• Manage a team of Applied and Data Scientists, Deep Learning Architects, and Managers responsible for GenAI models and infrastructure.

• AI Advisor to various Startups and VCs.

• Advise research projects in NLP, Vision, Speech, and Multimodal AI.• Published research in top AI venues such as ACL, EMNLP, AAAI, EACL, ECML, WACV, ICASSP, etc.

• Advise research projects in NLP, Vision, Speech, and Multimodal AI.• Published research in leading AI venues.

• Advise research projects in NLP, Vision, Speech, and Multimodal AI.• Published research in leading AI venues.

• Headed AI Research and Development for Speaker Understanding and Personalization.• Architected AI/ML pipelines that power on-device and cloud features at scale on Amazon Alexa devices.

• Dreaming up amazing, intelligent, and differentiating AI-powered experiences on Apple devices.• Trained Multimodal AI models for a wide range of applications including NLP, Speech, and Vision.• Proposed and prototyped novel deep learning architectures that achieve state-of-the-art performance.• Designed privacy-preserving on-device ML models by implementing model compression techniques.• Collaborated with cross-functional teams to enable Apple products with efficient and accurate ML solutions.• Presented data and analysis to executives and cross-functional teams.

• Proven track record in leading the team and architecting new tools/methodologies.• Architected Apple’s portable and desktop offerings with a focus on performance. Co-led the development of the Neural Engine in the M1 "Apple Silicon" Macs from a performance perspective.• Led the development of a data analysis and visualization tool used regularly by the team's engineers.• Co-developed ML-based projection models to architect product roadmap for Macs by estimating performance of next-generation systems years in advance.• Collaborated with cross-functional teams to debug performance bottlenecks. Identified architectural improvement areas. Presented performance data and analysis to executives.• Go-to point of contact for several technical aspects of the team's day-to-day functioning.• Identified gaps in test coverage and defined new tests or bolstered existing ones.• Drove automation improvements from setup to execution to reporting.

• Led the validation of the neural processing subsystem for the Qualcomm AI Engine.• Co-authored a stress-testing framework that generated testing scenarios by randomly injecting events while system parameters were varied. This helped identify several hardware bugs and saved chip respins worth $2M.• Drafted test plans with common and corner use-cases for the core.• Coded test cases with a focus on functional coverage.

• Developed features in Python for an in-house tool to estimate power and performance using ML workloads for future chips on the company’s roadmap.• Profiled the tool to identify bottlenecks and optimized portions of the tool's code to quicken up response time• Developed a Python/Bash script that run nightly regressions, parsed and tabulated results as an HTML report, flagged anomalies in the regression runs and sent a report as a daily email.• Developed a MongoDB backend which supported create, read, update and delete operations on the tool's results.

• Developed drivers in C for the camera pipeline. • Wrote unit and system tests with randomized control and data signals to verify functionality.• Developed shell scripts to automate routine tasks.

• Developed web content for the Distance Education Professional Development (DEPD) program at the Division of Continuing Studies, UW-Madison

• Hardware development using Verilog for the Compact Muon Solenoid (CMS) experiment for the Large Hadron Collider (LHC) at CERN

• TA for ECE 315 (Introductory Microprocessor Laboratory) and ECE 353 (Introduction to Microprocessor Systems).• Lectured on the subject matter and developed programming assignments for ARM7/Cortex M3.

• Investigated topics under the domain of biometrics including Face Detection & Recognition, Signature Verification, Voice Recognition and Security of Biometric Templates.• Published research results at various international venues.

• Research staff at Sardar Patel Institute of Technology, under Prof. (Dr.) Y. S. Rao, involved in the development of a state-funded research project titled ‘Portable Patient Monitoring System’: an integrated system that aims at providing patient identification, monitoring of abnormal body conditions, tracking, rescue and response to deal with life-threatening emergencies. • The project involved processing of body signals and monitoring of body weight, blood pressure and pulse oximetry to identify critical body conditions and generate alert triggers that could be transmitted to a monitoring station in case of an abnormality.• As part of the research team, my role in this project was to accomplish the processing of body signals such as ECG, to aid the detection and diagnosis of cardiac abnormalities.

• Conducted lab-sessions on “Microprocessor and Microcontrollers” and “Introduction to C++ Programming”.• Conducted a workshop on “Image Processing using MATLAB”.