neptune (POC), shared Jupyter Notebook server. PUBLICATIONS AND PATENTS

● “Investigating Cellular Profiling in ALS through the Application of Geneformer a Large scale Language Model on scRNA seq Data Analysis”, Y. Shiiba, R. Motodate, Y. Abe, T. Nashida, M. Sakuma, Y. Mamy Randriamihaja, G. Guffanti, K-Y. Chen, C. Tao, ALSMND 2024

● “Exploring Drug Switching in Patients: A Deep Learning-based Approach to Extract Drug Changes and Reasons from Social Media” M. Sarrouti, C. Tao, Y. Mamy Randriamihaja, BioNLP 2023

● “Systems and methods for biomedical information extraction, analytic generation and visual representation thereof”, Yoann MAMY RANDRIAMIHAJA, Mingzhe TAO, Mourad SARROUTI, US patent application WO2023170555A1, 2022

● “Systems and methods for centroid-based vector analysis of content items and interactive visual representation generation thereof”, Shigehiro Asano, Yoann MAMY RANDRIAMIHAJA, Mingzhe TAO, US patent application WO2023175480A1, 2022

● “Comparing Encoder-Only and Encoder-Decoder Transformers for Relation Extraction from Biomedical Texts: An Empirical Study on Ten Benchmark Datasets”, M. Sarrouti, C. Tao, Y. Mamy Randriamihaja, BioNLP 2022

● “Advancing Hallmarks of Cancer Identification from Scientific Literature”, C. Tao, N. Liu, M. Dandu, Y. Mamy R., AMIA 2022

● “A Multi-Task Learning Approach to Chemical Property Prediction”, C. Tao, Y. Mamy Randriamihaja, poster AMIA 2022

● “Method, apparatus and system for targeted healing of stability failures through bias temperature instability”, A. Gautam, R.W. Mann, W. McMahon, Y. Mamy RANDRIAMIHAJA, Yuncheng Song, US patent application US9601188B1 2016

● “Method to identify extrinsic sram bits for failure analysis based on fail count voltage response”, V. Joshi, S. Balasubramanian, C. Weintraub, Y. Mamy RANDRIAMIHAJA, W. McMahon, US patent application US20160284421A1, 2015

● “Assessing Intrinsic and Extrinsic End-of-Life Risk Using Functional SRAM Wafer Level Testing”, Y. Mamy Randriamihaja, W. McMahon, et al., in IEEE Int. Reliab. Phys. Symp. (IRPS) 2015

● “From atoms to circuits: Theoretical and empirical modeling of hot carrier degradation”, W. McMahon, Y. Mamy- Randriamihaja, B. Vaidyanathan, T. Nigam, Book “Hot Carrier Degradation in Semiconductor Devices” 2014

● “New Hot Carrier degradation modeling reconsidering the role of EES in ultra short N-channel MOSFETs”, Y. Mamy Randriamihaja, X. Federspiel, et al., Int. Reliab. Phys. Symp. (IRPS) 2013

● “Microscopic scale characterization and modeling of transistor degradation under HC stress”, Y. Mamy Randriamihaja, V. Huard, X. Federspiel, et al., Microelectronics Reliability, 2012

● “Hot Carrier degradation: from defect creation modeling to their impact on MOS parameters”, Y. Mamy Randriamihaja, A. Zaka, V. Huard, P. Palestri, D. Rideau, D. Roy, A. Bravaix, M. Rafik, in IEEE Int. Reliab. Phys. Symp. (IRPS) proceeding, 2012

● “New insights into gate-dielectric breakdown by electrical characterization of interfacial and oxide defects with reverse modeling methodology”, Y. Mamy Randriamihaja, D. Garetto, V. Huard, D. Rideau, A. Bravaix, in IEEE IRPS proceeding, 2012

● “MOSFET's Hot-Carrier degradation characterization and modeling at a microscopic scale”, Y. M. Randriamihaja, A. Zaka, V. Huard, D. Rideau, A. Bravaix, IEEE IRPS, 2011

● “Oxide defects generation modeling and impact on BD understanding”, Y. M. Randriamihaja, V. Huard, A. Zaka, S. Haendler, X. Federspiel, M. Rafik, D. Rideau, D. Roy, A. Bravaix, in IEEE Int. Reliab. Phys. Symp. (IRPS) proceeding, GD.3.1, 2011

● “Multiple microscopic defects characterization methods to improve macroscopic degradation modeling of MOSFETs”, Y. M. Randriamihaja, A. Bravaix, V. Huard, D. Rideau, M. Rafik, D. Roy, in IEEE Int. Integ. Reliab. Work. (IIRW) final report, p. 61, 2010

● “Impact of the gate-stack change from 40nm node SiON to 28nm High-K Metal Gate on the Hot-Carrier and Bias Temperature damage”, A. Bravaix, Y. Mamy Randriamihaja, V. Huard, D. Angot, X. Federspiel, in IEEE IRPS proceeding, 2013

● “Modeling stressed MOS oxides using a Multiphonon-Assisted quantum approach—Part I: impedance analysis”, D. Garetto, Y. M. Randriamihaja, D. Rideau, A. Zaka, A. Schmid, Y. Leblebici, H. Jaouen, in Trans. Elec. Dev., vol. 59, p. 610, 2012

● “Modeling stressed MOS oxides using a Multiphonon-Assisted quantum approach—Part II: transient effects”, D. Garetto, Y. M. Randriamihaja, D. Rideau, A. Zaka, A. Schmid, Y. Leblebici, H. Jaouen, in Trans. Elec. Dev., vol. 59, p. 621, 2012

● “Analysis of defect capture cross sections using non-radiative multiphonon-assisted trapping model”, D. Garetto, Y. M. Randriamihaja, A. Zaka, D. Rideau, A. Schmid, H. Jaouen, Y. Leblebici, in Sol. Stat. Elec. (SSE), vol. 71, p. 74, 2012

● “Comparing defect characterization techniques with non-radiative multiphonon charge trapping model”, D. Garetto, Y. Mamy Randriamihaja, D. Rideau, A. Schmid, H. Jaouen, invited paper under review in Journal of Computational Electronics

● “AC analysis of defect cross sections using non-radiative MPA quantum model”, D. Garetto, Y.M. Randriamihaja, A. Zaka, D. Rideau, in Ulti. Integ. Silic. (ULIS), 2011

● “Small signal analysis of electrically-stressed oxides with Poisson-Schrödinger based multiphonon capture model”, D. Garetto, Y.M. Randriamihaja, D. Rideau, E. Dornel, F. William, A. Schmid, V. Huard, Y. Leblebici, in Int. Work. Comp. Elec. (IWCE), 2010

Contact this candidate