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186 | 186 | \section{Education} |
187 | 187 |
|
188 | 188 | \begin{twocolentry}{ |
189 | | - 09/2022 -- Present |
| 189 | + 09/2022 -- 05/2027 (Expected) |
190 | 190 | } |
191 | 191 | \textbf{The Chinese University of Hong Kong, Shenzhen}\\ |
192 | | - Major in Computer Engineering |
| 192 | + Major in Electrical and Computer Engineering |
193 | 193 | \end{twocolentry} |
194 | 194 |
|
195 | 195 | \vspace{0.10 cm} |
196 | 196 | \begin{onecolentry} |
197 | 197 | \begin{highlights} |
198 | | - \item Cumulative GPA: 3.85/4.0 (Rank: 5/268 in School of Science and Engineering) |
| 198 | + \item Cumulative GPA: 3.849/4.0 (Rank: 5/268 in School of Science and Engineering) |
199 | 199 | \item Research Interests: Robot Learning, Reinforcement Learning, Deep Learning |
200 | 200 | \item Awards \& Honors: Creativity and Innovation Award, 2024; Academic Scholarship, 2023 \& 2024; \\ |
201 | 201 | Dean's List, 2023 \& 2024 \& 2025 |
|
208 | 208 | 08/2024 -- 12/2024 |
209 | 209 | } |
210 | 210 | \textbf{University of California, Berkeley}\\ |
211 | | - Visiting Program |
| 211 | + Visiting Student |
212 | 212 | \end{twocolentry} |
213 | 213 |
|
214 | 214 | \vspace{0.10 cm} |
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235 | 235 | \vspace{0.10 cm} |
236 | 236 | \begin{onecolentry} |
237 | 237 | \begin{highlights} |
238 | | - \item Aimed to design efficient reinforcement learning algorithms enabling humanoid robots to walk on complex terrains |
239 | | - \item Conducted simulations using IsaacLab, optimized observation space and reward design, and designed a Learn-to-Teach training framework, achieving promising results in simulation environments |
240 | | - \item Planning to deploy the policy on real hardware and conduct a series of tests in real-world environments |
| 238 | + \item Aimed to develop efficient reinforcement learning algorithms enabling humanoid robots to walk on complex terrains |
| 239 | + \item Conducted simulations using IsaacLab, optimized observation space and reward design, and implemented a Learn-to-Teach using rsl\_rl, achieving good results in simulation environments |
| 240 | + \item Planning to switch from Digit to G1, add LiDAR as perception, and conduct a series of tests in real-world environments. |
241 | 241 | \end{highlights} |
242 | 242 | \end{onecolentry} |
243 | 243 |
|
|
246 | 246 | \begin{twocolentry}{ |
247 | 247 | 09/2024 -- 12/2024 |
248 | 248 | } |
249 | | - \textbf{UAV Path Planning and Attitude Control}\\ |
| 249 | + \textbf{UAV Attitude Control}\\ |
250 | 250 | Research Assistant; Supervised by Prof. Mark M. Mueller and Ruiqi Zhang\\ |
251 | 251 | High Performance Lab, UC Berkeley |
252 | 252 | \end{twocolentry} |
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262 | 262 | \vspace{0.2 cm} |
263 | 263 |
|
264 | 264 | \begin{twocolentry}{ |
265 | | - 09/2023 -- Present |
| 265 | + 09/2023 -- 08/2025 |
266 | 266 | } |
267 | 267 | \textbf{Smart Stop Snoring Pillow}\\ |
268 | 268 | Research Assistant; Supervised by Prof. Jian Zhu and Xuanyang Xu\\ |
|
272 | 272 | \vspace{0.10 cm} |
273 | 273 | \begin{onecolentry} |
274 | 274 | \begin{highlights} |
275 | | - \item Aimed to design and implement a smart pillow to achieve an anti-snoring effect by detecting the user's snoring and adjusting the pillow's height to keep the user's airway clear |
276 | | - \item Achieved precise control of the balloon's altitude using Poiseuille's principle to replace the flow meter with two barometers; Built an intermediate layer using ROS, achieving efficient communication between the upper computer and the microcontroller; Implemented Snoring Recognition with Spatio-Temporal Graph Neural Networks |
277 | | - \item Submitted to IEEE Transactions on Mechatronics (under review, second author) |
| 275 | + \item Designed and implemented a pneumatic robotic pillow that achieves non-invasive snoring mitigation by detecting snoring and adjusting the pillow height to keep the user's airway clear |
| 276 | + \item Achieved precise height control of the airbag using Poiseuille-based flow modeling with two barometers instead of a flow meter, and built a ROS-based middleware for reliable communication between the upper computer and the microcontroller |
| 277 | + \item Utilized only built-in pressure sensors to extract breathing and heart-rate signals via frequency analysis, and designed a Transformer–CNN multi-task network to jointly recognize posture, snoring, and apnea events; Submitted to IEEE Transactions on Mechatronics (under review, second author) |
278 | 278 | \end{highlights} |
279 | 279 | \end{onecolentry} |
280 | 280 |
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|
296 | 296 | \end{highlights} |
297 | 297 | \end{onecolentry} |
298 | 298 |
|
299 | | - |
300 | | - |
301 | 299 |
|
302 | | - \section{Internship and Competitions} |
| 300 | + \section{Internship} |
303 | 301 |
|
304 | 302 | \begin{twocolentry}{ |
305 | | - 04/2024 -- 08/2024 |
| 303 | + 12/2025 -- Present |
306 | 304 | } |
307 | | - \textbf{Shenzhen Research Institute of Big Data}\\ |
308 | | - Research Assistant; Supervised by Dr. Yangyang Peng and Dr. Yinjun Shen |
| 305 | + \textbf{Dexforce}\\ |
| 306 | + Research Intern |
309 | 307 | \end{twocolentry} |
310 | 308 |
|
311 | 309 | \vspace{0.10 cm} |
312 | 310 | \begin{onecolentry} |
313 | 311 | \begin{highlights} |
314 | | - \item Aimed to achieve efficient and accurate prediction of building loads, providing valuable information for power allocation |
315 | | - \item Extracted features using Fast Fourier Transform and constructed an LSTM-T-KAN model for long-term building load forecasting |
316 | | - \item Submitted to Applied Energy (under review, second author) |
| 312 | + \item Responsible for developing Vision-Language-Action (VLA) agents |
| 313 | + \item Built testing benchmarks for evaluation |
317 | 314 | \end{highlights} |
318 | 315 | \end{onecolentry} |
319 | 316 |
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320 | 317 | \vspace{0.2 cm} |
321 | 318 |
|
322 | 319 | \begin{twocolentry}{ |
323 | | - 07/2024 -- 09/2024 |
| 320 | + 04/2024 -- 08/2024 |
324 | 321 | } |
325 | | - \textbf{2nd Prize in the Chinese Undergraduate Physics Experiment Competition}\\ |
326 | | - Team Leader; Supervised by Prof. Xiaolu Zhuo, Prof. Chaorui Li, and Dr. Edward Chen |
| 322 | + \textbf{Shenzhen Research Institute of Big Data}\\ |
| 323 | + Research Intern; Supervised by Dr. Yangyang Peng and Dr. Yinjun Shen |
327 | 324 | \end{twocolentry} |
328 | 325 |
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329 | 326 | \vspace{0.10 cm} |
330 | 327 | \begin{onecolentry} |
331 | 328 | \begin{highlights} |
332 | | - \item Proposed a real-time synchronous measurement scheme for steady and alternating weak magnetic fields in a double solenoid based on the giant magnetoresistance effect and digital lock-in amplification technology |
333 | | - \item Submitted team paper to Physics Experiment journal |
| 329 | + \item Aimed to achieve efficient and accurate prediction of building loads, providing valuable information for power allocation |
| 330 | + \item Extracted features using Fast Fourier Transform and constructed an LSTM-T-KAN model for long-term building load forecasting |
| 331 | + \item Submitted to IEEE Transactions on Neural Networks and Learning Systems (under review, second author) |
334 | 332 | \end{highlights} |
335 | 333 | \end{onecolentry} |
336 | 334 |
|
| 335 | + |
337 | 336 | \section{Activities} |
338 | 337 |
|
339 | 338 | \begin{twocolentry}{ |
|
350 | 349 | \end{highlights} |
351 | 350 | \end{onecolentry} |
352 | 351 |
|
| 352 | + \vspace{0.2 cm} |
| 353 | + |
| 354 | + \begin{twocolentry}{ |
| 355 | + 07/2024 -- 09/2024 |
| 356 | + } |
| 357 | + \textbf{2nd Prize in the Chinese Undergraduate Physics Experiment Competition}\\ |
| 358 | + Team Leader; Supervised by Prof. Xiaolu Zhuo, Prof. Chaorui Li, and Dr. Edward Chen |
| 359 | + \end{twocolentry} |
| 360 | + |
| 361 | + \vspace{0.10 cm} |
| 362 | + \begin{onecolentry} |
| 363 | + \begin{highlights} |
| 364 | + \item Proposed a real-time synchronous measurement scheme for steady and alternating weak magnetic fields in a double solenoid based on the giant magnetoresistance effect and digital lock-in amplification technology |
| 365 | + \item Submitted team paper to Physics Experiment journal |
| 366 | + \end{highlights} |
| 367 | + \end{onecolentry} |
| 368 | + |
353 | 369 | \section{Skills} |
354 | 370 |
|
355 | 371 | \begin{onecolentry} |
356 | | - \textbf{Technologies \& Frameworks:} PyTorch, Tensorflow, Pybullet, ROS, SIMD/OpenMP, IsaacLab |
| 372 | + \textbf{Technologies \& Frameworks:} PyTorch, Tensorflow, IsaacLab, Pybullet, ROS, SIMD/OpenMP, Linux, Git, Docker |
357 | 373 | \end{onecolentry} |
358 | 374 |
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359 | 375 | \vspace{0.2 cm} |
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