Abhishek Singh Dhadwal

AI Researcher

Tempe, Arizona, United States2 yrs 10 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Expert in healthcare AI and clinical decision support.
Proven track record in developing privacy-preserving systems.
Strong background in machine learning and data science.

Stackforce AI infers this person is a Healthcare AI Researcher with strong software development and data science expertise.

Contact

Skills

Core Skills

Clinical Decision SupportData ScienceFhirSoftware DevelopmentC#Machine LearningJava

Other Skills

Fast Healthcare Interoperability Resources (FHIR)CQL.NET FrameworkSQLPythonAmazon S3Mobile ComputingMobile HealthObject-Oriented Programming (OOP)CryptographyPredictive ModelingGenerative AISynthetic Data GenerationComputer VisionOpenCV

About

I am a healthcare AI researcher and MS Computer Science (Biomedical Informatics) student at Arizona State University focused on wearable time series modeling, clinical decision support, and privacy preserving clinical systems. Research focus: Wearables time series, FHIR and CQL clinical decision support, consent driven privacy and segmentation, clinical NLP reliability. I authored “4 Hz, 4 Pages” at the NeurIPS 2025 TS4H Workshop on just-in-time relapse risk detection from wearable time series data, as a solo author. In parallel, I contribute as a graduate student researcher in ASU’s SHARES Lab. I build and benchmark HL7 FHIR R4 and Clinical Quality Language (CQL) components for consent driven, auditable segmentation of sensitive health data aligned with 42 CFR Part 2. I have worked on a FHIR R4 plus CQL Consent Engine and supported benchmarking on 10k synthetic Synthea patients, achieving about 18.9k FHIR resources per second throughput with an estimated $0.009 AWS Lambda runtime cost. Before ASU, I spent two years in computational psychiatry research developing multimodal ML for depression detection. I built an end to end sensing and modeling pipeline, optimized data collection memory by 90 percent, and co authored peer reviewed publications with 60 plus citations. I also bring three years of production engineering experience from Credit Suisse. I shipped and operated global trading and backend systems, handled 85 plus production RFCs, and reduced ETL processing time by about 70 percent. I received two RAVE awards for impact in production delivery and collaboration. I am actively exploring research and industry roles in healthcare ML, biomedical informatics, and clinical AI systems. Contact: asinghdhadwal@gmail.com | GitHub: AbhishekSinghDhadwal | LinkedIn DM Keywords: Healthcare ML, Biomedical Informatics, Digital Health, Wearables, Time Series, TS4H, JITAI, Relapse Risk, Substance Use Disorder, SUD, Multimodal ML, Depression Detection, Mobile Sensing, Digital Phenotyping, Clinical NLP, Clinical Informatics, HL7, FHIR R4, CQL, CDS, CDS Hooks, Consent Management, Privacy Preserving Systems, 42 CFR Part 2, Data Segmentation, Synthetic EHR, Synthea, Benchmarking, Evaluation, AWS S3, AWS Lambda, Python, NumPy, Pandas, SQL, FastAPI, React, Next.js, MongoDB, C#, .NET, ETL, Production Systems, Distributed Systems

Experience

2 yrs 10 mos

Total Experience

2 yrs 10 mos

Average Tenure

Current Experience

Arizona state university

Graduate Student Researcher, Substance Use Disorder Informatics and Clinical AI

Aug 2024 – Present · 1 yr 8 mos · Tempe, Arizona, United States · Hybrid

Graduate student researcher contributing to SHARES: consent-driven, privacy-preserving clinical data sharing. Build and benchmark FHIR-native tooling (FHIR R4 + CQL) for auditable segmentation of sensitive health data (42 CFR Part 2).
Developed deterministic + AI-assisted CDS components for privacy-preserving segmentation of sensitive health data aligned with 42 CFR Part 2.
Built a FHIR R4 + CQL Consent Engine enabling physician-driven, auditable rule execution and granular data sharing for SUD-related records.
Supported large-scale benchmarking on 10k Synthea patients; achieved 18.9k FHIR resources/sec throughput with ~$0.009 estimated AWS Lambda runtime cost.
Collaborated with clinicians/informaticians/policymakers to translate prototypes into deployable tools; co-authored an accepted AMIA 2025 Systems Demonstration and a research paper in ACI (under review).
Independent research: Authored “4 Hz, 4 Pages” - NeurIPS 2025 TS4H workshop paper on just-in-time relapse risk detection from wearable time-series data.

Fast Healthcare Interoperability Resources (FHIR)Data ScienceClinical Decision Support

Credit suisse

3 roles

Exempt Non-Officer - Software Development, Investment Banking

Promoted

Jun 2023 – May 2024 · 11 mos · Pune, Maharashtra, India

Designed features for global trading algorithms and order management platforms (for stocks,futures and options) to ensure regulatory compliance and operational excellence for EMEA and US regions.
Managed deployments and modifications of trading services, including short sell order locators, compliance systems, and administrative applications. Oversaw 85+ production-level changes (RFCs) over two years, demonstrating expertise in C# and WinForms development alongside database management in Sybase and Oracle.
Founded a mentorship program for underrepresented STEM professionals and earned two RAVE awards for leadership and innovation.

.NET FrameworkC#SQLSoftware Development

Technical Analyst, Investment Banking

Jul 2021 – Jun 2023 · 1 yr 11 mos · Pune, Maharashtra, India

Designed and optimized daily ETL (Extract, Transform, and Load) pipelines using C# that reduced processing time by 70 percent, enhancing global data-driven decision-making.
Created and managed crucial daily jobs and reports to fetch data from various stock exchanges to the Credit Suisse Program Trading database, used by traders to book and review trades.
Facilitated the deployment and production of various trading services encompassing global order management systems, compliance check and administrative applications.
Interacted and coordinated with stakeholders across regions (US, UK, APAC) to discuss software requirements, design, and creation of application features based on C#’s .NET Core and the .NET Framework.

Data Science

Technology Intern, International Wealth Management

May 2020 – Jun 2020 · 1 mo · Pune, Maharashtra, India

Assisted in the provision of Continuous Integration and DevOps solutions for the International Wealth Management Tech Department.
Briefly worked on the deployment of Load balancers and OpenShift Clusters for cross-functional projects.

Visvesvaraya national institute of technology

Student Researcher, Computational Psychiatry

Jan 2020 – Jan 2022 · 2 yrs · Nagpur, Maharashtra

Conducted quantitative research towards the creation of a novel multimodal early detection approach for mental health ailments based on an end-to-end machine learning pipeline, under the guidance of Dr. Praveen Kumar.
Designed remote sensing protocols for the collection of user smartphone data (via AWS S3 Buckets) and extracted high-level features for smartphone, audio, and visual data (using NumPy and Pandas).
Optimized memory efficiency of data collection by 90% over the pre-existing methodology.
Co-authored 2 papers on the topic, providing valuable insights into the approach’s effectiveness for future researchers.

PythonAmazon S3Data ScienceMachine LearningMobile ComputingMobile Health

The apache software foundation

Software Developer - Google Summer of Code 2019

May 2019 – Jul 2019 · 2 mos · Remote

Researched and implemented pseudorandom number generators for the Apache Commons open-source project.
Worked extensively on the Integration of LCG, Permuted Congruential Generator variants, and other generators into the commons-rng repositories, used by thousands of developers globally.
Used Java and utilized Maven, JUnit, and JMH for project building and test suite creations for the generators.

Object-Oriented Programming (OOP)JavaCryptographySoftware Development