A Journey of Growth, Discovery, and Innovation
We are excited to share the next alumni spotlight: Tejal Ravindra Bhavsar, M.S. ’26, information systems. Tejal’s experience at UMBC demonstrates the power of combining industry expertise with academic research. As an M.S. in Information Systems student specializing in AI and Data Science, she explored emerging technologies, conducted impactful research, and developed solutions to address challenges faced by students and researchers. Her story highlights the innovation, collaboration, and lifelong learning that define the Department of Information Systems community.
Information Systems: Tell us about yourself and your journey at UMBC.
Tejal Ravindra Bhavsar: I’m Tejal Bhavsar, originally from Amalner, Maharashtra, India. I came to UMBC in August 2024 to pursue my MS in Information Systems with a specialization in AI and Data Science drawn by the program’s strong technical curriculum and its active research culture as an R1 university.
Before UMBC, I worked as a software engineer for 4 years, delivering full-stack systems for Siemens Technology, fintech startups in Mumbai, and most recently at Globant where I built LLM-powered pipelines to automate resume parsing and talent matching replacing inefficient manual review processes with production AI systems.
At UMBC, I transitioned from practitioner to researcher. Under the guidance of Professor George Karabatis an incredible mentor who kept me motivated throughout I completed my thesis: “Attention with Extra Context is All You Need: An Empirical Study on Enriching Embeddings via Explicit Context Injection,” exploring how context-aware AI embeddings improve model performance. I also competed in the 3-Minute Thesis competition, reaching the final round as the only master’s candidate among all PhD competitors.
Beyond academics, I built Academia Connect a full-stack platform solving a problem I personally experienced as an incoming student: missing research events, lab open houses, and collaboration opportunities due to poor information flow. I also served as a Conference Assistant and Orientation Advisor, helping new students navigate campus life.
UMBC transformed me from a software engineer into a researcher and AI builder, and I leave ready to pursue a career as a Full-Stack AI Engineer.
IS: How has UMBC and the IS Department helped prepare you for your future career?
TRB: UMBC and the IS Department prepared me not just technically but holistically. From AI and software engineering to databases, management information systems, cybersecurity, and data mining, every course pushed me to think like both an engineer and a researcher. The program kept me updated with the latest technology trends and helped me develop a strong research acumen which I applied directly in my thesis on context-aware AI embeddings. I leave feeling genuinely confident in my skillset and ready to dive into full-time work.
IS: What experiences, projects, or opportunities have been most meaningful during your time at UMBC?
TRB: A few experiences stand out. Building Academia Connect for my Advanced Software Engineering course was deeply meaningful because it solved a real problem I personally faced as an incoming international student I missed lab open houses, research events, and networking opportunities simply due to lack of awareness I developed Academia connect to resolve the issue of missed opportunities in campus and providing platform for student and professor to find right talent. Competing in the 3-Minute Thesis competition and reaching the final round as the only master’s candidate among PhD students was a defining moment. Serving as a Conference Assistant and then an Orientation Advisor let me give back to the community that welcomed me. And working under Professor Karabatis on my thesis connected everything research, AI, and purpose.
IS: Have you participated in experiences outside the classroom connected to your field?
TRB: Yes, I actively participated in webinars, tech talks, and networking events across the DMV area throughout my time at UMBC. Staying connected to the broader tech community helped me keep pace with rapidly evolving AI trends and build meaningful professional relationships beyond campus.
IS: Describe a project, internship, research experience, or role you are most proud of.
TRB: I am most proud of two things. First, my thesis in AI which explores how enriching AI embeddings with explicit context improves model understanding, sitting at the intersection of LLMs, RAG, NLP, and embedding models. Second, Academia Connect a full-stack platform I built using React, TypeScript, Python, and PostgreSQL that bridges the communication gap between students and professors at UMBC, enabling research collaboration and event discovery. I also interned at UpRobotics, an AI and robotics startup, where I used my software engineering background to teach younger kids as an AI and robotics intern.
IS: What tools, technologies, or skills have you used throughout your academic or professional experiences?
TRB: React, TypeScript, Next.js, Python, Node.js, LLMs, RAG, LangChain, Prompt Engineering, Embedding Models, GenAI Pipelines, FastAPI, PostgreSQL, MongoDB, Docker, AWS, CI/CD, GitHub Actions, TensorFlow, scikit-learn, Figma, Agile/Scrum.
IS: What advice would you give to current or future students?
TRB: Explore as much as you can. UMBC has an incredible range of opportunities research labs, networking events, competitions, campus roles and they will genuinely amaze you. Don’t wait for things to come to you. Show up, stay curious, and connect with the people around you.
IS: Which skill or area are you most excited to continue developing after graduation?
TRB: I am most excited about deepening my expertise in LLMs, RAG pipelines, and agentic AI systems. I also want to grow as a full-stack AI engineer building end-to-end intelligent applications and eventually move into an AI Product Manager role where I can bridge engineering and product strategy.
IS: What are your career goals or roles you are you interested in pursuing?
TRB: I am interested in roles as a Software Engineer, AI Engineer, Full-Stack AI Engineer, Agentic AI Developer, or AI Product Manager. My goal is to build intelligent, human-centered AI applications that solve real problems combining my engineering background with the research thinking I developed at UMBC.
To learn more about Tejal and her work, connect with her on LinkedIn and visit her webpage.
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