Rituja Bhattacharya - ECE PhD Student of the Month - January 2026
Rituja Bhattacharya is a second-year PhD student in the ECE department at NJIT, advised by Dr. Cong Wang. Her research focuses on minimalist robotic manipulation for domestic services, motivated by everyday tasks such as cooking, prioritizing durability and affordability. She has also developed general prompting techniques for AI-assisted tool reasoning and design. Rituja's current work largely focuses on dexterous in-hand manipulation using reinforcement learning and evolutionary optimization methods, with the overarching goal of reducing dimensionality and decision complexity while preserving robustness and generalization. In addition to her research, she is a Teaching Assistant in the ECE department and, continuing from last semester, she is instructing ECE 429: Computer Communications laboratory in the Spring semester. Beyond academics, she says she finds peace in nature, whether in forests, mountains, or along the coast. She enjoys exploring new places and visiting museums and state parks. She also finds comfort in poetry and literature, and considers singing and dancing joyful and grounding forms of expression.
What would you say that could be the next big thing in your area of research?
The next major shift in robotics could likely be towards systems where intelligence, hardware, and tools are designed together, favoring deliberately simple hardware that is aided by AI and LLM-based reasoning rather than only complex mechanical designs, with a strong emphasis on affordability and durability. At the same time, progress will come from learning a small set of reusable low-level behaviors that can be combined in different ways to solve new tasks, instead of retraining an entire system from scratch each time. LLMs will not only act as controllers but also as reasoning layers, organizing skills, selecting tools, and adapting strategies as task context changes. Overall, the emphasis will be on low-cost, replaceable, and durable systems, with AI-driven reasoning playing a central role in both design and decision-making.
You took ENGL 621 Technical Writing for Graduate Students at the beginning of your PhD study. How do you find it helpful to your writing of research paper?
Yes, I took the ENGL 621 Technical Writing for Graduate Students taught by Dr. Paris at the very beginning of my PhD. It was a unique and refreshing course, and an especially important one, as it is where I learned the specific style of technical writing that has been instrumental in my subsequent paper-writing efforts. Dr. Paris emphasized and instilled the habit of reading scientific articles, which forms essential groundwork for PhD research, and provided guidance on how to read papers efficiently and critically. It also helped me understand the subtle differences between sentence structure in technical and non-technical contexts, offering insight into the nuanced art of technical sentence construction, which I have been consciously incorporating into my research writing ever since.
More and more people are using AI to speed up their work. Some say it's becoming a must-have skill. Please share your experience on using AI tools to assist research.
As AI tools have become more common in professional workflows, simply having access to them is no longer the main challenge. What matters more is knowing how to use these tools effectively and responsibly to get real value from them. I have come to appreciate the importance of natural language prompting, since the quality of an AI’s response depends heavily on the quality of the input, and I have become fairly proficient at this through practice. Without thoughtful use, AI on its own offers limited benefit. With this perspective, I approach AI not as a shortcut, but as a tool to be used deliberately to support my learning. I use AI tools primarily as a personal assistant to accelerate understanding, rather than as a replacement for my own thinking. In my studies, AI is especially useful as a guide for learning complex concepts, helping me build intuition around topics and clarify concepts from papers and theories. This is particularly effective when combined with domain knowledge in programming or computing, as it allows me to ask precise, technical questions and critically evaluate and edit its responses instead of accepting them at face value. I also use AI as a search tool to efficiently find relevant papers and articles. Beyond academics, one of the most practical ways I use AI is in everyday life, especially for cooking, where it helps me find, generate, and adapt lunch or dinner recipes to suit my preferences. I then cook these for myself, which has become a personal, ongoing daily "research" project in its own right! Overall, when used thoughtfully and ethically, AI has become an effective productivity and learning aid that complements research practices while also serving as a helpful assistant in daily life.