If you've spent hours online searching for the secret to a perfect graduate school personal statement, you've likely found a lot of generic advice like "Be yourself!" or "Show your passion!", "Highlight your strengths!". While well-intentioned, this vague guidance won't help you craft a statement that makes the admissions committee take notice.
There's no magic formula for writing a personal statement that guarantees acceptance, but you don't need one. The key to a standout statement boils down to just 5 essential principles. These are the fundamental building blocks of the most compelling statements.Â
Now let's look at actual graduate personal statements that got into CMU and UC Berkeley
‍Personal statement #1 : CMU Robotics‍
Growing up in a small town in India, I witnessed many people getting injured while taking up precarious jobs such as mining and construction work. My mother, a surgeon, recounted to me her experiences when a surgery was too complicated or the time too limited to be successfully completed by human hands. I believe that if robots can manipulate and perceive objects effectively and take decisions as cleverly as humans do, they can replace us. Sadly, this is not possible today, even with state-of-the-art technology. This has motivated me to pursue research in robotics as a career. My strong foundations in electronics and computer science, exposure to systems engineering, and projects and research experiences in robotics make me a viable candidate for the Master of Science in Robotics program. Following this, I plan to pursue a PhD in robotics and work as a researcher to fulfill my life-long dream.
Since childhood, I was fascinated by gadgets and autonomous machines. As I enjoyed hands-on learning, I joined an aero-modelling club at my school at the age of 14, where I modeled balsa wood gliders and flew RC diesel engine gliders. As my interest grew, I started designing and building small RC boats. My first encounter with a real robot was when one of my friends bought a Lego Mindstorms kit, and we started programming the tiny humanoid to react to haptic and audio inputs. The limited behavior that we could program made me appreciate the mechanical and behavioral complexity of robots like Honda’s Asimo.
I developed my background in Electronics and Computer Science after joining the bachelor’s program in Electronics and Communication Engineering. The study of electronic circuits, embedded systems, and signal processing coupled with courses in data structures, algorithms, networks, and pattern recognition has enabled me to work at the confluence of computer science and electronics.
I built upon my foundations in embedded systems and systems engineering when I was selected as a member of Team Gaganyaan, which represented the institute at Cansat 2010, a NASA-sponsored international competition. It involved the compilation of a preliminary design review, a critical design review, and a post-flight review. This helped me grasp the methodical approach to problem-solving and the process of fashioning devices with compliant mechanical and electronics subsystems. As part of multiple sub-teams, I learned the importance of coordination and team dynamics. Ours was the only Cansat that accomplished all the objectives, and we finished first among 16 teams from across the world. I further cultivated my skills by leading Team Gaganyaan at Cansat 2011. My responsibilities were to coordinate various sub-teams and deliver design presentations during the preliminary and critical phases. We finished in third position among twenty international teams.
To delve deeper into robotics, I joined the honors program in robotics under a professor, Head of the Robotics Lab. As a team leader, along with three other members, I proposed a design for the Defence Research and Development Organization's (DRDO, Government of India) Student Robot Challenge, a scaled-down version of the DARPA challenge. Our proposal was among the top fourteen, selected from over 240 entries from all over India. We implemented the mechanical and autonomous behavior of the robot based on research papers we found as well as probabilistic techniques learned during our coursework. Working overtime to develop both the software and hardware from scratch within three months made me aware of the challenges posed in comprehensive system development. But the experience of building something, programming complex behavior, and watching it work as expected in a real-world scenario gave me immense satisfaction.
I complemented my projects with relevant courses in which I excelled. In the Mobile Robotics course, I learned the effectiveness of probabilistic techniques to deal with uncertainty and noise, which is inherent in real-world sensors and actuators. I also became familiar with various techniques for mapping and localization in a well-formulated and principled manner. Following this, I took the course Introduction to Robotics, adding manipulator kinematics, dynamics, and various control techniques to my repertoire. I also audited the Computer Vision course to learn about multi-view geometry and structure from motion, which helped me to get an insight into VSLAM algorithms.
My experiences motivated me to undertake core research in robotics. Building upon my encounter with aerial vehicles from my school's aero-modelling days and after hearing about recent developments in the use of quad-rotors, my project partner and I started implementing vision-based tracking of a ground robot by a quad-rotor. This prompted us to work towards building a collaborative system consisting of these two robots. During the summer, I carried out a literature survey to analyze the limitations and strengths of laser-based 2D SLAM and VSLAM algorithms. Going through a recent paper, I realized how cameras and lasers can complement each other for accurate 6D SLAM. With this inspiration, we proposed a novel system consisting of a ground robot (UGV) with a laser scanner used to build accurate 2D maps of the ground plane, and a quad-rotor with a vertical camera to create 3D point clouds (using Klein’s PTAM) of elevated regions not accessible by the UGV. While the quad-rotor mapped an elevated region, its 6D pose was tracked by the UGV, which allowed us to induce scale into the PTAM algorithm. The maps hence built were accurate, had exact scale, and were more comprehensive than just 2D maps. Analyzing the problem of mapping an indoor environment, doing a literature survey to find out the limitations of current approaches, proposing a novel system that addresses some of these problems, implementing the system using Robot Operating System (ROS), and finally submitting a paper at the Eleventh International Conference on Automated Agents and Multi-Agent Systems in 2012 gave me a glimpse of how exciting research can be.
My research interests lie in developing AI for robotics, control theory, and robotic vision, especially for mobile robots. In order to develop robots that can actually move out of research labs, interact with humans, and replace them in hazardous or complex tasks, further effort in enhancing cognition, perception, and action is required. The research at the Robotics Institute is precisely aimed at this, and I have found that one professor’s research interests in mobile robots closely match my own. His PerceptOR project is similar to my major project in that both use a UGV and a UAV in collaboration to improve the system’s performance. Also, another professor's focus on building robots that can operate in unstructured or hazardous environments is quite akin to my ultimate goal.
As part of my major project, I have dealt with robotic vision and SLAM and would now like to explore cognition and manipulation as well. The master’s program at the Robotics Institute provides me with an ideal ground to do so, as it lays great emphasis on diversity through its core courses. It will also equip me with the appropriate skills and research experiences to solve newer and tougher problems in a holistic and formal manner. I believe I can contribute innovative ideas to my research group and add vibrancy to the university campus, creating a mutually rewarding relationship for both of us.
GradGPTÂ evaluation of this personal statement:
Personal statement #2 : PhD, UC Berkeley
There exist a lot of tasks in the world which are hazardous or too complex to be completed by humans. I believe that if robots can manipulate and perceive objects effectively and take decisions as cleverly as humans do, they can replace us. Sadly, this is not possible today, even with state-of-the-art technology. This has motivated me to assail research in robotics as a career. My strong foundations in electronics and computer science, exposure to systems engineering, and projects and research experiences in robotics make me a viable candidate for the M.S. or PhD program in EECS at UC Berkeley. Following this, I plan to work as a researcher in an academic setting to fulfill my life-long dream.
I developed my background in Electronics and Computer Science after joining the bachelor’s program in ECE at [University]. The study of electronic circuits, embedded systems, and signal processing coupled with courses in data structures, algorithms, networks, and pattern recognition has enabled me to work at the confluence of computer science and electronics.
To delve deeper into robotics, I joined the honors program under Professor [Name], Head of the Robotics Lab. I was selected for [Organization]’s Student Robot challenge, a scaled-down version of the DARPA challenge. We implemented the mechanical and autonomous behavior of the robot based on research papers and probabilistic techniques learned during coursework. Working overtime to develop both the software and hardware from scratch within three months made me aware of the challenges posed in comprehensive system development.
I complemented my projects with relevant courses such as Mobile Robotics, where I learned the effectiveness of probabilistic techniques in dealing with uncertainty and noise which is inherent in real-world sensors and actuators. In Introduction to Robotics, I added manipulator kinematics, dynamics, and control techniques to my repertoire. I also audited the Computer Vision course to learn about multi-view geometry and structure from motion, which helped me to get an insight into VSLAM algorithms.
My experiences motivated me to undertake core research in robotics. For our major project, my project partner and I implemented vision-based tracking of a ground robot by a quad-rotor. I carried out a literature survey to analyze the limitations and strengths of various SLAM algorithms. Finally, we proposed a novel collaborative system consisting of a UGV and a quad-copter, which can build augmented maps that are better than just 2D maps. Analyzing the problem, doing a literature survey to find out the limitations of current approaches, proposing a novel system that addresses these problems, implementing the system using Robot Operating System (ROS), and finally submitting a paper at [Conference] gave me a glimpse of how exciting research can be.
My research interests lie in developing AI for robotics, control theory, and robotic vision, especially for personal robots. In order to develop robots which can interact with humans and replace them in hazardous or complex tasks, further effort in enhancing cognition, perception, and manipulation is required. The robotics research at the EECS department is precisely aimed at this, and I have found that Prof. Pieter Abbeel’s research interests in service robots closely match my own. I am really interested in his work on surgical robots which can help reduce surgeon tedium and duration of operations. Also, Prof. Claire Tomlin’s work on the STARMAC project, especially the use of LBMPC for quad-copter control, interests me to a great extent.
Until now, I have dealt with robotic vision and SLAM and would now like to explore surgical robots, milli-robots, and hybrid control theory as well. The PhD program in EECS at UC Berkeley provides me an ideal ground to do so, as a variety of projects and excellent faculty will be available for my guidance. It will also equip me with the appropriate skills and research experiences to solve newer and tougher problems in a holistic and formal manner. On the other hand, if I am selected for the M.S. program, it will give me an opportunity to lay the foundations for a PhD by writing a research thesis via Plan 1. I believe I am highly motivated and ready to face the challenges of graduate studies and robotics research. I can contribute innovative ideas to my research group and add vibrancy to the university campus, creating a mutually rewarding relationship for both of us.
GradGPTÂ evaluation of this personal statement:
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Essay Coach Feedback:
Since these are graduate level personal statements, writing style might not be a decisive factor, but engaging writing certainly enhances the overall impact.
This glimpse into successful applications at CMU and UC Berkeley provides inspiration.
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