Abhinav Gupta

AI Researcher

Cambridge, Massachusetts, United States9 yrs 1 mo experience

Highly StableAI Enabled

Key Highlights

Expert in AI/ML for drug discovery.
PhD from MIT with a focus on Bayesian modeling.
Proven track record in interdisciplinary research.

Stackforce AI infers this person is a Healthcare AI specialist focused on drug discovery and computational biology.

Contact

abhinavgupta0110@gmail.com 6178003899 LinkedIn

Skills

Core Skills

Machine LearningBiologicsData ScienceBayesian InferenceMechanical EngineeringComputational Fluid Dynamics

Other Skills

Antibody EngineeringAntibody and Nanobody EngineeringApplied MathematicsArtificial Intelligence (AI)Artificial Neural NetworksComputational BiologyComputational Fluid Dynamics (CFD)Computational PhysicsData AssimilationDeep LearningDynamical SystemsFluid MechanicsInformation TheoryLaTeXLarge Language Models (LLM)

About

Working at Sanofi to apply cutting-edge computation, AI/ML/DL, and structural biology technologies to resolve challenges in real-world drug discovery. As part of my PhD at MIT, I developed state-of-the-art algorithms and methodologies for uncertainty quantification, Bayesian learning, deep learning, and numerical methods for applications to dynamical systems.

Experience

Sanofi

2 roles

Principal Machine Learning Scientist

Promoted

Oct 2025 – Present · 5 mos · Cambridge, Massachusetts, United States

Developing state-of-the-art foundational ML models for biologics, integrating sequence, structural, and experimental data for antibody and NANOBODY® VHH discovery.
Building scalable pipelines to curate protein complex data, facilitating the discovery of patterns in immune recognition.
Utilizing large language models and generative AI for protein design and engineering, enhancing research capabilities.

Large Language Models (LLM)Machine LearningArtificial Intelligence (AI)BiologicsAntibody and Nanobody EngineeringProtein Engineering+1

Senior Scientist, AI Innovation for Antibody

Aug 2022 – Oct 2025 · 3 yrs 2 mos · Cambridge, Massachusetts, United States

Working in an interdisciplinary team with the Sanofi Large Molecule Research Platform to apply cutting-edge computation, AI/ML/DL, and structural biology technologies to resolve challenges in real-world drug discovery and make impacts on patients’ life.

Predictive ModelingMachine LearningData ScienceArtificial Intelligence (AI)Deep LearningPyTorch+10

Massachusetts institute of technology

4 roles

MIT-Tata Center for Technology & Design Fellow

Promoted

Jun 2018 – May 2020 · 1 yr 11 mos

Studied interplay of technology, entrepreneurship, and policy; and deepened perspectives on severely resource-constrained communities by interviewing Indian fishermen, non-profits, and government institutions

Machine LearningStatisticsData SciencePresentation SkillsArtificial Intelligence (AI)Matlab+4

Graduate Teaching Assistant

Feb 2018 – May 2018 · 3 mos

Teaching assistant for the course "Numerical Fluid Mechanics (2.29)". Held recitations every week, helped prepare lecture material, graded assignments, and quizzes. Mentored approx. ~ 25 for their end-of-term projects.

Mechanical EngineeringFluid MechanicsComputational PhysicsNumerical SimulationMATLAB

Research Assistant [Multidisciplinary Simulation, Estimation, Assimilation Systems (MSEAS) Lab, MIT]

Jan 2017 – Jul 2022 · 5 yrs 6 mos

RESEARCH PROFILE:
Advancing algorithms on the intersection of uncertainty quantification, Bayesian modeling and inference, deep learning, and data-driven scientific computing for high-dimensional and multidisciplinary problems
Developing a partial-differential-equations-based Bayesian machine learning framework for model discovery; has applications in learning ocean ecosystem models, sustainable fisheries management, brain tumor modeling and more
Developed a delay-differential-equations based deep learning framework to learn closure models for dynamical systems; applications include capturing the effects of subgrid-scale processes in coarse models, simplification of complex biochemical models, and more
Research presentations:
Dynamic Data Driven Applications Systems (Virtual, Oct'20); AGU Fall Meeting (SF, Dec’19); IEEE Oceans (Seattle, Oct’19); Indian Institute of Science Bangalore (India, Jul’19, Aug'21); Indian Space Research Organization (India, Jul’19); SIAM, Computational Science and Engineering (Spokane, Mar’19); AGU Ocean Sciences Meeting (Portland, Feb’18); SIAM Dynamical Systems (Virtual, May'21); Caltech (Jul'21)
ALLIED CONTRIBUTIONS:
Developing collaboration protocols to facilitate multi-university-research project across 5 universities
Mentored 3 undergraduate and 3 high-school interns on research projects

Predictive ModelingMachine LearningStatisticsTensorFlowData SciencePresentation Skills+19

International Visiting Student

May 2015 – Jul 2015 · 2 mos · Cambridge, Massachusetts, United States

I worked with the Multidisciplinary Simulation, Estimation, and Assimilation Systems (MSEAS) research group. Gained skills in numerical methods, probabilistic modeling, and data-assimilation.

Machine LearningData ScienceComputational Fluid Dynamics (CFD)Artificial Intelligence (AI)Computational PhysicsNumerical Simulation+1

13th indo-european winter academy

Student at the 13th Indo-European Winter Academy

Dec 2014 – Dec 2014 · 0 mo · Indian Institute of Technology, Kanpur

1 among 42 students selected across India
Completed course on Modelling and Algorithms in Fluid Mechanics and Heat Transfer
Studied numerical methods currently in use for fluid modelling

Computational Fluid Dynamics (CFD)Computational PhysicsNumerical SimulationComputational Fluid Dynamics

Massachusetts institute of technology

International Visiting Student (S.N. Bose Scholar)

May 2014 – Jul 2014 · 2 mos · Cambridge, MA - 0239, USA

I worked with the Multidisciplinary Simulation, Estimation, and Assimilation Systems (MSEAS) research group. Gained skills in numerical methods, and ecosystem modeling for the ocean.

Machine LearningData ScienceComputational Fluid Dynamics (CFD)Artificial Intelligence (AI)Computational PhysicsNumerical Simulation+1

Indian institute of technology, kanpur

Summer Undergraduate Research Grant for Excellence (SURGE) Fellow

May 2013 – Jul 2013 · 2 mos · Kanpur, Uttar Pradesh, India

Analyzed the phenomenon of vortex shedding and its control using active and passive methods
Gained experience in computational fluid dynamics (CFD) and numerical methods

Computational Fluid Dynamics (CFD)Computational PhysicsNumerical SimulationComputational Fluid Dynamics