Combining Skills and Experience to Build Meaningful Solutions
Aditi Ashutosh Deodhar, MS’25, information systems, through her academic journey at Northeastern, has been able to grow her skill set and experiences through impactful projects, an incredible co-op opportunity and participating in vigorous hackathons.
Aditi Ashutosh Deodhar is a current student in the MS in information systems program. She earned a bachelor’s degree in electronics and telecommunication engineering from Pune Institute of Computer Technology in Pune, India. After graduating, she worked for two years as a software development engineer at Persistent Systems Ltd. During that time, Deodhar realized she wanted to move beyond software engineering and develop expertise in AI and machine learning, while also gaining industry-ready skills.
Northeastern stood out to Deodhar because of its unique blend of experiential learning and strong academics, especially the co-op program, which provides real-world experience alongside coursework. What particularly drew her to the information systems program was its applied focus and flexibility. One of the highlights of the MGEN program for Deodhar has been this flexibility to design her own track. She has chosen courses that match both her technical interests and professional aspirations, ranging from data science, engineering tools and methods, advanced data science and database design, to business-focused courses, such as Organizational Change and IT in her final semester. This approach has allowed her to build depth in data and AI while also developing the organizational skills needed to succeed in the workplace.
A course that had the biggest impact on Deodhar was “Big Data Systems & Intelligent Analytics” with Adjunct Professor Srikanth Krishnamurthy, which pushed her out of her comfort zone through multiple projects where she built pipelines, handled large-scale data, and worked with a wide range of tools. Another highlight was “High-Performance Parallel ML & AI” with Teaching Professor Handan Liu, where she gained hands-on experience with distributed training, CUDA, and MPI skills highly relevant to today’s AI systems. Deodhar is deeply grateful to her co-op advisor, Giuseppina Cucciniello, whose “Career Management for Engineers” course helped her prepare for interviews and navigate the co-op process with confidence. She also shares that her peers played a fundamental role in her journey.
Deodhar secured her co-op at Jutly Inc., an early-stage startup in Cambridge, as an AI engineer. During her time at Jutly, she focused on exploring and integrating emerging AI orchestration technologies such as LangGraph and LangChain. She built prototypes demonstrating how these tools could enhance the company’s AI-driven simulations and workflows. Her role also involved collaborating with teammates to design and optimize workflows, as well as documenting and sharing her findings. The experience provided her with both technical depth and the opportunity to contribute to the team’s collective learning.
Deodhar shares that the “Advances in Data Science and Architecture” course with Associate Teaching Professor Nicholas Brown was particularly valuable in preparing her for this role. As part of the class, she worked on “MediPedia”, a medical chatbot project where she built ingestion pipelines, vector databases and retrieval-based QA systems. This project strengthened her AI technical skills and gave her the confidence to apply these concepts in real-world scenarios.
Projects and Innovations
Deodhar had the opportunity to work on several impactful projects through both coursework and hackathons. One of her favorites was an AI-Powered Interview Prep Assistant, where she built pipelines to scrape and validate over 200k records, indexed embeddings, and created a front-end using Streamlit and FastAPI. The result was a system that significantly improved performance metrics such as latency and session completion, with clear applications for education and career services.
Another major project was “AI vs. Human Image Classification”, completed as part of her “High-Performance Parallel ML & AI” course. Using ResNet18 and Vision Transformer models on a 4-GPU cluster, she optimized training through distributed parallelism, mixed precision, CUDA and efficient data loaders. The biggest challenge was resource constraints, including limited GPU and memory availability, which pushed her to focus on efficiency and optimization.
Many of these projects have real-world potential: the Interview Prep Assistant could support students and career services, healthcare-focused work like MediPedia could aid medical applications, and image classification could have further medical or research applications.
Outside the Classroom
Hackathons were among the most exciting and transformative parts of Deodhar’s Northeastern journey. They gave her the opportunity to rapidly turn ideas into working prototypes with real-world impact while collaborating with talented peers under intense pressure.
At the Confluent AI Day 2025 Hackathon, Deodhar and her team earned 2nd place overall with their project “SecureStream AI”: a real-time streaming app that detects sensitive data (PII/PHI), assesses privacy risks and recommends sanitization before information reaches AI models. Built using Confluent Cloud, Kafka, Flink and MongoDB, the solution transformed live data into actionable, secure insights. The fast-paced three-hour sprint taught her how to quickly translate real-world problems into functional solutions, collaborate effectively under pressure and leverage cutting-edge streaming technologies to build AI that prioritizes user privacy.
At the DreamAI 2025 Hackathon, her team was selected as finalists for “FinFluent”, an AI-powered personal finance assistant that helps users manage money through natural language interactions and data visualizations. Developed with Streamlit, OpenAI and PerplexityAI, the project was pitched to a panel of investors and industry leaders. Through this experience, Deodhar learned how to transform a problem into a viable product, craft and deliver a compelling pitch, and build AI tools that genuinely improve people’s lives.
She also participated in the MIT Women’s Health AI Hackathon, where her team developed a conversational agent to address critical gaps in women’s health data. With women representing nearly half the world’s population but less than 5% of medical research data, the project was both technically challenging and socially impactful. Working in such a dynamic and collaborative environment reinforced the importance of teamwork and shared purpose.
These hackathon experiences strengthened what she learned at Northeastern: courses provided the technical foundation, faculty offered mentorship, and hackathons became the playground where she could creatively apply her skills to real-world challenges.
Future Perspectives
Deodhar aspires to continue working at the intersection of AI and systems, particularly in areas like healthcare, education, and social impact, where technology can truly make a difference. She will be graduating in December 2025 and is beginning to explore full-time opportunities where she can combine her skills, experience, and passion for solving meaningful problems.
Deodhar shares that what stands out most about her Northeastern experience is the balance of technical rigor and community. From faculty who challenged her to think critically, to peers who constantly inspired her and opportunities like hackathons and co-op that pushed her to grow, she reflects, “I will leave with not only strong skills, but also with the confidence and curiosity to keep learning and building.”