Experience

Research rigor with an engineer's delivery mindset

I build dependable AI systems across LLM-powered workflows, retrieval-augmented generation, structured evaluation, multimodal AI, computer vision, media forensics, and edge deployment.

Contact Abhineet Resume PDF

Latest resume updated July 2026.

Professional experience

May 2026
August 2026

Summer Graduate Fellow -- Agentic AI and Red Teaming

AI & Society Research Center and Center for Advanced Red Teaming, University at Albany / Albany, NY

  • Selected as a resident Summer Graduate Fellow to design and develop a secure, local-compute AI system for red-teaming research proposals.
  • Developing agentic LLM pipelines to evaluate proposal drafts, apply review criteria, generate structured feedback, and produce section-level recommendations.
  • Building specialized evaluation agents and synthesizing multi-agent outputs into consolidated recommendations for institutional research support.
  • Testing locally hosted model workflows with controlled data access, reproducibility, software validation, and responsible AI-assisted evaluation.
August 2024
May 2026

Research Assistant

Office of Strategic Initiatives, University at Albany / Albany, NY

  • Developed LLM-powered assistant systems for retrieval, question answering, recommendation synthesis, proposal evaluation, and institutional knowledge automation.
  • Built RAG pipelines using FAISS, ChromaDB, embeddings, metadata-aware retrieval, prompt routing, and cross-encoder reranking to improve answer relevance, grounding, and retrieval precision.
  • Designed agentic workflows for scoring, eligibility reasoning, feedback generation, structured recommendations, and tool-based reasoning over institutional data.
  • Implemented evaluation pipelines for hallucination detection, groundedness, relevance, consistency, response quality, and failure-case analysis across multiple knowledge domains.
  • Integrated local and cloud-based model workflows using Ollama, Hugging Face models, Azure OpenAI-style APIs, offline indexing, controlled data access, and reproducible validation.
  • Created engineering documentation covering architecture, model behavior, validation results, failure modes, and maintainability considerations for handoff and future deployment.
May 2024
July 2024

Adjunct Lecturer

Dean's Office, Rockefeller College / Albany, NY

  • Taught labs for Introduction to Computer Science.
  • Evaluated projects and exams with structured feedback.
August 2022
May 2024

Teaching Assistant

University at Albany, SUNY / Albany, NY

  • Supported Data Mining, Machine Learning, AI, Computer Vision, Networks, Operating Systems, DBMS, and introductory computer science courses.
  • Delivered lectures, guided labs, and managed assessments.
May 2022
August 2022

Computer Vision and Deep Learning Research Intern

Siemens Healthineers / Princeton, NJ

  • Worked on object detection and tracking for product-specific environments.
  • Built training and evaluation workflows including data ingestion, preprocessing, experimentation, dataset QA, and failure-mode analysis.
  • Developed synthetic data generation and training pipelines to reduce labeling effort and accelerate model iteration.
  • Trained and evaluated monocular depth estimation models for reflective, low-texture, and harsh-lighting conditions.
May 2021
August 2021

Computer Vision and Deep Learning Research Intern

Siemens Healthineers / Princeton, NJ (remote)

  • Developed object detection and tracking pipelines for robotic perception and applied AI systems.
  • Built training and evaluation workflows covering data ingestion, preprocessing, experimentation, dataset QA, and failure-mode analysis.
  • Developed synthetic data generation and training pipelines to reduce labeling effort and accelerate model iteration.
July 2019
May 2021

Senior Research Project Assistant -- GE Research Collaborations

The Research Foundation for SUNY / Albany, NY

  • Developed computer vision analytics for GE Research rail applications, including railcar detection, identification, tracking, and re-identification in multi-camera environments.
  • Implemented an edge-to-control-center AI architecture using NVIDIA Jetson AGX Xavier with multiple cameras deployed at operational checkpoints.
  • Built safety-focused video analytics for rail crossing protection using instance segmentation and multi-object tracking.
  • Contributed to production-oriented AI systems in industrial environments requiring robustness, performance awareness, monitoring needs, and operational reliability.
  • Supported reusable code development, experimental documentation, and technical reporting for cross-functional engineering and research teams.

Education

Ph.D. in Computer Science expected 2026, M.S. in Computer Science from University at Albany, and B.E. in Computer Science from SDMCET.

Ph.D. in Computer Science expected 2026.

Technical range

LanguagesPython / C / C++ / Java / CUDA / MATLAB / SQL

MLLarge Language Models / Computer Vision / Deep Learning / Multimodal AI / Model Evaluation / Hallucination Analysis

LLM systemsRAG / Agentic Workflows / Prompt Engineering / Structured Outputs / Hybrid Retrieval / Cross-encoder Reranking

PlatformsDocker / Linux Servers / GPU Servers / PostgreSQL / Neo4j / NVIDIA Jetson / Ollama

Service, leadership, and mentoring

Service

Professional memberships and peer review

The current resume lists IEEE and ACM membership and reviewing activity across ICIP, IMPROVE, ICME, MICCAI, AI City, TVCJ, Signal Processing: Image Communication, MDPI, and TMM.

Leadership

Research infrastructure and lab platforms

Managed GPU/data servers and research platforms including GitLab and Nextcloud.

Mentoring

Student mentoring

Advised master’s and high-school students on projects and research.