Aishwarya Naresh Reganti — Founder

🚨PLEASE NOTE: I don't check my LinkedIn messages regularly. For speaking, advisory or collaboration inquiries, please send a message here: https://tr.ee/Kdgcp5lXO2 I'm currently in the process of building my AI solutions lab: LevelUp Labs (More details coming soon) Before this, I worked as an Applied Science Tech Lead at the AWS Generative AI Innovation Center (GenAIIC). At GenAIIC, we partner with external organizations to pinpoint and evaluate valuable uses for generative AI. We seamlessly integrate these solutions into their existing operations to improve efficiency. Prior to this, I worked in the Amazon Search Science and AI Org where I led multiple projects involving large scale language, vision and graph models that improve Amazon search quality, trust and recommendations. I have over 9+ years of hands-on ML experience and 35+ publications in top-tier conferences like AAAI, ACL, CVPR, NeurIPS, EACL e.t.c. I've worked on a wide spectrum of problems that involve Large Scale Graph Neural Networks, Machine Translation, Multimodal Summarization, Social Media and Social Networks, Human Centric ML, Artificial Social Intelligence, Code-Mixing e.t.c. I've mentored several Masters and PhD students in the aforementioned areas. I've also served as a reviewer in various NLP and Graph ML conferences like ACL, EMNLP, AAAI, LoG e.t.c. I've been fortunate to work with some of the best minds in both academia and industry through collaborations and internships in Stanford University, Microsoft Research, University of Michigan, NTU Singapore, IIIT-Delhi, NTNU-Norway, University of South Carolina e.t.c. Please look up my Google Scholar profile for more information. I'm also a visiting lecturer in MIT and University of Oxford. All opinions shared here are my own and don’t represent my employer.

Stackforce AI infers this person is a leader in AI solutions and generative AI technology.

Location: San Francisco, California, United States

Experience: 7 yrs 11 mos

Skills

Generative Ai

Career Highlights

9+ years of hands-on ML experience.
35+ publications in top-tier conferences.
Mentored several Masters and PhD students.

Work Experience

LevelUp Labs

Founder (8 mos)

Wharton Cypher Accelerator

Startup Mentor/Advisor (3 mos)

University of Oxford

Tutor/Lecturer (1 yr 10 mos)

MIT Professional Education

External Lecturer (6 mos)

Amazon Web Services (AWS)

Applied Science Tech Lead (Generative AI) (1 yr 6 mos)

The LevelUp Org

Co-Founder (3 yrs 4 mos)

Amazon

Applied Scientist (3 yrs 10 mos)

Carnegie Mellon University

Graduate Teaching Assistant (8 mos)

Graduate Teaching Assistant (4 mos)

Amazon Lab126

Applied Scientist Intern, Alexa AI (3 mos)

University of Michigan - Rackham Graduate School

Research Assistant (4 mos)

Microsoft

Research Intern (1 mo)

IIIT-Delhi

Research Associate (2 mos)

Norwegian University of Science and Technology (NTNU)

Undergraduate Research Assistant (4 mos)

Nanyang Technological University, Singapore

Undergraduate Research Assistant / Summer Intern (1 mo)

IIIT Hyderabad

IIIT-H SUMMER START-UP BOOTCAMP (1 mo)

Education

Master's degree at Carnegie Mellon University

Startup School at Y Combinator

B.Tech( Hons.) at Indian Institute of Information Technology, SriCity

High School at Delhi Public School - Bangalore South

Aishwarya Naresh Reganti

Founder

San Francisco, California, United States7 yrs 11 mos experience

AI EnabledAI ML Practitioner

Key Highlights

9+ years of hands-on ML experience.
35+ publications in top-tier conferences.
Mentored several Masters and PhD students.

Stackforce AI infers this person is a leader in AI solutions and generative AI technology.

Contact

Skills

Core Skills

Generative Ai

Other Skills

Amazon Web Services (AWS)CC++Deep LearningHTML5JavaMachine LearningMatlabMicrosoft AzureNatural Language ProcessingPHPPython

About

Experience

Levelup labs

Founder

Jul 2025 – Present · 8 mos · San Francisco Bay Area · On-site

Most companies in their AI journey don’t struggle with a lack of tools or products to build/buy, they struggle with the right vision, problem-scoping, and building systems that actually fit business constraints.
We’re a team of forward-deployed AI specialists who embed deeply with your teams to strategize, design, and build production-ready systems with a problem-first, enterprise-grade mindset.
What we do:
AI advisory
Hands-on implementation or engineering team augmentation
Corporate training programs and workshops
Let’s talk: contact@levelup-labs.ai

Wharton cypher accelerator

Startup Mentor/Advisor

Jan 2025 – Apr 2025 · 3 mos · Pennsylvania, United States · Remote

Guide founders on AI strategy and implementation.

University of oxford

Tutor/Lecturer

May 2024 – Present · 1 yr 10 mos · Remote

Invited to deliver lectures for professional courses in artificial intelligence
My GitHub repo and other content are extensively used as references for course design and as reading material for students

Mit professional education

External Lecturer

Apr 2024 – Oct 2024 · 6 mos · Massachusetts, United States · Remote

- Advise on curriculum development and deliver guest lectures for the hands-on (coding) components of the “AI Strategies and Roadmap” course

Amazon web services (aws)

Applied Science Tech Lead (Generative AI)

Dec 2023 – Jun 2025 · 1 yr 6 mos · Santa Clara, California, United States · On-site

Work as an Applied Science Tech Lead at the AWS Generative AI Innovation Center (GenAIIC)

Generative ai

The levelup org

Co-Founder

Nov 2022 – Present · 3 yrs 4 mos · San Francisco Bay Area

The LevelUp Org is a non-profit self-reliant tech ecosystem and community where members help each other accomplish career goals through 1:1 mentorship programs and a host of other community events

Amazon

Applied Scientist

Feb 2020 – Dec 2023 · 3 yrs 10 mos · Palo Alto, California, United States

Feb 2023- December 2023
Led multiple science projects focused on building new Amazon Search features using cutting-edge generative language and vision models.
Oct 2021- Feb 2023
Research on LLM-enhanced Graph Neural Network (GNN) architectures, enabling rich contextual representations for diverse downstream applications, at an Amazon-scale data level (tens of billions of edges!).
Feb 2020 - Oct 2021
Worked in the Alexa AI Teachable AI team to build large scale language models that help Alexa understand customer preferences better via interactive teaching sessions. Our capability was featured by WSJ, TechCrunch & MSN among others.

Carnegie mellon university

2 roles

Graduate Teaching Assistant

Jun 2019 – Feb 2020 · 8 mos

11-785 Introduction to Deep Learning (http://deeplearning.cs.cmu.edu/document/extra/TAs.html)

Graduate Teaching Assistant

Jan 2019 – May 2019 · 4 mos

05-898: Data Science and Visualization

Amazon lab126

Applied Scientist Intern, Alexa AI

May 2019 – Aug 2019 · 3 mos · Sunnyvale, California

Worked on developing end-to-end models for multi-domain goal-oriented conversational dialogue systems with a focus on system side dialogue act prediction and response generation.
Explored possible unsupervised pretraining objectives and fine-tuning approaches for learning dialog context representations using neural architectures like hierarchical attention models, self-attentive encoders, BERT, etc.
Conducted experiments to develop robust end-to-end conversational systems with domain-generalization and knowledge transfer capabilities using low-resource settings, zero-shot, and few-shot learning approaches.

University of michigan - rackham graduate school

Research Assistant

Sep 2017 – Jan 2018 · 4 mos · United States

• Worked with Prof. Rada Mihalcea. Developed a new benchmark grit score gold standard data-set using Crowdflower and modeled a Bi-LSTM based social attention model for grit classification using Twitter data (Paper accepted at IEEE Access 2019).

Microsoft

Research Intern

May 2017 – Jun 2017 · 1 mo · Bengaluru Area, India

Collected verbal aggression data using Twitter API and modelled machine learning classifiers (using word vector representation inputs) to predict aggression and flag unratified aggressive posts in real-time.
Released a prototype Google Chrome plug-in and paper accepted at LREC-2018

Iiit-delhi

Research Associate

Oct 2016 – Dec 2016 · 2 mos · Delhi

Developed machine learning classifiers that predict individuals' vulnerability to online ISIS recruitment
Performed analysis using social network structure, psycho-sociological patterns and community detection

Norwegian university of science and technology (ntnu)

Undergraduate Research Assistant

Jul 2016 – Nov 2016 · 4 mos · Remote Assistance

Developed machine learning models to predict various psycho-social metrics (values, ethics, personality) using features like n-grams, topic models, psycho-linguistic lexica, and speech-acts.
Used above classifiers for various applications such as community detection (Our community detection model beat Stanford's CESNA by a margin of 4%), recommendation systems, multi-cultural analysis, societal sentiment analysis
Papers accepted at: AAAI-2017, IEEE Intelligent Systems, EACL-2017, CSCW-2017

Nanyang technological university, singapore

Undergraduate Research Assistant / Summer Intern

Jul 2016 – Aug 2016 · 1 mo · Singapore

• Investigated common patterns (continuity disruption, sentiment flip, lexical variations) in natural language for identifying satire in text to develop a soft ensemble classifier with optimum hyper-parameters and recursive feature selection techniques.