School of Engineering
Showing 1-100 of 118 Results
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Ramtin Keramati
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2015
Current Research and Scholarly InterestsReinforcement Learning, Deep Learning, Human in the Loop Reinforcement Learning
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Suleyman Kerimov
Ph.D. Student in Management Science and Engineering, admitted Autumn 2016
BioSuleyman Kerimov is a Ph.D. student in the Department of Management Science & Engineering at Stanford University.
Research Area: Operations Research -
Asir Intisar Khan
Ph.D. Student in Electrical Engineering, admitted Autumn 2018
Grader for EE223, Electrical Engineering - Student ServicesCurrent Research and Scholarly InterestsMy research focuses on the thermal engineering, fabrication, and characterization of novel phase change heterostructures (PCH) for high density, low-power data storage both on the flexible and non-flexible platform. My research further expands into the fabrication and characterization of PCH for thermoelectrics and low-power solid-state flexible reflective display. I am also working on the real-time characterization of fast temperature sensors using atomically thin two-dimensional materials.
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Moo Jin Kim
Masters Student in Computer Science, admitted Autumn 2020
BioMoo Jin Kim is a master's student in Computer Science at Stanford University who is concentrating primarily in Artificial Intelligence, with a secondary focus on Systems. He plans to complete the master's program by the spring of 2022.
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Sungjin Kim
Ph.D. Student in Electrical Engineering, admitted Autumn 2016
BioSung-Jin received his B.S. and M.S. in Electrical Engineering from KAIST in 2008 and 2010 respectively, and he is currently a Ph.D. student in Electrical Engineering at Stanford University. Prior to starting the PhD program, he worked for Samsung Electonics from 2010 to 2016. He is interested in synthesizable analog circuits and automated design flow for high speed serial links(SerDes). He is currently working for the Open Source Phy project.
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Allison Koenecke
Ph.D. Student in Computational and Mathematical Engineering, admitted Autumn 2016
Masters Student in Computational and Mathematical Engineering, admitted Autumn 2020BioI am a PhD candidate in the Institute for Computational and Mathematical Engineering (ICME). Prior to joining the Stanford community, I worked at NERA Economic Consulting in New York, where I specialized in data work with applications to antitrust litigation and mergers. I am originally from the DC area and received my Bachelor's in Mathematics with Computer Science from MIT. Previous internships include data science roles at Facebook, Google, and Microsoft.
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Fikunwa Kolawole
Ph.D. Student in Mechanical Engineering, admitted Summer 2019
Masters Student in Mechanical Engineering, admitted Winter 2021BioPh.D. student in the Mechanical Engineering Department. Focus on using Magnetic Resonance Imaging to study Cardiovascular Biomechanics. Using experimental methods and computational models to develop a platform to quantify myocardial mechanical properties to provide clinical tools for cardiovascular disease diagnoses and treatment progression.
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Neha Konakalla
Masters Student in Computer Science, admitted Autumn 2019
BioAI | Mobile | Web | Speech | Software Developer
I am a highly self-motivated and enterprising third-year undergraduate student whose primary interests involve interdisciplinary research in artificial intelligence, linguistics, and psychology to help individuals, especially those with special needs, improve their language and communication skills.
I have always been fascinated by linguistics, even at a young age. In the eighth grade, I was a championship finalist (top 10) in the Scripps National Spelling Bee out of 11 million students worldwide, after 5 years of hard work and dedication. Later on, in high school I began merging my interests in linguistics with artificial intelligence and psychiatry, developing and "bringing the heart" to innovative conversational technologies to improve the lives of individuals.
Over the past four years, I've been the creator and developer of BuddyBot, a voice-based AI trainer companion to improve conversational skills and socio-communicative ability in autistic individuals. On the psychiatric side, I've been a member of the Fung Lab (http://med.stanford.edu/funglab.html) at the Stanford Psychiatry and Behavioral Sciences Department since 2017 for human subjects research (data collection, clinical trials) to train and evaluate BuddyBot. BuddyBot has also been entered into the 4-year, $5M IBM Watson Artificial Intelligence XPRIZE, and has been fortunate to have been selected among the top 30 out of 683 teams for Round 2 of the contest (http://ai.xprize.org). Additionally, in May 2019, BuddyBot was featured at the United Nations AI For Global Good Summit in Geneva, Switzerland.
--Technology Skills--
-Reinforcement Learning (q-learning, policy gradient learning)
-Machine Learning (K-means clustering, markov models, regression, classfication)
-Deep Learning (artificial, convolutional, and recurrent neural networks)
-Natural Language Processing (semantic parsing, sentiment analysis, POS tagging, semantic similarity, information retrieval)
-Data Science (data scraping and collection, data structure and databases, exploratory data analysis and visualization, Bayesian statistics, regression methods, forecasting)
-Neo4j Graph Databases
-IBM Watson, IBM Cloud (Speech-to-text, Text-to-speech, Database Services, Unix Servers, Natural Language Processing, Data Science Experience)
-iOS Development (Xcode, Swift)
-Android Development (Android Studio, Java)
-Python Flask and Django Web Development
-Java Projects (computer games, reading smartphone sensor data)
-Arduino and Sensors
-3D Engineering Design (Autodesk Inventor)
--Programming Languages--
Python, C++, C, Swift, Java, HTML, SQL, Cypher -
Taeyoung Kong
Ph.D. Student in Electrical Engineering, admitted Autumn 2017
BioTaeyoung is a Ph.D. student at Stanford University working with prof. Mark Horowitz in VLSI group and he is currently working within the AHA Agile Hardware Project. He is interested in hardware accelerator for deep learning / image processing and hardware design methodology. Taeyoung received a B.S. in Electrical and Computer Engineering from Seoul National University in 2017, and M.S. in Electrical Engineering from Stanford University in 2020.
