I bring boundless passion to the realm of Artificial Intelligence & Machine Learning technology with speciality in Generative AI and Language Models. If you've got an exciting project that demands exceptional skills, look no further—I'm your go-to expert!
I'm currently a torchbearer leading AI/ML pursuits in healthcare projects and RCM leveraging Generative AI Technology.
I’ve worked on a wide variety of internal tools for Zebo.ai, which is an AI based Dermatology platform.
I started my Machine Learning career with Google Cloud Program.
I think everyone wants the same thing - relationship with humanity, peace with the metaphysical, and experience with the universe. I try to grasp these things with my values: authenticity, creativity, & hospitality.
With a skill set that embraces various dimensions of AI/ML, I'm your perfect ally for a full-fledged project. Your unique needs won't be met with a one-size-fits-all approach – I thrive on crafting tailored solutions to tackle any challenge you throw my way.
Delivered production‑grade, end‑to‑end solutions and scalable deployments—across GPT 5, Grok 4, Claude 4.5 and Gemini 3 Pro, also Whisper and transformer‑based speech‑to‑speech pipelines achieving sub‑50 ms latency and >96% accuracy.
Developed and deployed Agentic AI frameworks leveraging a proprietary Model Context Protocol (MCP) to dynamically manage and synchronize model state, enabling autonomous agents to perform multi‑step reasoning, real‑time context switching and seamless interoperability across diverse LLMs and modalities.
Unified Transformer architectures, CNNs (U-NET, YOLO), and GNNs with PyTorch and TensorFlow into a production MLOps lifecycle—automating fine-tuning pipelines and model versioning to cut development cycles by 40% and accelerate inference optimization 3×.
Engineered scalable NLU pipelines (BERT, RoBERTa, DeBERTa) for intent, sentiment and entity resolution, and integrated retrieval‑augmented NLG to power enterprise chatbots and dynamic report generation with human‑grade fluency.
Hands-on experience in computer vision projects, including image classification, object detection, and facial recognition. Implementation of state-of-the-art vision models for real-world applications.
Worked on forecasting and anomaly‑detection frameworks combining ARIMA, SARIMA, Prophet and Temporal Fusion Transformers across finance, retail, healthcare and IoT applications to drive proactive decision‑making and significant cost savings through intuitive admin dashboards.
Auriclin AI is a comprehensive healthcare revenue cycle automation platform that orchestrates twelve specialized AI agents to streamline clinical and financial workflows. The system autonomously manages the complete patient journey from intake to reimbursement while utilizing advanced voice synthesis for insurance claim status inquiries. By automating complex tasks like coding and prior authorizations, the tool significantly reduces administrative burdens and improves revenue recovery to let providers focus on patient care.
A web app which unveils a new era of intelligent assistance. The cutting-edge application combines the power of advanced AI, including OpenAI's GPT technology, with a user-centric approach to transform your daily experiences.
An ADAS pipeline that consists of Traffic Light, Traffic Sign detection and anterior car distance estimation is developed in this project. A deep learning approach is used to develop a robust object detection model. Different algorithms and deep learning frameworks are experimented with, to provide a detailed analysis.
meet.ai is an innovative teleconferencing platform designed to transform virtual meetings with intelligent AI-driven features. From facial recognition-based attendance and productivity tracking to personalized meeting insights and dynamic engagement tools, meet.ai ensures every session is efficient and impactful. With a focus on enhancing collaboration and streamlining workflows, it brings a smarter, more intuitive approach to modern communication.
Currently pursuing a STEM-designated and thesis driven Master’s in the USA with a specialization in Data Science, focusing on Generative AI and serving as a Research Assistant. Gaining hands-on experience through projects, research and industry collaboration to level up my AI expertise.
Completed a B.Tech in Computer Science with a specialization in AI, focusing on algorithms, machine learning, and data analysis. Gained technical expertise through hands-on projects, preparing for roles in AI and technology.
Completed Cambridge AS & A Levels with a focus on mathematics, computer science, business studies, and economics, building a strong foundation in analytical and problem-solving skills.
My LinkedIn connections are established with professionalism and a commitment to mutual growth.
Connect with me for more brain storming.
If you're into expanding your network and share a passion for cars (obviously F1 too), check out my Instagram! I’m an automotive enthusiast capturing moments on the road and under the sky that I'd love to share with the world.
In the rapidly evolving landscape of automotive technology, the integration of Advanced Driver Assistance Systems (ADAS) has become paramount in addressing the increasing complexities of modern traffic scenarios. This research paper delves into the realm of automotive safety by presenting an innovative approach to ADAS through the incorporation of intelligent sensing technologies. The proposed system goes beyond conventional ADAS by leveraging state-of-the-art sensors and artificial intelligence, creating a sophisticated framework capable of perceiving, analyzing, and responding to dynamic driving environments in real-time.
*awaiting conference
We present an extensive strategy for improving images using deep learning-based techniques, concentrating on-super- resolution (SR) and low-light image improvement utilizing generative adversarial networks (GANs) and misalignment-robust networks (MIRNet), respectively. During the SGAN training phase, a deep convolution neural network learns a complete link between low- and high-resolution pictures.
Talking on a deeper note regarding technological advancements, today we experience chatbots taking over client handling and customer service completely, assisting humans in tasks big or small. The greatest asset we have as individuals would be health only and improving the health sector more and more via technology would be the biggest boon for humankind.
Topical and breaking news are very useful in daily life for enhancing and enriching our understanding of the global trends. Social platforms i.e., social media are emerging to be several of the world's primary digital communication sources for millions and millions of people. This method of news communication stands out due to their low budget, rapid reach and easily accessible sources. Taking deep learning in hand, here we propose a technique which works on the basis of deep learning and cuts down the spread of bogus news on social networking sites.
More than just recognition, but also a testament to my commitment to continuous learning and growth.
Led the research, planning, and technical implementation of HydroOptix, an AI driven water intelligence platform for data centers, during the Invent for the Planet 2026 challenge at Texas A&M University Corpus Christi. The system analyzes AI workloads and cooling infrastructure to make water consumption visible and optimize efficiency through predictive analytics and automated ESG reporting.
The project won 1st place and prize money, recognized for sustainability impact, research depth, and strong technical execution during the rapid innovation challenge.
Led a team of 3 to build bAI Watch, an AI powered disaster preparedness platform at the IslanderHack hackathon at Texas A&M University Corpus Christi. I led the AI centric system design, integrating multiple AI services to deliver personalized evacuation plans, supply lists, and an SOS voice agent that transcribes emergencies, classifies intent, and triggers automated calls with live location data.
Out of 40 participants and 10 projects, the platform earned 2nd place for technical depth and strong end to end execution under a 24 hour build timeline.
Devpost: https://devpost.com/software/bai-watch
GitHub: https://github.com/ivishakan/bAIWatch-tamuccHackathon
Newsletter: https://www.tamucc.edu/engineering/newsletter/assets/images/islanderhack.php
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