People / Students / Class of 2026
Ishan Monie holds a Bachelor of Arts in Data Science with Honors from the University of California, Berkeley. During his undergraduate studies, he developed a deep interest in natural language processing, generative AI, and low-resource language technologies. Through coursework in deep learning, efficient algorithms, and NLP, he built a strong foundation in machine learning while applying these skills in both academic research and production-grade systems.
For his UC Berkeley honors thesis, Ishan created a multi-stage pipeline that extracted citations from noisy OCR-scanned documents by combining LLaMA with a Bi-LSTM model. He improved citation accuracy by using prompt-based filtering alongside a named entity recognizer and sequence classifier to extract valid and complete references and separate them by component. He continued this line of work by contributing to the Akkadian NLP Kaggle Challenge, where he co-designed a lemmatizer and part-of-speech tagger for cuneiform, which served as a benchmark for evaluating the accuracy of competitors’ models.
In industry, Ishan has built and deployed several real-world AI tools. At Deeta Analytics, he designed LLM-based agents that automate Google Analytics reporting, SEO meta tag generation, and web-scale content operations. He also built retrieval-augmented systems that selectively surfaced relevant context before prompting the LLM, improving response accuracy while reducing token usage. At Hyphenova, he developed media scraping tools and used YOLOv5-based object detection to automatically tag and categorize visual content by topic and safety level. These experiences showcased his ability to bridge back-end infrastructure with NLP and machine learning applications in fast-paced environments.
Outside of internships, Ishan served as Project Manager for the Pioneers in Engineering program at UC Berkeley, a student-led initiative that mentors high school students through robotics competitions. In this role, he led the backend development of “Dawn,” a compiler that translates student-written Python code into C to interface with Raspberry Pi–based robotics kits. He also managed code reviews and mentored student teams through debugging challenges during the competition.
Ishan is excited to join the Machine Learning and Data Science program at Northwestern University, where he hopes to deepen his expertise in retrieval-augmented generation, scalable LLM deployment, and socially informed AI systems. He looks forward to applying these skills to build intelligent technologies that are rigorous, accessible, and impactful across domains.
